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i. Strategen responded that the first scenario will not be as cost sensitive as the third scenario, meaning the results are likely to look different. The third scenario will take the lowest-cost option to comply with California’s clean energy mandate, including the use of renewable energy credits (RECs) when cheapest. The first scenario won’t include as much of a reliance on RECs. The first scenario could also go ‘above and beyond’ California’s mandate by achieving 100 percent clean energy slightly faster, potentially at an incrementally higher cost. The third scenario would likely not do that, because it would always opt for the lowest-cost resource selection. ii. Strategen also clarified a question raised at the third Townhall about the use of RECs in GWP’s third scenario. The question had asked whether that strategy might ultimately be more expensive than GWP developing clean energy itself, given the increasing social cost of carbon and price of RECs. Strategen explained that GWP’s third scenario doesn’t prioritize the use of RECs above all other strategies; it prioritizes the lowest-cost option. The hypothesis going into this scenario is that there are likely to be cases where purchasing RECs is cheaper than GWP developing clean energy itself. But if it turns out that isn’t the case, then the model will select the new clean energy development instead. While the social cost of carbon is increasing over time, the most salient carbon price for this scenario is actually the CARB carbon price (the price at which RECs are sold), given this is the price GWP will have to pay for using resources that emit greenhouse gases. b. One member asked where the CARB prices being used in the model came from. In Ascend’s ‘key assumptions’ spreadsheet (which was shared with members before the meeting), the carbon price listed seems lower than the allowance price reached at a recent sale. They said they weren’t familiar with the details of that auction, but saw that allowances sold for more than the stated CARB carbon price for this year. i. Ascend responded that it wasn’t familiar with this particular sale, but that their assumptions on CARB’s carbon price are aligned with the floor price, because historically the market has cleared at that price. That floor price grows exponentially year over year. Polling exercise and discussion on STAG Scenario 3 1. Strategen conducted a poll of the STAG to gauge their interest in potential directions to take for STAG Scenario 3. These were used as a starting point for discussion among the group. 2. The poll asked members to reflect on elements that are missing from existing scenarios that they might want to test in STAG 3; elements from existing scenarios that they’d like to include in STAG 3; the year at which STAG 3 should achieve 100 percent clean energy; and whether there should be an interim clean energy target before reaching 100 percent. 3. See STAG Meeting 5 Presentation slides 14–16 (starting on page C-100). 4. After STAG took the poll, discussion included the following: a. Some members wanted to see a scenario that reflects the life cycle environmental impacts of resources being evaluated, like electric vehicles, and how that might impact customer adoption. i. Strategen responded that a life cycle analysis is not possible in the IRP, but that STAG could opt to assume that fewer customers adopt EVs than GWP anticipates. 731 of 839
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ii. Strategen also noted it can add this idea to the ‘parking lot’ of topics that have been raised by STAG, but that aren’t possible to integrate in the IRP, for report out at a later date. b. One member suggested adopting 2040 as a compromise 100 percent clean energy year, given that the group was fairly split in its preference. (A majority of members favored a 100 percent clean energy date between 2040 and 2045, with no year having a majority.) Other members seemed to agree with this suggestion. c. One member suggested the group take an approach suggested by some attendees at the third Townhall, which would result in a more moderate version of STAG’s Scenario 1 (relaxing some of the emphasis on customer-sited resources and doing so with a 100 percent clean energy date between 2035–2040). i. This member emphasized the importance of taking direction from Townhall attendees given that people go out of their way to come to Townhalls, especially the last one which was held on a Saturday. They noted that, while GWP might say STAG was chosen to be representative of Glendale, it is not actually representative. There are only three women and one person under the age of 40 in STAG. They stated Townhalls often have different demographics, with younger attendees and more renters than STAG. d. One member suggested adopting more conservative estimates on distributed energy resources (DERs) than are being assumed in GWP’s scenarios to model what the impact would be if customer DER adoption was lower than anticipated. i. Several members pushed back on this idea, saying that GWP’s scenarios already take a ‘conservative’ view on DER adoption and STAG’s scenarios should explore higher assumptions. 5. After the group discussed these points and a handful of ideas emerged, Strategen launched an addition to its original poll and asked the group to vote on the ideas raised for STAG 3. a. See the results of these two questions (questions 5 and 6) on STAG Meeting 5 Presentation slides 23–24 (starting on page C-100) Outcomes of the meeting 1. STAG agreed on a third scenario with the following characteristics: a. Achieving 90 percent clean energy by 2035 and 100 percent by 2040. b. Developing 75 MW of distributed energy resources by 2040. (This is a lowering of the DER requirements in STAG’s Scenario 1. STAG 1 will model 100 MW of DERs, per Council goal.) 732 of 839
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Next steps 1. Strategen will send a survey to STAG to decide on the detailed assumptions going into all three STAG scenarios. Once results are received (and shared with STAG), Strategen will send these assumptions to Ascend to begin modeling. 2. Strategen, Ascend, and GWP are compiling a public ‘key assumptions’ spreadsheet, following a request at the last Townhall, which will outline major data points driving Ascend’s model. This document has already been shared with STAG, but additional time will be provided for STAG review and questions before it is finalized. Strategen will be organizing optional STAG office hours for members to ask questions on both this document and the assumptions survey. 733 of 839
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STAG Meeting 5 Presentation Ascend presented initial results from the modeling of two of GWP’s scenarios: the California policy scenario and the Glendale goal scenario (slides 3–13). Strategen then presented a summary the third Townhall (slide 14), introduced the addition of a third STAG scenario (slides 15–16), and presented the results of the STAG poll about elements to include in the third STAG scenario (slides 17–26).
+ + + + + + + + + + + + + + ++ + + + + + + + + + + + + + ++ + + + + + + + + + + + + + ++ + + + + + + + + + + + + + ++ + + + + + + + + + + + + + ++ + + + + + + + + + + + + + ++ + + + + + + + + + + + + + ++ + + + + + + + + + + + + + ++ + + + + + + + + + + + + + + September 6, 2023
GWP 2024 Integrated Resource Planu
Stakeholder Technical Advisory Group meeting 5
2 Agenda+Initial results of GWP scenario modeling (55 min)+Presentation from Ascend Analytics (20 min)+Q&A (35 min)+Readout from community townhall and poll on STAG scenario 3 (10 min)+Break (10 min) +Full-group discussion on STAG scenario 3 (60 min)+Finalization of STAG 1 and 2 scenario details (30 min) +High-level overview and discussion of Ascend’s key assumptions spreadsheet (10 min) 3 Objectives for this meeting
+Present initial results of the modelingof GWP’s scenarios for discussionand feedback+Finalize details of all STAG scenarios,including the new STAG scenario 3 4 Initial modeling results
+DISCLAIMER: All results presented in the following slides are preliminary. The data included here will change before results are finalized for inclusion in the IRP.+The slides present initial results from two of GWP’s scenarios:+California policy: 100% zero-carbon energy by 2045+Glendale goal: 100% clean energy by 2035 5 CA Policy Resource Buildout
0102030405060708090100
2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 Nameplate Capacity (MW)
4 Hour StorageGeothermalWindSolar
GWP relies on solar and wind generation to meet RPS and clean energy goals while 4hour storage provides capacity
6 0
50 100
150
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250
202720282029203020312032203320342035
Nameplate Capacity (MW)
4 Hour StorageGeothermalWind8 Hour StorageHydrogen CT
Glendale Goal Resource BuildoutA combination of hydrogen generation and 8-hour storage to replace the carbon emitting resources - -
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7 Total New Resource AdditionsCA PolicyGlendale GoalWind240 MW250 MWSolar5 MWGeothermal50 MW50 MW4-hour storage205 MW165 MW8-hour storage25 MWHydrogen CT90 MWTotal500 MW580 MW 8 CA Policy Energy Mix
0%10%20%30%40%50%60%70%80%90%100%Percent of Energy Generation Axis TitleNuclearGeothermalWindSolarHydroCoalOtherNatural GasStarting in 2027, renewable generation becomes a substantial portion of GWP energy generation 9 CA Policy Clean Energy
0%20%40%60%80%100%120%RPS/Clean Energy percent of Retail Sales RPSClean Energy
100% Clean Energy
60% RPS
10 Glendale Goal Clean Energy
0%20%40%60%80%100%120%RPS/Clean Energy percent of Retail Sales RPSClean Energy
100% Clean Energy
60% RPS
11 Dispatchable Resource Capacity Factors
0%10%20%30%40%50%60%70%80%90%100%Capacity Factor
Grayson Unit 9 ICE - 54 MW IPP Repower with Hydrogen Magnolia IPP Converts to 100% Hydrogen
Reliance on natural gas generation declines through the 2020s 12 CA Policy Carbon Emissions
01234567
2024202520262027202820292030203120322033203420352036203720382039204020412042204320442045 Carbon Emissions (Million Tons)
Carbon emissions from GWP supply resources decline rapidly over the IRP period Q&A (35 min)
14 Readout from third community townhall+Several community members called for more transparency in the inputs and assumptionsdriving Ascend’s model.+One person asked for a public document to be released.+This is why Ascend has created its key assumptions spreadsheet to share publicly.+Multiple community members raised concern with GWP’s scenario 3 (CA mandate – leastcost) and called for replacing it with a third community scenario.+After discussion, GWP has decided not to eliminate its scenario 3 because some STAG memberswere interested in seeing an affordability-centered scenario.+Instead, GWP and Ascend are making a third scenario available to STAG, for a total of 6scenarios. 735 of 839
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15 Things to consider in developing STAG scenario 3+What gaps are left in current scenarios that STAG scenario 3 could fill in?+Is there any community input from townhalls that hasn’t been adequately integrated into current scenarios?+Can any of the current scenarios act as a basis for STAG scenario 3, with modifications?+For example, take the same assumptions on high local resource potential as STAG 1, but push the clean energy timeline back. 16 Reminder summary of scenariosScenario100% clean energy dateMeets CA mandateMeets Glendale goalBaseline assumption changesCA mandate2045X --Glendale 2035 goal2035XX--CA mandate – least cost2045X •Requires use of lowest-cost resources, which couldinclude RECs up to maximum limit.Local resources + accelerated electrification2035XX•Integrates all City Council clean energy goals.•Assumes maximum customer DER participation.•Assumes maximum utility-owned solar + storage inGlendale.•Assumes accelerated electrification.Middle path + long duration energy storage2042X •Assumes higher customer DER participation thanbaseline (lower than above).•Assumes higher utility-owned solar + storage inGlendale than baseline (lower than above).•Assumes LDES project developed in Glendale.
Poll on STAG scenario 3
18 Poll results – 1/6
19 Poll results – 2/6
20 Poll results – 2/6 (continued)
21 Poll results – 3/6
22 Poll results – 4/6
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Figure 93. STAG Meeting 5 Presentation Slides
23 Poll results – 5/6
Note: This question was asked after analyzing the results of question 3, in which most STAG responses favored a 100% clean energy date of 2040 or later. One member proposed a 2040 date as a compromise, which this poll was meant to gauge group opinion on. 24 Poll results – 6/6
Note: In this question “conservative DERs” meant conservative assumptions about customer adoption of distributed energy resources, below the assumptions GWP is making in its scenarios. “Elongated/slightly lower version of STAG 1” was shorthand for taking ambitious assumptions on customer DER adoption by 2035 and either elongating them (a similar MW target over more years) or lowering the customer adoption slightly. 25 Finalizing STAG scenarios 1 and 2 – detailed assumptions+Strategen will share the STAG scenario summary document, talk through suggestions, andtake STAG questions and comments.+STAG needs to decide on two assumptions:+Accelerated electrification assumption for STAG scenario 1+Clean energy definition for STAG scenario 2 26 Discussion on Ascend key assumptions spreadsheet+Strategen will share the spreadsheet and walk through it at a high level.+The spreadsheet will also be discussed at STAG office hours next week before beingreleased publicly.
Next steps in IRP process: STAGs, townhalls, etc.
27 +9/27: STAG meeting 6+Discuss draft IRP and the representation of the stakeholder engagement process in the report+Wrap-up STAG by soliciting feedback on IRP process and suggested improvements for next IRP+10/4: Townhall 4 (tentative)+Present modeling results to community for questions, discussion, feedback+Present GWP’s thinking on its preferred scenario +Discuss the representation of community input in the IRP draft+This townhall date may be pushed to the following week depending on modeling progress.+GWP Commission meeting+GWP will provide IRP updates at Commissionmeetings in October and November.+Glendale City Council updates+GWP is scheduled for an update to Council inlate September. 737 of 839
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STAG Meeting 6: Wednesday, November 1, 2023 STAG Meeting 6 Minutes Overall Takeaways 1. Ascend presented the modeling results from 5 of the 6 scenarios, with the exception of GWP’s third scenario, which will look largely the same as GWP’s first scenario, but with a portion of the renewable energy projects replaced with offsets. 2. The scenarios’ cost differ widely, with the price highly dependent on whether natural gas resources are being completely retired, or if they’re still able to run at very low capacity for reliability. The cost of transitioning natural gas units over to hydrogen is a significant portion of the costs for GWP 2 and all of STAG’s scenarios. 3. STAG, GWP, and its consultants continued to discuss the likelihood of some of the model’s technology assumptions becoming true, namely its assumptions around the availability of hydrogen and long-duration storage. Ascend described that the modeling results all point for a need for technological innovation to meet clean energy goals. 4. All scenarios result in nearly identical actions over the first 5 years of the IRP period, although there are differences in rooftop solar buildout. From there, they diverge depending on their clean energy timeline, whether certain resources are being retired, etc. Ascend described that the near-term similarity of all these scenarios means there are several “no-regrets” planning investments GWP can make now to create progress for the next 20 years. Ascend Analytics Introduction to Modeling Results 1. Ascend’s modeling included several phases: a. The scenarios were first run through a “capacity expansion” model. The results of this modeling select resources that are available to meet GWP’s energy needs. b. The “production cost” model then shows how GWP’s system would operate with the resources selected in the capacity expansion model. It simulates transmission constraints and has to match the selected resources with Glendale’s anticipated load. c. Ascend also does some “hand adjustments” based on the results of these models. For instance, the models like batteries, especially 8-hour batteries, and choose to build a lot of them. But then these batteries only get cycled 50 times a year, which isn’t really a good investment. Ascend sees this dynamic happening and manually tries to replace those batteries with other things to correct it. 2. Capacity expansion inputs and assumptions (slide 4): a. The capacity expansion model considered a variety of resources. i. Geothermal:
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All California utilities would like to get more geothermal, but it’s scarce and they can’t find it. Geothermal is a great resource because it’s clean and firm (that is, around the clock) energy. There are a couple companies looking at enhanced geothermal to get past its scarcity. Ascend limited the geothermal buildout to 50 MW. In inland California, that would come in through the SWAC transmission line. ii. Wind: Wind could be located in the Washington state area and come to Glendale via the Pacific DC Intertie transmission path. We’re in a weird world right now with wind. Wind is very constrained. Idaho and other areas are facing those constraints: there are developers who want to build, but interconnection and permitting are all backlogged. There will be wind soon, though. iii. In addition to utility-scale solar, each scenario had a different amount of behind-the-meter solar. iv. Basically every model says build geothermal, then wind in the Pacific Northwest. Then bring in solar through the SWAC line. v. Long-duration storage was also considered to be available in the future. 3. Production cost models (slide 5): a. The outputs from the production cost model are where you can see how much carbon emissions are generated, how much energy is generated by each resource in a realistic setup, and what the market interactions are. b. Ascend ran the production cost models, made adjustments, and ran them again in an iterative process. 4. Clean vs. zero carbon emissions (slide 6): a. California’s 2045 clean energy mandate applies to retail sales. Of every 100 MW you generate, at least 90 of it needs to be clean, because roughly 10 of it is lost in transmission. i. The upshot is that, according to SB1020, you can have some natural gas in your system post-2045, but you can’t use it very much. ii. Right now, this is calibrated annually, rather than hourly (that is, on a 24/7 basis). b. Zero carbon emissions is more strict. This definition says no greenhouse gas emissions, pure and simple. That means no natural gas in the system at all. c. GWP 1 and 3 adhere to California’s definition of clean energy, while GWP 2 and all of STAG’s scenarios achieve zero carbon emissions. 5. Scenarios (slide 7): a. GWP 3 results are not presented today because the production cost model is wrapping up. But it’s basically a spinoff of GWP 1 and will look similar, but with substituting some amount of renewable generation with renewable energy credits. 6. Key findings (slides 8–10): a. A transition to a clean energy system relies on technical progress. i. Models that rely on wind, solar, and four-hour batteries aren’t sufficient. 739 of 839
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ii. We need at least medium duration batteries (8–10 hour), and ideally long duration batteries (multi-day). There’s a company called Form Energy that makes batteries that can store 100 hours’ worth of energy, called iron air batteries. Ascend assumed that the most LDES that could be built was 50 MW. The good thing about these batteries is they’re very environmentally inert. But they require a large amount of land (3 MW per acre). The drawbacks are they don’t make these batteries yet. But the company exists and they’re doing pilots. Long-duration batteries have only 60 percent efficiency (so you lose 40 percent of the energy). Medium-duration batteries have 90 percent efficiency. iii. Also need clean and firm generation that’s dispatchable (that is, can be ramped up and down quickly to meet needs). Clean hydrogen, carbon capture and storage, renewable natural gas, and nuclear small modular reactors are all options. We picked hydrogen to fill this role because we think it’s most likely. b. A full transition requires replacement of in-basin natural gas resources (Grayson 9, internal combustion engines, and Magnolia) with firm, clean options. i. With no new resource additions, you’d have 372 MW of resources in GWP’s baseline portfolio. But you need 416 MW of capacity to meet load growth. So you need to add 44 MW of new local capacity to meet that load growth. ii. In several scenarios, we’re taking out local fossil resources, so we need to build replacements for those. iii. The reason we have to build them in Glendale is because we’re worried about the weak point of having only two central transmission lines. c. Geothermal, storage, hydrogen generation, and wind are selected most by the model. i. Solar isn’t selected even though it’s cheap and abundant. The model didn’t automatically pick solar because it doesn’t provide that high of a value for the time of day at which it generates energy. Ascend manually added solar by replacing a portion of the model’s suggested wind generation with solar. 7. Summary of results (slide 12): a. The cost numbers are net present value for the next 23 years. They reflect total costs. i. These numbers show what happens when you go fully clean. The large price difference between the scenarios is mostly a function of hydrogen cost, which comes into play when you retire gas plants and transition them to hydrogen. ii. Note: The cost numbers presented at this meeting have since been updated. The figures presented in this slide do not reflect the most recent results. b. STAG member question: Why does STAG 1 achieve so much more than 100 percent clean energy in 2035? 740 of 839
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Glendale Water & Power 2024 IRP C-107
i. Ascend: STAG 1 is generating a lot more than you need at times. That’s because there’s a lot of rooftop solar in that scenario, as well as more utility-scale solar. The result is that the clean energy generated in a given year would be well over Glendale’s actual energy use. The excess is either sold into a market, curtailed, or not used. This doesn’t mean the clean energy generation is high all the time – it just means that, on average over that year, that scenario did over-generate energy. ii. This is also the case for other scenarios that go over 100 percent clean energy. c. STAG member question: Can’t GWP make money from selling excess generation? i. GWP: You’re not necessarily making money from over-generating. Oftentimes you’re losing money. The overgeneration from the middle of the day (like when solar produces) goes into negative pricing. In some cases, you’d have to actually pay someone to take that energy. ii. A STAG member commented that the energy could also be stored in a battery. Modeling Results: California Policy Scenario (GWP Scenario 1) 1. GWP California Policy buildout (slide 13): a. Anything above the “0” line in this graph is added. Anything below is taken out. b. Before 2027, all scenarios look essentially the same. In 2025, we add in the Intermountain Power Plant’s (IPP) natural gas and hydrogen resources. Then retire its coal resources the following year. c. In 2028, the model starts building storage. A little bit of solar is added, too. d. By 2035, IPP is fully hydrogen and is therefore carbon free. That transition to hydrogen is reflected by the natural gas resources that appear to be retiring in 2032 and 2035. e. The model doesn’t remove any natural gas in 2045 because remaining natural gas resources don’t run above the 10 percent capacity allowed under California law. 2. GWP California Policy capacity (slide 14): a. Note this is capacity, not energy. Capacity reflects the total technical potential of resources to generate energy, not the energy they actually generate. i. That’s why the natural gas bars (light grey) are so large here, even through 2045. In this scenario, we aren’t retiring natural gas units and they remain available to meet GWP’s reserve requirements. They might run sometimes, or they might not ever run. This graph shows the total potential that each resource could provide, not the energy it will provide. b. Early on you see coal (black bar) goes away as IPP is transitioned. 3. GWP California Policy energy mix (slide 15): a. In this slide, you can see that natural gas usage is actually much less than its total capacity. This is really Magnolia, which has a minimum generation requirement. It’s considered a resource that always has to be online and operating. i. The Magnolia contract is complex because there are six cities associated with the project. If any one of them needs energy, all the partners have to take it. ii. So for system stability, Magnolia stays on. 741 of 839
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b. STAG member question: Is that contract online after 2045? And do we get dinged every time someone needs to turn it on? i. GWP: Magnolia has a much longer life than we would anticipate. There is a study right now in which all owners are trying to make sure Magnolia is kept in our portfolio, but is clean (that is, transition it to hydrogen or another clean fuel). Believe they’re targeting around 2040. c. STAG member question: What’s causing the big jump in load between 2028 and 2029? i. Ascend and GWP: In that year, there are a few large new customers coming online which we considered in our demand projections. We got the base load forecast from the California Energy Commission, then we adapted it to account for new customers like those. 4. GWP California Policy RPS and clean generation (slide 16): a. California’s mandate requires that by 2030, renewable resources have to cover 60 percent of load. That’s represented by the green line, which goes along with the righthand Y axis. b. The green and blue bars together make up all the clean MWh that GWP is generating. They correspond to the lefthand Y axis. c. By California policy, “renewable” and “clean” resources mean different things. Clean resources (the blue bars) include things that are carbon free but don’t meet the renewable portfolio standard (RPS) requirement (for example, nuclear, large hydropower, hydrogen). Renewable resources (the green bars) include wind, solar, geothermal, small hydropower, and landfill gas (like Scholl). d. You can see from the green line that this scenario will be well in excess of the 60 percent RPS requirement by 2030. Close to 78 percent by 2030. e. As we move through time, the percent of renewable and clean energy in this portfolio goes slightly down, because there’s load growth happening. 5. GWP California Policy costs (slide 17): a. Note: The cost numbers presented at this meeting have since been updated. The figures presented in this slide do not reflect the most recent results. b. The cost of new resource additions across the IRP is reflected in net present costs. c. To arrive at net present costs, we consider the capital cost of all the resources in the model, levelized over a period of time (like the life of the project). d. So, for instance, the cost of adding geothermal (red bar) is spread out across the graph. As we move through time, we’re accumulating annual expenses to pay for the resources. e. We then add all those bars back into the present value and integrate a 5 percent discount between each year (meaning the expenses later on are less than the near-term expenses). That then gives us the net present cost of the resource portfolio. 6. GWP California Policy carbon emissions (slide 18): a. We remove carbon emissions from IPP early on. Emissions continue to decrease after IPP converts to hydrogen, meaning natural gas carbon emissions become a lot more stable. 742 of 839
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Modeling Results: Clean by 2035 Scenario (GWP Scenario 2) 1. GWP Clean by 2035 build out (slide 19): a. This scenario differs from the last in that it has a lot more storage. b. Natural gas all goes offline here to be completely zero emissions by 2035. That looks like a retiring of natural gas (the large grey bar) and a simultaneous coming online of a hydrogen resource (green bar). 2. GWP Clean by 2035 capacity (slide 20): a. You can see a lot more storage at the top of these bars. b. By 2035, the capacity has grown a lot. As we get more lower-capacity-value resources (resources that don’t run all the time), we end up overshooting the peak load, meaning over-generating energy. c. You can see in 2035 all natural gas goes away and we’re carbon free from that point on. d. The 2035 bar is lower than the rest of them because it reflects the retirement of natural gas in that year. We’re still able to cover the load with the 600 MW of capacity that’s in the portfolio, then, though. 3. GWP Clean by 2035 energy mix (slide 21): a. So you can see some differences here from the past slide. In the past slide, geothermal wasn’t that big from a capacity perspective, but since it generates around the clock, it has high energy content. The geothermal here equates to 50 MW. b. This particular scenario doesn’t have as much new solar as the others. 4. GWP Clean by 2035 RPS and clean generation (slide 22): a. We’re actually at over 100 percent clean energy by 2035. 5. GWP Clean by 2035 costs (slide 23); a. Note: The cost numbers presented at this meeting have since been updated. The figures presented in this slide do not reflect the most recent results. b. The big jump in costs in 2035 is what happens when you add hydrogen in the model. c. The challenge here is that I don’t know how much hydrogen will cost in 2035, so there’s uncertainty. But we made assumptions based on our best knowledge today, which were developed by Ascend’s market research team. They anticipate that later on, hydrogen will be a bit more expensive than natural gas. 6. GWP Clean by 2035 carbon emissions (slide 24): a. When you retire natural gas and transition it to hydrogen, all carbon emissions go away. Modeling Results: STAG Scenario 1 1. STAG 1 buildout (slide 25):
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a. The results here are similar to the last scenario, but the differences are in the ordering of when these resources come online. 2. STAG 1 capacity (slide 26): a. You can see behind-the-meter (BTM) solar is a much larger part of this scenario’s capacity than in other scenarios, due to high assumptions on customer solar adoption. 3. STAG 1 energy mix (slide 27): a. You can see that the load here (black line) is affected by the larger contribution of BTM solar. In this slide, that solar is built into the load projection (because it impacts people’s energy demand) rather than being displayed as a separate resource. When 90 MW of BTM solar comes online in 2028, the load line is lowered. b. This scenario also included more aggressive energy efficiency. So that flattens out the load where it would grow otherwise. c. STAG member question: Why is there a dip in load only in 2028 and then it goes right back up in 2029? i. Ascend: That’s because we have all the BTM solar coming online in 2028 and then largely leveling off after that point, with slight increases in adoption after that. Also, the load goes up in 2029 because of the new project coming online, which offsets some of the contributions of solar and efficiency. d. STAG member question: What about customer storage? We have wasted power during the day. i. Ascend: We didn’t give a capacity accreditation to customer storage, although we did assume some growth in customer storage in this scenario. 4. STAG 1 RPS and clean generation (slide 28): a. The RPS in this scenario is well over the California requirement, exceeding even 100 percent in some years. 5. STAG 1 carbon emissions (slide 29): a. As with the last scenario, carbon emissions completely go away with the retiring and transition of all natural gas resources. 6. STAG 1 costs (slide 30): a. Note: The cost numbers presented at this meeting have since been updated. The figures presented in this slide do not reflect the most recent results. b. In terms of costs of customer resources like rooftop solar, we modeled this scenario with net energy metering. If you install solar panels on your roof, the extra solar that’s generated gets sold back into the grid. You’re avoiding paying to buy that energy, but GWP is instead buying it from you. So there is a cost to GWP of expanding rooftop solar and other distributed resources displayed here. c. As with the last scenario, hydrogen is the largest contributor to costs. 744 of 839
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Modeling Results: STAG Scenario 2 (slides 31–36) 1. Note: At the time of the STAG meeting, the results from this scenario needed to be validated and some inaccuracies corrected. The accompanying PowerPoint reflects this updated information, but STAG did not talk extensively about this scenario due to the changes required. 2. When looking at the resource buildout for this scenario (slide 31), you can see that the model retires natural gas units at the last minute to be able to meet this scenario’s 2042 zero emissions requirement. Modeling Results: STAG Scenario 3 (slides 37–42) 1. The main difference between this scenario and the last one is that hydrogen comes online sooner in this case. 2. These results were only quickly highlighted to allow time for questions and discussion. Open Discussion and Questions: 1. Scenario costs a. Multiple STAG members commented that it’s difficult to know what the scenario costs actually mean without knowing how they would impact rates. They requested more information on this point. b. GWP shared that the current proposed rate increase amounts to roughly $500 million in total, which is similar to the capital cost of the GWP California Policy scenario. The IRP’s cost is different than the current rate increase, though, because it’s spread out over 20 years. In certain years, there’d likely be big jumps in cost as resources shift (like 2035). c. One STAG member noted that energy efficiency technologies and BTM resources may be counter to GWP’s desire to increase revenue. i. GWP responded that revenue growth doesn’t matter to them. They have fixed costs that go into rates. ii. STAG members and GWP discussed where GWP’s revenue goes, noting that not all revenue goes into energy production. Some of it goes back to the city for use on other public goods and services. It isn’t up to GWP to decide what to do with its revenue – that’s largely up to City Council. d. One STAG member noted that it’s hard to take any cost projections past 2028 seriously due to future unknowns. They said they’d be very surprised if this year’s projections remained true in five years. i. Ascend underscored this point, noting that projecting across 20 years is a difficult exercise and there are large uncertainties. 2. Social cost of carbon (SCC) a. One STAG member wanted to know more about the social cost of carbon analysis and if data could be presented on total scenario costs with the SCC added. b. GWP responded that one challenge with looking at the SCC is that there is no mechanism to collect money or pay any party that value. c. STAG members responded that the SCC is meant to reflect costs that individuals and society would pay due to carbon emissions, although not necessarily through utility bills. 745 of 839
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d. GWP also added that the difference between scenarios with regards to their SCC is not as large as you might expect, given that coal is being phased out and GWP already plans to run its natural gas units less frequently in the future. 3. Near-term outlook a. Ascend emphasized that, although the IRP looks out to 2045, we’re only in 2023. This process will be repeated in 2028, meaning that what GWP does from 2023–2028 matters most. In the near-term, all scenarios show GWP needs to look for more geothermal, storage, solar, and wind, while continuing to plan for the period after that. When the IRP is done again in 2028, new developments are expected (like IPP running on hydrogen), meaning we’ll know more about the likelihood of hydrogen technology then. b. A STAG member asked how the scenarios differ in the first five years. i. Ascend responded that the only scenario that substantively differs in the near-term is STAG 1, which requires a large buildout of customer solar. The other scenarios all indicate you need more geothermal, wind, and a little bit of solar, then to invest in energy storage in the late-2020s. After the first five years, the differences really come down to timing – do you replace natural gas in 2035, 2040, 2042? Or not at all. 4. New models for clean energy a. One STAG member raised that there’s a local community choice aggregator (CCA), which Glendale seems to be exempt from, and asked why. i. Strategen responded that CCAs don’t apply to municipal utilities, so using a CCA is not possible in Glendale. b. One STAG member asked about community solar and why it hasn’t been integrated in the models. They noted that community solar is ideal for tenants and multifamily housing. i. GWP agreed community solar is uniquely suited for renters and multifamily housing. GWP explained that the primary community solar model includes a developer creating a solar project shared among community “owners,” with the energy generated at that project offsetting part of the participants’ electric bills. But they typically require an upfront investment to buy part of that project, which not everyone can afford. As people buy into community solar, they contribute less to utility costs via their electric bills. Those who are left without community solar may then pay a greater share of the fixed cost of electric rates, which can create an equity issue. ii. The STAG member noted that subsidies can help offset some of the community solar costs and help more people afford it. They were also curious whether there are other community solar models besides that which GWP described. c. One STAG member shared an article stating that technologies are available today to reach 100 percent clean energy, predominantly with solar, wind, etc., but that we need to talk more about efficiency solutions like heat pumps. d. One STAG member asked if stacking battery storage units is possible to save acreage. i. GWP explained there’s only one vendor considering stackable batteries at the size they’d need. This vendor is the same one they’re considering for the Grayson Repower sites. The company 746 of 839
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hasn’t perfected the technology with regards to withstanding things like earthquakes and fires. But part of the reason GWP selected that company’s technology was for the potential that the batteries could stack in the future. 5. Hydrogen a. GWP and STAG members discussed the Intermountain Power Project in depth. GWP described that, despite the inefficiencies of converting renewable energy to hydrogen, the project is still critical for reliability and helps GWP meet clean energy requirements. Having hydrogen in its portfolio can also help GWP overcome transmission constraints. 6. Transmission a. One STAG member asked whether developing new transmission might be the cheapest way to access clean energy. i. GWP responded that people have been wanting to develop transmission for the past 35 years, but none has been built in that time. It’s a question of will, rather than cost. Land challenges also come into play, with communities saying, “not in my backyard.” Next Steps 1. Ascend will send out a finalized version of its modeling results to STAG for their review. 2. Strategen will send out a survey to STAG soliciting input on modeling results and members’ preferred scenarios after members have a chance to review the final results. 3. GWP will look at STAG’s survey results and discuss its options for a preferred scenario. This scenario selection will be presented to GWP Commission on November 6, 2023. 747 of 839
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STAG Meeting 6 Presentation
1 November 1, 2023
STAG meeting 6: Modeling results
2 Disclaimer•This presentation has been updated from the version presented to STAG at its 6th meeting to correct for inaccuracies and fill in some missing information. The updated version was shared with STAG after the meeting. •Even after this updated version, some data related to hydrogen costs changed. As a result, certain slides that reflect scenario costs are no longer accurate. A note has been included on these slides to reinforce this point. 2 Modeling Process•Modeling for the 2023 IRP was conducted in the phases shown belowoBaseline model with GWP’s current and planned resources§Provides insight for GWP’s portfolio for near term decisionsoCapacity Expansion Models§Outcome of Capacity Expansion models provide the timing and quantity of new resource additions to meet the GWP requirements for capacity and renewables§Resource selection is based on economics and the ability of resources to satisfy GWP needsoResource Adequacy Models§Provide metrics on the ability of GWP’s system to serve load all hours of the year over a wide range of system conditionsoProduction Cost Models§Outcome of production cost models show how GWP’s system would operate with the resource selection from the Capacity Expansion model§Important outputs include renewable generation serving load, carbon emissions, and portfolio costs 3 Capacity Expansion Inputs/Assumptions•The following resources were considered in the GWP modelsoGeothermal –Provides firm power around the clock via the SWAC transmission pathoWind –Could be located in the Pacific Northwest via the PDCI path or the Southwest via the SWAC pathoSolar –Available in Southern California via the SWAC pathoHydrogen –Assumes CT or ICE generators can run on 100% hydrogen by 2035oLong Duration Storage –Assumes a 100-hour battery available by 2035oLi-Ion Storage –Model included 4-hour and 8-hour storage options. •Resource selection met the capacity and the RPS/Clean energy requirementso60% RPS by 2030o100% Clean by 2035 or 2045•Transmission was not directly modeled in the Capacity Expansion phase, instead limits were placed on resource construction 4 Production Cost ModelsOutputs from Capacity Expansion models are fed into Production Cost models•Resources are added to one of three locations: Glendale, Southwest (SWAC line), Pacific Northwest (PDCI line)•The model simulates GWP’s system on an hourly basis, stepping through time to dispatch resources and serve load•Outputs includeoCarbon emissionsoEnergy generation by resource oLoadoTransmission flowsoMarket interactions•Ascend ran the Production Cost models multiple times to adjust resources around the transmission limits and hit the RPS/Clean energy requirements Define Clean vs Zero Caron EmissionClean Generation per California policy mandates•Utility serves retail load with carbon-free energy•Retail load is approximately 90% of “gross” load which includes power losses in the transmission and distribution lines. •SB 1020 requires utilities to provide enough carbon-free energy to cover roughly 90% of load (depending on the actual power losses in the utility) Zero Carbon Emissions is more strict•A portfolio with zero-carbon emissions with have no fossil fuel generation 6 ScenariosGWP•Clean by 2045 per current California policyoMeets RPS and Clean energy requirements with long-term contracts•Zero Carbon Emissions by 2035oMeets the City Council target of fully clean by 2035•Clean by 2045 with REC purchases for offsetsoMeets RPS and Clean energy requirements partially with purchased RECs STAG•Zero Carbon Emissions by 2035oHigh DR, High BTM Solar, DER batteries•Clean by 2042oMid DR, Mid BTM Solar, DER batteries•Zero Carbon Emissions by 2040oMid DR, Mid BTM Solar, DER batteries 7 Key Finding 1A transition to a clean energy system relies on technical progress•Long Duration Storage (multi-day) –Show example productsoAble to shift variable generation over several daysoNot yet commercially availableoSome pilot projects are being planned with small capacitiesoInstallation require large amount of land –(from energy states 3 MW per acre)•Medium Duration Storage (eight to ten-hours)oCommercially available but not yet widely installedoShifts variable generation from low demand to high demand hours within a day•Clean Firm Generation (dispatchable)oMost promising technologies are Green Hydrogen, CCUS, Renewable Natural Gas, and Small Modular ReactorsoNot yet commercially availableoOf the possible options, Green Hydrogen is considered the most likely and most cost-effective, but requires infrastructure and technical advancement 748 of 839
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8 Key Finding 2 A full transition requires replacement of Grayson 9, ICEs, and Magnolia with firm, clean options•Retirements of in-basin natural gas resources create reliability challenges for GWP•GWP is required to maintain operational reserves based on the N-1-1 contingency planning oIn 2035, peak load is projected to be 416 MWoFor N-1-1, GWP can rely on 100 MW from the SWAC line, remaining capacity must be localoRemaining resources add up to 372•GWP must add 416 –372 = 44 MWof local capacity to meet load growth N-1-1 Resource ContributionSWAC line (without STS)100DR 8City Solar10Magnolia44ICE 54Grayson 948Eland Solar and Storage25Energy Storage75Scholl’s Canyon8Total Resources372 9 Key Finding 3Based on the projected resource costs and market outlook, the Capacity Expansion model selects geothermal, storage, hydrogen generation, and wind•Solar is not selected by the Capacity Expansion models due to the heavy build out of solar in California which has pushed market prices lower during solar hours. Ascend added solar per the scenario requirements by replacing a portion of wind with solar•Geothermal was selected as soon as possible in all scenarios due to its capacity and high RPS contribution•Hydrogen was selected for capacity purposes•Storage, especially long-duration, was selected to boost capacity and manage renewables 10 High level summary of scenarios•GWP 1 –Clean by 2045. In this path, GWP will procure resources to meet the CA mandates for renewable energy and clean energy. The mandates state that GWP must serve 60% of the energy needs with renewable energy by 2030 and serve 100% of the retail energy with clean energy by 2045. In this path, GWP continues to develop wind and solar remotely while adding storage in Glendale.•GWP 2 –Carbon Free by 2035. In this path, GWP will aggressively procure carbon-free resources including geothermal, wind, and solar while also building storage early in the process. Natural gas generation will be replaced or converted to a clean fuel source such as hydrogen by 2035. The costs of the transition are uncertain as they depend heavily on the cost of replacing natural gas with hydrogen. This scenario aligns with the IRP of LADWP .•GWP 3 –Clean by 2045 with offsets. Same as GWP 1, but with less renewable generation. The lower renewable generation is offset with purchases of renewable energy credits to meet the California mandates.•STAG 1 –Carbon Free by 2035 with a focus on local resources. GWP would aggressively procure geothermal, wind, and solar at the utility scale while also pursuing customer-sited resources. Rooftop solar increases significantly along with distributed batteries at residences. GWP would also work to increase energy efficiency. •STAG 2 –Carbon Free by 2042. In the path, GWP will work to convert natural gas resources to run on a clean fuel by 2042. GWP will push for increased renewable procurement in the near-and mid-term while working towards the transition out of natural gas. One thing that stands out in STAG 2 is that Magnolia retires in 2038 instead of 2042 causing less emissions here compared to STAG 3. This scenariolines up with other smaller municipal utilities in the region. •STAG 3 –Carbon Free by 2040. This is very similar to STAG 2 with a slightly more aggressive timeline. 11 Summary of Results
Total New Resource Cost (Millions)PercentClean Energyin 2035Total CO2Emissions(Million Tons)Total Cost of Carbon with SCC applied ($Million)GWP CA Policy$53591%2,597$385GWP Zero Emissions by 2035$1,887109%1,642$267 GWP CA Policy with Offsets$49782%2,597$385
STAG 1$1,815132%1,434$209STAG 2$1,344103%1,828$290STAG 3$1,36395%2,032$316 12 GWP California Policy Build Out
13 GWP California Policy Capacity
14 GWP California Policy Energy Mix
15 GWP California Policy RPS/Clean Generation
*RPS and Clean Energy percentage is measured compared to wholesale load in this slide. The California policy is measured against retail sales. Clean energy equal to 90% of gross load is approximately 100% of retail sales. 749 of 839
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16 GWP California Policy CostsNet Present Cost of Resource Additions from 2023 to 2045 = $535 Million 17 GWP California Policy Carbon Emissions
18 GWP Clean by 2035 Build Out
19 GWP Clean by 2035 Capacity
20 GWP Clean by 2035 Energy Mix
21 GWP Clean by 2035 RPS/Clean Generation
*RPS and Clean Energy percentage is measured compared to wholesale load in this slide. The California policy is measured against retail sales. Clean energy equal to 90% of gross load is approximately 100% of retail sales. 23 GWP Clean by 2035 CostsNet Present Cost of Resource Additions from 2023 to 2045 = $1,888 Million Note: Cost data has changed since the time of this meeting. The costs reflected here are not the most recent or accurate. 23 GWP Clean by 2035 Carbon Emissions
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24 STAG 1 Build Out
25 STAG 1 Capacity
26 STAG 1 Energy Mix
27 STAG 1 RPS/Clean Generation
*RPS and Clean Energy percentage is measured compared to wholesale load in this slide. The California policy is measured against retail sales. Clean energy equal to 90% of gross load is approximately 100% of retail sales. 28 STAG 1 Carbon Emissions
30 STAG 1 CostsNet Present Cost of Resource Additions from 2023 to 2045 = $1,816 Million Note: Cost data has changed since the time of this meeting. The costs reflected here are not the most recent or accurate. 30 STAG 2 Build Out
31 STAG 2Capacity
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32 STAG 2Energy Mix
33 STAG 2RPS/Clean Generation
*RPS and Clean Energy percentage is measured compared to gross load in this slide. The California policy is measured against retail sales. Clean energy equal to 90% of gross load is approximately 100% of retail sales. 35 STAG 2Policy CostsNet Present Cost of Resource Additions from 2023 to 2045 = $1,344 Million $0
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20232024202520262027202820292030203120322033203420352036203720382039204020412042204320442045 Annual Cost of New Resources
Long-duration storageFour-hour storageEight-hour storageGeothermalSolarSWAC WindPDCI WindHydrogenDRBTM SolarDER BESS Note: Cost data has changed since the time of this meeting. The costs reflected here are not the most recent or accurate. 35 STAG 2Carbon Emissions
36 STAG 3 Build Out
37 STAG 3Capacity
38 STAG 3Energy Mix
39 STAG 3RPS/Clean Generation
*RPS and Clean Energy percentage is measured compared to gross load in this slide. The California policy is measured against retail sales. Clean energy equal to 90% of gross load is approximately 100% of retail sales. 752 of 839
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Figure 94. STAG Meeting 6 Presentation Slides
41 STAG 3Policy CostsNet Present Cost of Resource Additions from 2023 to 2045 = $1,363 Million $0
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20232024202520262027202820292030203120322033203420352036203720382039204020412042204320442045 Annual Cost of New Resources
Long-duration storageFour-hour storageEight-hour storageGeothermalSolarSWAC WindPDCI WindHydrogenDRBTM SolarDER BESS Note: Cost data has changed since the time of this meeting. The costs reflected here are not the most recent or accurate. 41 STAG 3Carbon Emissions
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STAG Scenario Preference Surveys After the sixth and final STAG meeting, Strategen sent out two surveys that asked for STAG members to indicate their preferred scenario. All STAG members responded to these surveys. The surveys had two parts. First, STAG members chose their top 3 scenarios (in no particular order). STAG was then asked to allocate 100 points across their 3 selections to indicate which scenario they preferred, and how strongly. Members could allocate points any way they chose, including giving no points to one or more of their scenarios. The only requirement was that the total points allocated had to equal 100. This survey was conducted twice to capture STAG’s perspective at different points as results were validated and updated. The first survey took place shortly following the final STAG meeting, before GWP had decided on its recommended scenario and presented that recommendation to the GWP Commission. After the Commission meeting, a review of the model’s cost inputs revealed that there was an inaccuracy in the cost assumptions for hydrogen. The costs were updated, which changed the overall cost of each scenario that STAG had used to make its decision. Ascend Analytics also completed its analysis of operating costs for all scenarios, further altering the original costs presented to STAG. Since STAG voted on its preferred scenario using the prior data, it was later decided (following the final townhall) that STAG should revote on their preferred scenario with the complete and accurate picture of costs. Table 24 presents the costs that were originally presented to the STAG (at time of first vote) and the updated costs that were considered in STAG’s second vote. Cost Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5 Scenario 6 Original New Resource Costs (first STAG survey) $535 $1,887 $497 $1,815 $1,344 $1,363 Updated New Resource Costs (second STAG survey) $535 $1,296 $491 $1,145 $897 $867 Operating Costs (only available for second STAG survey) $1,073 $970 $1,098 $1,086 $1,131 $1,142 Total Costs $1,608 $2,267 $1,589 $2,231 $2,027 $2,009 Original and updated costs in $M net present value (2024–2045) Table 24. Original and Updated New Resource Costs: All Scenarios STAG Survey Results: First Survey The STAG’s top three scenarios: In the first survey, every scenario was selected by at least one person for their top three. The scenarios that most members chose for their top three were: § GWP 1 (nine people) § STAG 2 (nine people) § STAG 1 (six people) § STAG 3 (six people) 754 of 839
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Figure 95. STAG Top Three Scenario Selections (Survey 1) STAG’s scenario weighting: When asked to weigh their top three scenarios by allocating 100 points across them, a different picture emerged. While STAG 2 and STAG 3 were among the STAG’s most selected scenarios for the first question, they did not receive many points in the weighting exercise. In total, GWP 1 received the most points, with 530. § This scenario was the top choice for six members. That represents 55 percent of the STAG, and 67 percent of the nine people who put this scenario in their top three. § Three members allocated all 100 of their points to GWP 1 (27 percent of the STAG). STAG 1 received the second most points, with 375. § A difference of 155 points separated STAG 1 and GWP 1. § One member allocated all 100 of their points to STAG 1 (9 percent of the STAG). § Although STAG 1 wasn’t chosen in as many members’ top three scenarios compared to GWP 1 (six compared to nine), the people who chose it strongly preferred it. This scenario was the top choice for five members (46 percent of the STAG). Five out of six people who put it in their top three ultimately chose it as their top choice (83 percent). While STAG 2 was tied with GWP 1 for the greatest number of people who put it in their top three, only two members selected it as their top scenario, suggesting STAG 2 was a backup option for many. § Three of the people who selected STAG 2 as one of their top scenarios ultimately allocated no points to it because they put all 100 toward GWP 1. Similar to STAG 2, STAG 3 was also a backup option for many members, although no one selected it as their top choice. 755 of 839
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GWP 2 and GWP 3 were the least popular among the group. § While five people selected GWP 2 as one of their top scenarios, all of those people ultimately selected STAG 1 as their preferred scenario. GWP 2 was not any member’s top choice. Member comments suggest that STAG 1’s greater emphasis on rooftop solar and other customer programs may have made that scenario more attractive to them. § While four people selected GWP 3 as one of their top scenarios, three of those four people ultimately allocated all 100 of their points to GWP 1. Only one person allocated points to GWP 3. This scenario was not any member’s top choice.
Scenario Allocated Points Members Who Put Scenario in Their Top Three Members Who Allocated Points to Scenario GWP 1 530 9 9 STAG 1 375 6 6 STAG 2 180 9 6 STAG 3 135 6 5 GWP 2 70 5 4 GWP 3 10 4 1 Table 25. STAG Scenario Weighting: Survey 1 Figure 96. STAG Scenario Preference by Total Points Allocated per Scenario (Survey 1) Respondent comments: Many of the members who chose GWP 1 as their top choice expressed that part of their reasoning for doing so was because of the technological uncertainty and cost of getting to true zero emissions sooner than 2045: § “We must remain grounded with technologies that are available today to achieve our goals… We have to face affordability and reliability realities in front of us at this moment.” § “Most of the expensive scenarios rely on high-risk new technologies that might not be built, or will underperform.” 756 of 839
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§ “I believe rushing to zero emissions can be at high costs and choosing resources too soon as new technology continues to emerge.” Concern about the use of RECs in GWP 3 made that option unattractive for several members: § “I’m not confident in the use of offsets.” § “I don’t consider [RECs] to be effective in actually reducing carbon emissions.” § “I think offsets are a scam, so I don’t support that option.” Many of the members who chose STAG 1 or other STAG scenarios as their top option referenced the need to advance progress toward clean energy goals and increase the role for renewables: § “A net zero target of 2045 is no longer acceptable…” § “Future costs are largely fictional at this time, so we need to go for the greatest reduction of carbon by 2030.” § “We need forward-thinking, local dependence, harnessing freely available resources like sun, wind, water, wave energy, etc.” § “Considering the city’s transmission constraints, the immediate solution should be to emphasize local rooftop solar through the 10 percent resolution plan.” STAG Survey Results: Second Survey STAG’s top three scenarios: Again in the second survey, every scenario was selected by at least one person as among their top three. The STAG’s selection of its top three scenarios differed only slightly from the first survey. In this second survey, the group’s top scenarios were: § STAG 2 (nine people) § GWP 1 (eight people) § STAG 1 (seven people) 757 of 839
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STAG 2 was the group’s top choice this time around, with nine members selecting it (the same number as the last time). One fewer person selected GWP 1 as among their top three (for a total of eight members), instead opting to replace that slot with STAG 1 (selected by seven members, up one from the first survey). Selections of the last three scenarios remained unchanged.
Figure 97. STAG Top Three Scenario Selections (Survey 2) Scenario Survey 1 Survey 2 Difference GWP 1 9 8 –1 GWP 2 5 5 Same GWP 3 4 4 Same STAG 1 6 7 +1 STAG 2 9 9 Same STAG 3 6 6 Same Table 26. Top Three Scenario Selection Comparison between Survey 1 and Survey 2 STAG’s scenario weighting: As with the first survey, a different picture emerged when looking at STAG’s weighting of its top three scenarios. The results of this second survey remain overall the same as the first iteration (GWP 1, the California Policy scenario, still received the most points), although the distance between STAG’s first and second choices shrunk sizably. In total, GWP 1 received the most points, with 525. § This scenario was the top choice for six members, the same number as the first survey. That represents 55 percent of the STAG and 75 percent of the eight people who put this scenario in their top three. § Again, three members allocated all 100 of their points to GWP 1 (27 percent of the STAG). Again, STAG 1 received the second most points, with 480. § The gap between GWP 1 and STAG 1 shrunk considerably in this survey. In the first survey, the scenarios were separated by 155 points. In this survey, they were separated by 45. 758 of 839
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§ Two members allocated all 100 of their points to STAG 1 (15 percent of the STAG). This is one more member than the last time. § This scenario was the top choice for six members (55 percent of the STAG). Six out of seven people who put it in their top three ultimately chose it as their top choice (86 percent). While STAG 2 had the greatest number of people who put it in their top three, only two members selected it as their top scenario (one of these members had STAG 2 tied with GWP 1 for their top choice). As with the first survey, this suggests STAG 2 was a backup option for many. § Also seen in the first survey, three of the people who selected STAG 2 as one of their top scenarios ultimately allocated no points to it because they put all 100 toward GWP 1. In the first survey, STAG 3 received the fourth-most points, with 135. In this survey, members’ interest in STAG 3 dropped significantly (by 95 points), making this scenario the group’s second-to-last choice. GWP 2 was instead favored as the group’s fourth-ranked scenario. § Overall, though, both these scenarios received lackluster support from the group. While six and five members selected them as among their top three (for STAG 3 and GWP 2, respectively), only three members ultimately allocated points to each of them. § These scenarios were no members’ top choices. Again, GWP 3 was the least popular among the group. § As with the last survey, while four people selected GWP 3 as one of their top scenarios, three of those four people ultimately allocated all 100 of their points to GWP 1. Only one person allocated points to GWP 3. This scenario was not any member’s top choice.
Figure 98. STAG Scenario Preference by Total Points Allocated per Scenario (Survey 2) 759 of 839
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Scenario Survey 1 Survey 2 Difference GWP 1 530 525 –5 GWP 2 70 55 –15 GWP 3 10 30 +20 STAG 1 375 480 +105 STAG 2 180 170 –10 STAG 3 135 40 –95 Table 27. Scenario Point Allocation Comparison between Survey 1 and Survey 2 As depicted in Table 27, in the second survey, members concentrated their points more heavily around the two scenarios that received the most points in the first iteration (GWP 1 and STAG 1) and decreased their support for GWP 2, STAG 2, and STAG 3. Table 28 shows that fewer members allocated points to all scenarios in their top three selections than had in the initial survey. While five members allocated points to STAG 3 in the first survey, only three did in the second. While four members allocated points to GWP 2 in the first survey, only three did in the second.
Members Who Selected the Scenario in Their Top 3 Members Who Allocated Points to the Scenario Members Who Chose Scenario in Top 3 and Allocated Point to It Scenario Survey 1 Survey 2 Survey 1 Survey 2 Survey 1 Survey 2 GWP 1 9 8 9 8 100% 100% GWP 2 5 5 4 3 80% 60% GWP 3 4 4 1 1 25% 25% STAG 1 6 7 6 7 100% 100% STAG 2 9 9 6 6 67% 67% STAG 3 6 6 5 3 83% 50% Table 28. Scenario Summary for Top Three Selection and Allocated Points Instead of spreading points out among multiple scenarios as was more common in the first survey, members placed more of their points in a single top selection in the second. In the first survey, members allocated an average of 71 points to their top scenario and an average of 17 points to their second choice. In the second survey, the points members allocated to their top choice increased, while the points allocated to their second choice decreased: In survey 2, members allocated an average of 78.5 points to their top selection and 12 points to their second choice. Between surveys, the points gap between members’ top and second choices therefore widened by nearly 13 points (53.9 versus 66.6). Survey Top Choice Second Choice Difference Survey 1 71.2 17.3 53.9 Survey 2 78.5 11.9 66.6 Table 29. Average Point Allocation Comparison between Survey 1 and Survey 2 760 of 839
C. Stakeholder Outreach About the STAG Meetings
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These differences in voting behavior may stem from several sources. One potential reason is that the updated scenario costs changed the way STAG members weighed their preferences, making them more strongly support their top choice. This reasoning seems unlikely, though, given that cost differences between the scenarios became less pronounced between the first and second surveys, which one would expect might cause more dispersed support across all scenarios. Another possibility is that seeing the results of the first survey before responding to the second may have influenced the way members voted, encouraging them to concentrate their attention on the scenarios that got the most support in the first survey while reducing the emphasis placed on those scenarios that did not rise to the top initially. While all scenario options were still on the table in this survey, the second iteration may have therefore acted somewhat like a runoff election, with members narrowing down their choices between the first round’s top two options. While the change in voting behavior is worth noting, ultimately the reasons for these differences are not as important as the results themselves. Respondent comments: Many of STAG’s comments in the second survey reflected perspectives that were raised in the first iteration. Respondents who chose GWP 1 continued to raise points around affordability and the uncertainty of new technologies: § “I am representing a group who provided feedback to me that affordability and reliability are of key importance. [This scenario] provides for a path to a sustainable future with the most affordable option…” § “GWP 1 (following CA policy) is most cost effective for ratepayers.” Other scenarios “rely on underdeveloped infrastructure… We should decarbonize, but being the first to do so is just too costly and risky.” § “We have real challenges on affordability and it will get worse over [the] next few years. We have to balance cost while trying to make progress toward the transition to clean energy. The state’s goals of transition by 2045 are already ambitious.” Respondents who chose scenarios that aimed for a clean energy transition before 2045 again emphasized a desire to reach clean energy goals as quickly as possible. They also expressed that some of these scenarios’ costs may come down with technology developments. Some respondents who selected the 2040 or 2042 scenarios stated that they offered a balance between emissions reductions and cost. § “My goal is to reduce carbon emissions as quickly as possible.” § “I generally chose the STAG scenarios over the GWP scenarios because they get us to true carbon-free. They’re not that much more expensive and they result in significantly lower CO2 emissions, particularly STAG 1.” § “Technology improvements will reduce the costs [of the 2035 scenarios]… We need to act now to start moving our city to clean energy!” § “If we are seeking to reach carbon free, then 2042 achieves this at substantial cleaner air and not an aggressive cost impact.” 761 of 839
C. Stakeholder Outreach About the STAG Meetings
Glendale Water & Power 2024 IRP C-128
Respondents who chose STAG 1 as their top scenario indicated that this scenario’s high solar and DER assumptions were a central driver in their decision. § STAG 1 has “the greatest outcomes with DER and SOLAR.” § “I chose STAG 1 because it puts the most resources into solar.” 762 of 839
D. Standardized Tables Capacity Resource Accounting Table (CRAT) Glendale Water & Power 2024 IRP D-1
D. Standardized Tables
CAPACITY RESOURCE ACCOUNTING TABLE (CRAT) Figure 99: California Policy Scenario Capacity Build Out (CRAT) depicts the annual peak capacity demand in each year and the contribution of each energy resource (capacity) in GWP’s portfolio to meet that demand.
Figure 99. California Policy Scenario Capacity Build Out (CRAT) 763 of 839
D. Standardized Tables Energy Balance Table (EBT)
Glendale Water & Power 2024 IRP D-2
ENERGY BALANCE TABLE (EBT) Figure 100: California Policy Scenario Annual Energy Produced and Consumed (EBT) depicts the annual total energy demand and annual estimates for energy supply from various resources.
Figure 100. California Policy Scenario Annual Energy Produced and Consumed (EBT) 764 of 839
D. Standardized Tables Resource Procurement Table (RPT) Glendale Water & Power 2024 IRP D-3
RESOURCE PROCUREMENT TABLE (RPT) Figure 101: RPS and Clean Energy Totals by Year (RPT) contains a detailed summary of the GWP resource plan to meet the RPS requirements.
Figure 101. RPS and Clean Energy Totals by Year (RPT)
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D. Standardized Tables GHG Emissions Accounting Table (GEAT) Glendale Water & Power 2024 IRP D-4
GHG EMISSIONS ACCOUNTING TABLE (GEAT) Figure 102: Annual CO2 Emissions (GEAT) depicts the annual GHG emissions associated with each resource in GWP’s portfolio.
Figure 102. Annual CO2 Emissions (GEAT)
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Glendale Water & Power 2024 IRP E-1
E. Key Modeling Assumptions
Key modeling assumptions include forecasted costs and prices for: § Renewable generation solar, wind from New Mexico, and new geothermal from California through PPAs costs in dollars per MWh forecasted annually from 2027 to 2045. § 4-hour Li-ion, 8-hour Li-ion, and 100-hour iron air BESS costs in dollars per kW forecasted annually from 2027 to 2045 (the 100-hour BESS from 2030 to 2050). § Hydrogen fuel costs for new power plant CTs, CCS cost for new power plants—both forecasted annually from 2027 to 2045—and SMR costs in dollars per kW forecasted annually from 2032 to 2045. § Hydrogen fuel costs that includes the IRA PTC in dollars per MMBtu, California carbon prices in dollars per ton, and the social cost of carbon (from the EPA) forecasted annually from 2024 to 2045. § Off-peak and on-peak electricity power prices from the southern California SP-15 market in dollars per MWh, and natural gas prices from the southern California CityGate market in dollars per MMBtu forecasted monthly from 2024 to 2045. Except for the California carbon prices which were projected by CARB, Ascend Market Intelligence forecast all costs and prices. 767 of 839
E. Key Modeling Assumptions Generation Resource Cost Forecasts Glendale Water & Power 2024 IRP E-2
GENERATION RESOURCE COST FORECASTS Renewable Generation Cost Forecasts Year Solar New Mexico Wind New California Geothermal 2027 $29.92 $39.36 $102.36 2028 $29.35 $38.90 $103.76 2029 $28.72 $38.42 $105.17 2030 $28.03 $37.93 $106.57 2031 $27.28 $38.28 $109.38 2032 $26.46 $38.63 $112.27 2033 $25.57 $38.98 $115.24 2034 $24.61 $39.33 $118.29 2035 $23.58 $39.67 $121.42 2036 $23.91 $40.01 $124.63 2037 $27.33 $43.42 $135.35 2038 $30.86 $46.95 $146.55 2039 $34.51 $50.60 $158.25 2040 $38.29 $54.38 $170.47 2041 $42.19 $58.29 $183.23 2042 $46.23 $62.33 $196.54 2043 $46.93 $63.04 $201.74 2044 $47.64 $63.75 $207.09 2045 $48.34 $64.47 $212.58 Table 30. Renewable Costs through PPAs Forecasts ($/MWh) BESS Cost Forecasts Year 4-Hour Li-ion BESS 8-Hour Li-ion BESS 100-Hour Iron Air BESS 2027 $1,404.11 $2,504.86 – 2028 $1,367.46 $2,427.72 – 2029 $1,344.82 $2,375.00 – 2030 $1,320.73 $2,319.06 $2,278.25 2031 $1,326.37 $2,326.12 $2,232.68 2032 $1,331.71 $2,332.55 $2,237.15 2033 $1,336.72 $2,338.33 $2,241.62 2034 $1,341.41 $2,343.43 $2,246.11 2035 $1,345.75 $2,347.81 $2,250.60 2036 $1,349.73 $2,351.46 $2,255.10 2037 $1,353.33 $2,354.35 $2,259.61 2038 $1,356.54 $2,356.43 $2,282.21 2039 $1,359.33 $2,357.68 $2,305.03 2040 $1,361.70 $2,358.07 $2,328.08 2041 $1,363.61 $2,357.56 $2,351.36 2042 $1,365.06 $2,356.12 $2,386.63 2043 $1,366.03 $2,353.72 $2,422.43 2044 $1,366.48 $2,350.31 $2,458.77 2045 $1,366.41 $2,345.87 $2,495.65 Table 31. Battery Energy Storage Systems Cost Forecasts ($/kW) 768 of 839
E. Key Modeling Assumptions Generation Resource Cost Forecasts Glendale Water & Power 2024 IRP E-3
Year Hydrogen CT CCS SMR 2030 $1,860.76 $2,881.03 – 2031 $1,877.85 $2,872.54 – 2032 $1,896.89 $2,862.40 $5,000.00 2033 $1,916.21 $2,850.87 $5,000.00 2034 $1,935.59 $2,837.57 $5,000.00 2035 $1,955.05 $2,822.76 $5,000.00 2036 $1,974.35 $2,846.26 $5,000.00 2037 $1,993.92 $2,869.73 $5,000.00 2038 $2,015.62 $2,892.83 $5,000.00 2039 $2,037.38 $2,915.88 $5,000.00 2040 $2,058.97 $2,938.52 $5,000.00 2041 $2,080.86 $2,961.08 $5,000.00 2042 $2,102.80 $2,983.19 $5,000.00 2043 $2,124.78 $3,005.17 $5,000.00 2044 $2,146.80 $3,026.66 $5,000.00 2045 $2,168.59 $3,048.00 $5,000.00 Table 32. Hydrogen CT, CCS, and SMR Cost Forecasts ($/kW) Year Hydrogen Fuel Price ($/MMBtu) California Carbon Price ($/Ton) Social Cost of Carbon ($/Ton) 2024 $14.64 $27.77 $208.00 2025 $13.59 $28.45 $212.00 2026 $12.57 $29.72 $215.00 2027 $11.58 $31.63 $219.00 2028 $10.63 $34.26 $223.00 2029 $9.71 $37.66 $226.00 2030 $8.81 $41.93 $230.00 2031 $8.46 $47.15 $234.00 2032 $8.11 $53.41 $237.00 2033 $7.76 $57.15 $241.00 2034 $7.41 $61.15 $245.00 2035 $7.51 $65.43 $248.00 2036 $7.63 $70.01 $252.00 2037 $7.77 $74.91 $256.00 2038 $7.92 $80.15 $259.00 2039 $8.09 $85.76 $263.00 2040 $8.28 $91.76 $267.00 2041 $8.49 $98.19 $271.00 2042 $8.72 $105.06 $275.00 2043 $8.97 $112.42 $279.00 2044 $9.24 $120.28 $283.00 2045 $9.53 $128.70 $287.00 Table 33. Hydrogen Fuel, California Carbon, and Social Cost of Carbon Price Forecasts 769 of 839
E. Key Modeling Assumptions Power and Natural Gas Fuel Price Forecasts Glendale Water & Power 2024 IRP E-4
POWER AND NATURAL GAS FUEL PRICE FORECASTS
Year Mth Power SP-15 Off-Peak Power SP-15 On-Peak Natural Gas SoCal CityGate 2024 Jan $90.55 $95.61 $8.95 Feb $79.82 $79.12 $8.22 Mar $55.08 $46.07 $5.50 Apr $42.93 $33.11 $4.26 May $38.63 $29.45 $4.00 Jun $49.17 $54.45 $4.21 Jul $67.35 $102.20 $6.28 Aug $81.23 $116.63 $6.36 Sep $68.45 $102.05 $6.23 Oct $56.47 $58.86 $4.35 Nov $62.25 $63.56 $5.79 Dec $92.82 $96.85 $8.10 2025 Jan $100.58 $92.59 $7.65 Feb $72.79 $64.09 $7.29 Mar $57.22 $48.72 $5.36 Apr $41.01 $29.37 $4.98 May $36.91 $25.37 $4.93 Jun $56.44 $45.79 $5.04 Jul $80.22 $100.93 $6.05 Aug $80.10 $106.00 $6.09 Sep $81.07 $99.48 $5.94 Oct $60.73 $54.38 $4.88 Nov $60.53 $53.68 $6.42 Dec $100.26 $93.57 $7.93 Year Mth Power SP-15 Off-Peak Power SP-15 On-Peak Natural Gas SoCal CityGate 2026 Jan $104.94 $88.80 $7.23 Feb $78.72 $63.00 $6.95 Mar $61.94 $47.30 $5.52 Apr $37.35 $26.79 $4.28 May $32.38 $23.37 $4.23 Jun $45.50 $37.55 $4.35 Jul $81.47 $98.16 $5.72 Aug $87.57 $104.36 $5.77 Sep $82.87 $97.56 $5.58 Oct $71.94 $55.31 $4.81 Nov $70.66 $54.63 $6.53 Dec $113.80 $92.42 $7.53 2027 Jan $104.86 $88.03 $7.37 Feb $78.20 $62.00 $7.09 Mar $60.93 $45.25 $5.63 Apr $36.91 $25.50 $4.36 May $31.80 $21.50 $4.32 Jun $43.48 $34.21 $4.43 Jul $78.53 $90.80 $5.83 Aug $84.25 $98.22 $5.88 Sep $79.05 $91.37 $5.69 Oct $68.42 $51.62 $4.91 Nov $66.42 $50.36 $6.66 Dec $106.83 $84.47 $7.68 770 of 839
E. Key Modeling Assumptions Power and Natural Gas Fuel Price Forecasts Glendale Water & Power 2024 IRP E-5
Year Mth Power SP-15 Off-Peak Power SP-15 On-Peak Natural Gas SoCal CityGate 2028 Jan $98.22 $80.09 $7.52 Feb $72.17 $55.08 $7.23 Mar $56.79 $41.20 $5.75 Apr $33.89 $22.71 $4.45 May $29.77 $19.09 $4.40 Jun $40.63 $30.28 $4.52 Jul $71.42 $80.07 $5.95 Aug $78.19 $86.97 $6.00 Sep $74.32 $81.04 $5.81 Oct $63.60 $45.89 $5.01 Nov $62.01 $45.55 $6.79 Dec $98.71 $76.22 $7.83 2029 Jan $92.46 $75.87 $7.67 Feb $68.16 $50.96 $7.38 Mar $54.99 $38.29 $5.86 Apr $32.39 $21.23 $4.54 May $28.45 $17.82 $4.49 Jun $38.75 $28.20 $4.61 Jul $67.50 $73.96 $6.07 Aug $73.89 $80.35 $6.12 Sep $70.30 $74.93 $5.92 Oct $61.58 $42.58 $5.11 Nov $58.61 $42.89 $6.92 Dec $92.93 $69.87 $7.99 Year Mth Power SP-15 Off-Peak Power SP-15 On-Peak Natural Gas SoCal CityGate 2030 Jan $88.09 $71.45 $7.82 Feb $65.44 $49.14 $7.53 Mar $52.09 $36.28 $5.98 Apr $31.57 $20.28 $4.63 May $27.14 $17.58 $4.58 Jun $36.89 $27.28 $4.71 Jul $64.96 $71.49 $6.19 Aug $71.19 $80.37 $6.24 Sep $68.33 $75.67 $6.04 Oct $59.45 $43.62 $5.21 Nov $57.14 $42.85 $7.06 Dec $90.94 $70.19 $8.15 2031 Jan $86.30 $69.55 $7.98 Feb $63.45 $48.32 $7.68 Mar $52.47 $37.24 $6.10 Apr $31.83 $20.73 $4.72 May $27.58 $18.05 $4.67 Jun $37.70 $27.90 $4.80 Jul $65.95 $72.15 $6.31 Aug $72.79 $81.38 $6.37 Sep $70.08 $76.89 $6.16 Oct $62.74 $44.70 $5.31 Nov $58.91 $44.33 $7.20 Dec $92.45 $72.15 $8.31 771 of 839
E. Key Modeling Assumptions Power and Natural Gas Fuel Price Forecasts Glendale Water & Power 2024 IRP E-6
Year Mth Power SP-15 Off-Peak Power SP-15 On-Peak Natural Gas SoCal CityGate 2032 Jan $87.51 $71.44 $8.14 Feb $65.87 $49.67 $7.83 Mar $55.14 $38.62 $6.22 Apr $33.18 $21.73 $4.82 May $29.48 $18.91 $4.77 Jun $40.33 $29.16 $4.90 Jul $69.84 $76.65 $6.44 Aug $77.32 $84.19 $6.49 Sep $74.80 $79.73 $6.28 Oct $67.65 $46.69 $5.42 Nov $62.84 $45.73 $7.35 Dec $98.31 $74.03 $8.48 2033 Jan $90.72 $71.66 $8.30 Feb $66.93 $49.98 $7.99 Mar $57.60 $40.24 $6.34 Apr $34.92 $22.27 $4.91 May $31.03 $20.01 $4.86 Jun $42.39 $30.90 $4.99 Jul $72.74 $78.41 $6.57 Aug $80.56 $86.48 $6.62 Sep $78.07 $84.43 $6.41 Oct $69.54 $49.83 $5.53 Nov $65.31 $47.28 $7.50 Dec $101.74 $76.46 $8.65 Year Mth Power SP-15 Off-Peak Power SP-15 On-Peak Natural Gas SoCal CityGate 2034 Jan $93.29 $75.35 $8.47 Feb $68.83 $51.28 $8.15 Mar $59.56 $41.48 $6.47 Apr $36.28 $23.04 $5.01 May $32.25 $20.71 $4.96 Jun $42.95 $31.91 $5.09 Jul $75.00 $80.52 $6.70 Aug $83.11 $91.35 $6.76 Sep $80.67 $86.99 $6.54 Oct $72.12 $51.54 $5.64 Nov $68.65 $49.79 $7.65 Dec $104.47 $78.34 $8.82 2035 Jan $95.20 $76.75 $8.64 Feb $70.27 $52.23 $8.31 Mar $61.31 $42.56 $6.60 Apr $37.65 $23.79 $5.11 May $33.47 $21.40 $5.06 Jun $44.48 $32.89 $5.20 Jul $76.96 $82.25 $6.83 Aug $85.32 $93.49 $6.89 Sep $82.97 $89.21 $6.67 Oct $74.61 $53.16 $5.75 Nov $70.30 $50.85 $7.80 Dec $106.42 $79.42 $9.00 772 of 839
E. Key Modeling Assumptions Power and Natural Gas Fuel Price Forecasts Glendale Water & Power 2024 IRP E-7
Year Mth Power SP-15 Off-Peak Power SP-15 On-Peak Natural Gas SoCal CityGate 2036 Jan $96.20 $77.29 $8.81 Feb $69.60 $52.57 $8.48 Mar $62.82 $44.40 $6.73 Apr $39.13 $25.96 $5.21 May $35.65 $23.29 $5.16 Jun $46.19 $35.75 $5.30 Jul $78.68 $87.48 $6.97 Aug $86.98 $96.12 $7.03 Sep $84.53 $91.56 $6.80 Oct $76.45 $54.87 $5.87 Nov $70.69 $51.41 $7.95 Dec $103.82 $79.72 $9.18 2037 Jan $89.67 $72.78 $8.99 Feb $66.22 $49.61 $8.64 Mar $58.69 $42.18 $6.87 Apr $36.73 $25.61 $5.32 May $33.39 $22.98 $5.26 Jun $44.21 $34.31 $5.41 Jul $72.74 $85.52 $7.11 Aug $80.40 $91.24 $7.17 Sep $78.20 $86.91 $6.94 Oct $71.02 $52.30 $5.98 Nov $65.13 $48.52 $8.11 Dec $95.30 $73.19 $9.36 Year Mth Power SP-15 Off-Peak Power SP-15 On-Peak Natural Gas SoCal CityGate 2038 Jan $85.15 $70.59 $9.17 Feb $62.74 $48.05 $8.82 Mar $55.14 $41.56 $7.00 Apr $34.93 $24.35 $5.42 May $31.74 $21.85 $5.37 Jun $42.06 $33.62 $5.51 Jul $69.95 $82.24 $7.25 Aug $77.34 $87.77 $7.31 Sep $73.51 $83.50 $7.08 Oct $67.84 $49.96 $6.10 Nov $61.66 $46.88 $8.28 Dec $92.56 $71.08 $9.55 2039 Jan $84.74 $70.25 $9.35 Feb $61.02 $47.79 $8.99 Mar $54.60 $41.15 $7.14 Apr $34.41 $24.65 $5.53 May $30.53 $22.12 $5.48 Jun $40.44 $34.09 $5.62 Jul $69.31 $83.72 $7.40 Aug $74.93 $89.29 $7.46 Sep $72.80 $82.70 $7.22 Oct $65.54 $49.33 $6.23 Nov $59.99 $46.57 $8.44 Dec $90.25 $70.79 $9.74 773 of 839
E. Key Modeling Assumptions Power and Natural Gas Fuel Price Forecasts Glendale Water & Power 2024 IRP E-8
Year Mth Power SP-15 Off-Peak Power SP-15 On-Peak Natural Gas SoCal CityGate 2040 Jan $82.47 $68.18 $9.54 Feb $59.28 $46.28 $9.17 Mar $52.82 $39.68 $7.29 Apr $32.24 $22.94 $5.64 May $29.31 $21.16 $5.59 Jun $38.81 $32.60 $5.74 Jul $67.01 $80.66 $7.54 Aug $72.48 $86.12 $7.61 Sep $70.44 $79.75 $7.36 Oct $63.22 $48.66 $6.35 Nov $59.54 $45.13 $8.61 Dec $87.91 $68.75 $9.93 2041 Jan $80.97 $68.42 $9.73 Feb $59.46 $46.43 $9.36 Mar $52.82 $39.68 $7.43 Apr $32.12 $23.51 $5.76 May $29.20 $21.08 $5.70 Jun $38.68 $32.49 $5.85 Jul $67.05 $80.71 $7.70 Aug $72.53 $86.18 $7.76 Sep $70.45 $79.77 $7.51 Oct $63.10 $48.57 $6.48 Nov $59.68 $45.23 $8.78 Dec $88.27 $69.03 $10.13 Year Mth Power SP-15 Off-Peak Power SP-15 On-Peak Natural Gas SoCal CityGate 2042 Jan $82.88 $68.31 $9.92 Feb $59.47 $46.30 $9.54 Mar $52.89 $39.59 $7.58 Apr $32.11 $23.43 $5.87 May $29.20 $21.61 $5.81 Jun $38.65 $32.34 $5.97 Jul $67.04 $80.41 $7.85 Aug $72.55 $85.94 $7.92 Sep $70.54 $81.70 $7.66 Oct $63.21 $48.50 $6.61 Nov $59.82 $46.30 $8.96 Dec $88.37 $70.65 $10.33 2043 Jan $83.29 $70.20 $10.12 Feb $59.70 $47.59 $9.74 Mar $53.19 $41.83 $7.73 Apr $33.11 $24.16 $5.99 May $30.11 $22.28 $5.93 Jun $39.84 $33.34 $6.09 Jul $68.99 $82.75 $8.01 Aug $74.66 $88.44 $8.07 Sep $70.94 $84.09 $7.81 Oct $65.12 $49.97 $6.74 Nov $60.20 $47.61 $9.14 Dec $90.80 $70.81 $10.54 774 of 839
E. Key Modeling Assumptions Power and Natural Gas Fuel Price Forecasts Glendale Water & Power 2024 IRP E-9
Year Mth Power SP-15 Off-Peak Power SP-15 On-Peak Natural Gas SoCal CityGate 2044 Jan $83.69 $70.36 $10.32 Feb $59.92 $47.64 $9.93 Mar $53.48 $41.96 $7.89 Apr $33.28 $24.21 $6.11 May $30.29 $22.34 $6.05 Jun $40.02 $34.38 $6.21 Jul $69.28 $85.17 $8.17 Aug $75.01 $88.59 $8.23 Sep $71.33 $84.33 $7.97 Oct $65.56 $50.16 $6.87 Nov $61.91 $47.79 $9.32 Dec $91.24 $72.76 $10.75 2045 Jan $84.11 $70.54 $10.53 Feb $60.15 $47.71 $10.13 Mar $53.80 $42.10 $8.04 Apr $33.47 $24.27 $6.23 May $30.48 $22.42 $6.17 Jun $39.14 $34.44 $6.33 Jul $69.61 $85.31 $8.33 Aug $75.40 $88.78 $8.40 Sep $71.75 $84.62 $8.13 Oct $66.05 $50.38 $7.01 Nov $62.35 $49.19 $9.51 Dec $91.73 $72.96 $10.97 Table 34. Power (Off-Peak & On-Peak) and Natural Gas Price Forecasts 775 of 839
Glendale Water & Power 2024 IRP F-1
F. Po w e r S I M M P l a n n e r
POWERSIMM OVERVIEW PowerSIMM is a software program used for simulating the performance of an electric power system with high spatial and temporal granularity. This section provides an overview of the key features and capabilities of this simulation software. In the IRP analysis, PowerSIMM was used for the following applications: § Production Cost Modeling: Simulates power system operations, inclusive of transmission constraints, on an hourly or sub-hourly timestep for use in decision making for portfolio management or resource planning. § Capacity Expansion Optimization: Provides a roadmap of future resource procurements to meet policy or reliability needs at the lowest cost. § Resource Adequacy Analysis: Determines how well a portfolio of resources can serve customer load over a defined period of time on an hourly basis. All applications start with simulations of weather, load, renewables, forced outages, and market prices. The only exception is in resource adequacy models where prices are not used.
Simulations in PowerSIMM PowerSIMM simulations start with weather as the fundamental driver of load, renewable generation, and market prices. Weather simulations consist of daily maximum and minimum temperatures. PowerSIMM uses historical temperatures to construct future simulations of weather with a time-series model that includes seasonal inputs. Renewable items require hourly historical generation data coupled with weather data from a nearby station to determine the structural relationship between daily min and max temperatures and renewable generation. PowerSIMM constructs a model for each renewable item using inputs that include daily min and max temperatures, month, and hour. Future simulations are generated with the model using weather simulations as an input. Generation output is scaled to meet future expectations for monthly energy generation and capacity limits. 776 of 839
F. PowerSIMM Planner PowerSIMM Overview
Glendale Water & Power 2024 IRP F-2
For load, PowerSIMM creates a structural model using hourly load data, daily min and max temperatures, hour, day of the week, and month. Load simulations are based on weather simulations and scaled to match load forecasts for monthly energy and peak demand. The simulation of market prices follows a similar construct, but there are more structural variables observed in both historic and forecast values. There are also more parameters used as inputs. For market price simulations, PowerSIMM adheres to market expectations (that is, forward prices and option quotes for volatility in prices) by scaling simulations such that the average price exactly meets the forward curves for monthly average prices for natural gas, on-peak power, off-peak power, and carbon. The stochastic price ranges hold to future expectations of price volatility, correlations across time and commodities, and daily price shapes. Additional details on the model simulations can be found in “Simulation Details” (page B-7).
Dispatch in PowerSIMM Simulations of weather, load, renewables, and spot prices roll into the dispatch module. PowerSIMM models dispatch by optimizing supply resource options in a “dispatch to load” or “dispatch to price” model. In a dispatch to load model, PowerSIMM calculates dispatch decisions to serve load at the least cost, while accounting for transmission system congestion. Market purchases are generally, but not always, included as an option for serving load. The dispatch to price model calculates dispatch decisions to maximize market revenue from generation. Dispatch calculations rely on inputs to define the physical and economic characteristics of supply resources, including thermal resources, energy storage, hydro resources, or demand-side options. Users can also define transmission lines to represent constraints, such as import or export limits, or line losses. Ancillary services can be included in dispatch models where PowerSIMM will co-optimize supply resources to serve load and fulfill ancillary requirements. PowerSIMM ancillary product dispatch can include regulation up, regulation down, spinning reserves, and non-spinning reserves. PowerSIMM can also perform multiphase dispatch. PowerSIMM uses a mix-integer linear programming algorithm in the dispatch calculations. The objective function in the algorithm is the minimization of cost to supply energy and ancillary requirements. Included in the total cost are startup costs, variable operations and maintenance (VOM) costs, fixed O&M costs, fuel costs and fuel delivery costs, electric power purchases and power sales. Power sales are treated as negative costs. 777 of 839
F. PowerSIMM Planner Resource Planning Modeling
Glendale Water & Power 2024 IRP F-3
The decision variables for the dispatch algorithm include the online state of dispatchable generators, the generation setting for all dispatchable generators, the assignment of ancillary services for units capable of providing ancillary services, the charge or discharge state of energy storage resources, and the amount of market purchases. PowerSIMM iterates over a range of possible values to settle on the decision variables that provide the lowest possible cost within the model constraints. Dispatch constraints are set for all units in the model such as economic max generation, economic min generation, ramp rates, must run requirements, minimum generation, etc. There are also constraints attributable to transmission limits and the requirement to meet load. Variable generation from wind, solar and geothermal items are not considered dispatchable, but PowerSIMM may elect to curtail variable resources if system conditions require it. For example, wind generation may be curtailed due to transmission limits.
RESOURCE PLANNING MODELING PowerSIMM was used to run a variety of models for this resource plan. This section describes the types of models used for the plan.
Production Cost Modeling The most common application of PowerSIMM in resource planning is as a production cost model, which shows many detailed aspects of system operations over a future time period. Production cost models can run with dispatch modeled across a range of simulated future conditions. Outputs from production cost models include generation costs, fuel consumption, renewable generation, carbon emissions, and a long list of additional variables used to make investment and operational decisions. Example uses for PowerSIMM include analyzing options to hedge fuel price risk, evaluating new generation resource options, or conducting a study to determine renewable additions for RPS mandates. Production cost model outputs allow users to understand how the system will operate with the assumed inputs. Figure 103 shows hourly dispatch outputs over a three-day period from a production cost model plotted against load. Comparing outputs from two or more production cost models allows a user to 778 of 839
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understand how changes in resource mix, price forecast, operational constraints, or other aspects of the system will affect future outcomes.
Figure 103. Three-Day Dispatch Outputs Plotted against Load Key inputs for production cost models include the simulated system conditions17 and supply resource operating parameters. The operating parameters of dispatchable generation assets in the portfolio—such as ramp rates or start-up times for thermal assets, leakage rates and round-trip efficiencies for battery storage, or spill requirements for hydro—guide dispatch optimization to ensure the model adheres to the actual physical capabilities and attributes of the resources in the portfolio.
Capacity Expansion Optimization A second common application of PowerSIMM in resource planning is for capacity expansion optimization, which provides the least-cost selection of future resources over time, subject to user-specified constraints. Such constraints may include resource adequacy requirements, annual energy positions, renewable portfolio standards, or carbon emission limits. The Automatic Resource Selection (ARS) module contains the PowerSIMM capacity expansion model. ARS evaluates the performance of a portfolio of existing resources and candidate resources across a range of future operating conditions to assess their likely revenues, costs, and other characteristics (for example, carbon emissions). Based on the user inputs and constraints, the model determines the optimal resource additions (or retirements) for minimizing total costs while ensuring the generation portfolio can serve load without violating loss-of-load standards or emissions constraints. 17 Weather, load, renewables, and market prices for fuel and power, when not a dispatch to load without intertie purchases. 779 of 839
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Figure 104 illustrates an ARS model that adds candidate resources to a portfolio to serve load at the lowest cost. The portfolio of existing resources and customer load are evaluated with candidate resources across a range of future conditions to select the optimal portfolio composition under input constraints.
Figure 104. ARS Schematic of Candidate Resource Expansion The input data requirements for ARS are generally the same as for production cost modeling except for additional project cost information (for example, new candidate resources), accredited capacity (for example, existing and new resources), and project specific constraints such as annual build limits for new resources. Users must also define model constraints to apply in the resource selection process, such as requirements for capacity, energy, or renewable generation.
Resource Adequacy Analysis The third main application of PowerSIMM in resource planning is for resource adequacy analysis, which is used to assess the probability that a system will have adequate generation resources to meet load over a wide range of conditions. Common metrics for this assessment include loss-of-load probabilities (LOLP), expected unserved energy, and capacity deficit (the amount of additional capacity needed to meet reliability targets), among others. PowerSIMM’s resource adequacy module can also be used to assess the capacity contribution from specific resources or technology types, which is typically measured with the effective load-carrying capability (ELCC) metric. 780 of 839
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As shown in Figure 105, PowerSIMM’s simulation engine provides simulations of load, renewables, and forced outages used to analyze the ability of a portfolio of resources to serve load. Resource adequacy models may also include transmission constraints.
Figure 105. PowerSIMM Simulation Engine The PowerSIMM resource adequacy model considers weather variability as a key driver to renewable and load simulation. These simulations are coupled with stochastically imposed forced outage in the dispatch module to measure common metrics, including LOLP, loss-of-load expectations (LOLE), or loss-of-load hours (LOLH), expected unserved energy, and capacity deficit (MW short). The dispatch algorithm in a resource adequacy model differs from that used in production cost or capacity expansion models. Resource adequacy models evaluate systems based on how well they can meet system needs, so the ability to import power is typically eliminated (or significantly restricted). The model dispatches resources to minimize load shedding without regard to dispatch cost. Market prices also have no bearing on the dispatch decision in a resource adequacy model. Instead, the important inputs driving resource adequacy results include forced outage rates, correlation between load and renewables, and operational constraints. In each simulated hour of a resource adequacy study, the model calculates hourly load requirements and compares this to the sum of total renewable generation, available thermal capacity (that is, not on forced or scheduled outage), and available energy in storage (which is charged with excess energy when it is available). The model then dispatches thermal and energy storage resources chronologically (hour-by-hour) to determine how much (if any) load cannot be met in each hour. Resource adequacy models provide metrics to evaluate the reliability of a system. Additionally, resource adequacy models provide a useful means of determining the capacity contribution of a specific resource, known as the ELCC. The standard approach for an ELCC analysis involves three model runs. The reliability contribution of the ELCC resource is compared to the reliability contribution from a “perfect” generator to determine the capacity value of the ELCC resource. 781 of 839
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SIMULATION DETAILS Weather Simulation PowerSIMM has the ability to simulate weather across dozens of weather variables. Weather simulations in PowerSIMM typically include daily maximum and minimum dry bulb temperatures. These temperatures are then used as fundamental drivers for the load and for alignment with renewable simulations. The weather simulation engine requires historical daily maximum and minimum temperatures from weather stations in proximity to the weather-related resources in the model. PowerSIMM stores historical data for hundreds of weather stations via automated data pulls from the National Climate Data Center. PowerSIMM users select weather stations to create weather zones for use in their specific studies. PowerSIMM creates weather simulations by decomposing historical daily maximum and minimum temperature data into seasonal and irregular components. The seasonal component represents a smooth function showing how temperature changes over the year. The irregular component captures fluctuations around the seasonal component and represents the day-to-day variability in weather, which is the stochastic part of the weather simulations. The model structure for the irregular component includes 30-day, 60-day, and 90-day moving averages combined in a linear fashion with autoregression and random error terms. Annual patterns drive most of the temperature simulations, but the irregular component of the model allows for deviations from annual and seasonal norms, enabling potential periods of cooler weather in the summer and warmer days in the winter. PowerSIMM’s default method for creating temperature simulations does not use a temperature forecast or include trends in temperature. The result is a set of simulations that resemble historical weather conditions. However, the models can be configured to account for changes in future temperatures to reflect predictions of a changing climate. 782 of 839
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The resulting simulations should reasonably match historical data. Figure 106 shows an example of daily maximum dry bulb temperature simulations across a single year.
Figure 106. Multiple Simulations of Daily Maximum Dry Bulb Temperatures The stochastic framework captures variations in weather conditions and extreme events. PowerSIMM has the capability to modify the statistical parameters of the temperature distribution to capture extreme events. Ascend runs validations to ensure that simulated temperatures align with historical values at the mean level along with the fifth percentile and ninety-fifth percentile.
Load Simulation PowerSIMM creates realistic simulations of load that maintain a strong non-linear relationship between load and temperature. The load simulations capture the range of uncertainty exhibited in historical load data. After fitting historical load data to a time series model, PowerSIMM scales the load simulations to match future expectations for energy consumption, peak demand growth, and daily load shapes. 0 20
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Simulations of load rely on past data to create accurate representation of the utility load that matches historical statistics in the near term while matching the load forecast inputs through the simulation time frame. By scaling load simulations to forecast values, PowerSIMM produces accurate simulations of load that provide a realistic range of future load values around the expected mean. Figure 107 shows a time series of multiple load simulations.
Figure 107. Multiple Simulations of Load Over a Single Week Figure 108 shows the load versus temperature relationship maintained in the load simulations— when temperatures are at their highest load is at its highest, driven by the need to cool.
Figure 108. Load versus Temperature Relationships
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Wind and Solar Simulation PowerSIMM generates simulations of renewables with time series models fit to hourly historical data. Accurate wind and solar generation simulations are an essential part of power system modeling for determining cost of service (COS), loss of load risks, resource valuation, and many other modeling outputs used in utility decision making. Wind and solar simulation models use a structure that assumes generation is a function of maximum and minimum temperature inputs from the weather simulations. The model also allows structural variables, like time of day and month of year, to affect generation. For example, if generation is typically highest on afternoons in spring, even apart from the influence of temperature, then the model will be able to capture that. Finally, the model includes autoregressive terms to capture the influence of generation in the previous hour to the current hour’s generation. In addition to daily temperatures, hour, and month, solar simulations include the solar irradiance calculated at the location of the solar resource. Solar irradiance is a function of the time of day, day of the year, and the longitude and latitude of a project. PowerSIMM scales monthly wind and solar simulations to match monthly forecasts. Realistic simulations of variable renewable energy generation lead to accurate analysis of the value of renewable assets and the effect of renewables in production cost studies, resource adequacy, or capacity expansion. Figure 109 provides an example of solar simulations over a week.
Figure 109. Multiple Simulations of Solar Generation Over a Single Week 785 of 839
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Figure 110 provides an example of wind simulations over a week.
Figure 110. Multiple Simulations of Wind Generation Over a Single Week 786 of 839
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Small Hydro Simulation PowerSIMM models small hydro resources as run-of-the-river hydro. Dispatchable hydro resources are set up as a hydro project in PowerSIMM. Like other variable renewable resources in PowerSIMM, hydro simulations use a time series model fit to historical hourly generation data. The outcome is a set of simulations that capture the full range of potential hydro generation to provide accurate results for utility decision making. While the structural details of the hydro simulation model differ from the wind and solar simulation models, the general inputs are similar. Hydro simulation models also assume generation is a function of maximum and minimum temperature inputs from the weather simulations. Like wind and solar simulations, the model used for hydro simulations also allows structural variables, like time of day and month of year, to affect the generation. The hydro model also includes autocorrelation terms. Hydro simulations are scaled to match future expectations for monthly generation and capacity. PowerSIMM ensures that average monthly hydro simulations match the hydro forecast values. Figure 111 shows hydro simulations over a one-week period.
Figure 111. Multiple Simulations of Hydro Generation Over a Single Week 787 of 839
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Forward Price Simulation PowerSIMM simulates forward curves using a stochastic model with parameters derived from recent historical transaction dates and defined user inputs (as applicable). PowerSIMM constructs a system of equations for forward contracts that includes the stochastic component of the forward price, as well as the correlation with neighboring contract months, and other commodities. This framework produces price simulations that are realistic, benchmark well to historical data, and produce a payoff of cash flows consistent with market option quotes at multiple strike prices. Forward contract prices are modeled with an autoregression, or AR, model with volatilities and correlations maintained in accordance with historical data or with inputs provided in the forward price constraints. PowerSIMM uses an AR lag of one while limiting the coefficient to a value of less than 1. An AR coefficient less than 1 is equivalent to a Geometric Brownian Motion model with mean reversion. Thus, the forward prices tend to do a random walk with a constant pull back to the monthly mean values. Figure 112 shows multiple simulations of forward prices. The mean across all simulations equals to the input forecast.
Figure 112. Multiple Simulations of Forward Prices
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Spot Price Simulation PowerSIMM simulates spot prices beginning with the market expectations of monthly blocks of energy represented as the average forward or forecast price over the monthly block. Following the forward price simulations, spot prices are simulated with a hybrid approach that captures the uncertainty in price risk in power markets and trading hubs, including variability in weather, load, renewable output, congestion risk, and locational marginal prices, while maintaining consistency with forward price simulations. A sample of hourly spot price simulations are shown in Figure 113 over the course of a week.
Figure 113. Simulations for Spot Prices Over a Single Week Basis Price Simulation Basis price items in PowerSIMM allow for models to contain multiple pricing nodes. The main market configuration in PowerSIMM must select a primary forward price and spot price for use in the price simulations. PowerSIMM derives basis prices as “structural” (regression-based model) or “basic” (random noise) items from the main spot price configured in the model. Basis prices are an important feature of PowerSIMM because they allow for market interactions and simulate locational marginal prices of different nodes. Scalars applied in the Basis model allow users to set up expected deviations in prices between the basis price (node) and the reference spot price (hub). Users may set up scalars as a constant value across all hours or as random variables where the parameters are a function of time. The Basis module can also be used to produce sub-hourly simulations and ancillary services prices. 0 20
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G. Energy Risk Management Policy
Risk is inherent in GWP’s ability to procure sustainable power at reasonable costs, to operate prudently in the wholesale energy markets, to ensure a robust distribution system, and to deliver reliable power to its customers. GWP’s Energy Risk Management Policy identifies those risks and establishes a plan to, as much as possible, mitigate them. The Policy outlines and formalizes guidelines for how to plan for and manage operational risks and identifies the people responsible for implementing these guidelines. The Policy establishes: § Business and risk management objectives § Governance structure and responsibilities § Scope of business activities associated with risk management § Associated guidelines, policy documents, and registry Implementing the Policy entails coordinating the actions of all GWP departments, which when successfully implemented, supports GWP’s strategic business plan, and safeguards its business and risks. The Policy describes the responsibilities of certain positions in each department, including the City Council, the City Manager, and GWP’s General Manager who, together with other City of Glendale staff, comprise the Energy Risk Management Committee (ERMC). This Policy details the steps necessary for the ERMC to ensure its successful implementation. Since the 2019 IRP, GWP has updated its Policy twice, first in July 2021 and then again in August 2022. GWP’s policy has worked well over the years; as a result, these updates were minor. 790 of 839
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2.1GWP Business Objectives 2
2.2GWP Risk Management Objectives 2
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3.1City Council 5
3.2 City Manager 5
3.3 GWP General Manager 6
3.4 GWP Energy Risk Management Committee (ERMC) 7
3.4.1 Energy Risk Management Committee Structure
3.4.2 Meeting Timing,Frequency, and Voting Procedures
3.4.3 Member Vacancies
3.4.4 Energy Risk Committee Responsibilities
3.5 GWP Chief or Assistant General Manager (Power Management) 10
3.6 GWP Assistant General Manager (Business Services) 10
3.7 GWP Integrated Resources Planning Administrator 11
3.8 GWP Energy Trading Manager 12
3.9 GWP Power Planning Manager 13
3.10 GWP Energy Risk Manager 14
3.11 GWP Power Contracts Manager 16
3.12 GWP Utility Finance Manager 17
3.13 GWP Utility Business System Support Administrator 18
3.14 City of Glendale Finance 18
3.15 City of Glendale Legal 19
3.16 City of Glendale Audit 19
3.17 Conflict of Interest and Compliance 20
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6.1 Reporting Requirements 21
Table 6.1 Reporting Requirements 21
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Energy Risk Management Policy
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Glendale Water & Power (GWP) is in the business of generation, transmission, and distribution of electricity for the benefit of the City of Glendale. One of GWP’s main objectives is to procure reliable and sustainable power for its customers at stable and predictable rates while optimizing existing and local resources.This Energy Risk Management Policy (the Policy) is designed to establish the framework for GWP to manage the risks that are inherent in the wholesale energy operations and markets it participates in.
The purpose of this Policy is to formally establish an energy risk management program and document the organizational structure (Figure 3.1) utilized by GWP to meet the electricity needs of its customers and provide approved guidelines for GWP to plan, execute, and control the management of a variety of risks associated with energy portfolio activities. The purpose of this Policy is also to formalize the policies of GWP regarding managing its energy risks. Accordingly, this Policy will set forth GWP’s:
risk management objectives;
risk governance structure and responsibilities;
scope of business activities governed by this Policy; and list of associated guidelines, policy documents, and registry.
GWP intends that energy risk management will support the advancement of its strategic business plan and will properly manage its business and financial risks through:
prudent oversight;
adequate mitigation of energy risks consistent with GWP’s defined risk registry and tolerance; and
sufficient internal controls and procedures.
Managing the energy risks of GWP entails the coordination of resources and activities among all departments within GWP and within the City of Glendale (CoG) governance structure.
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An effective energy risk management policy better equips a utility to achieve its energy portfolio objectives. This Policy is focused on helping GWP achieve these business objectives:
Provide reliable, sustainable power to retail customers; Manage the energy portfolio to stabilize rates;
Comply with mandatory renewable and clean energy standards and other regulatory requirements;
Provide renewable and clean energy while reducing carbon and other emissions;
Allow for hedging to protect against adverse changes in energy market prices and mitigate the risk to customers of significant rate increases and budget shortfalls;
Allow for providing price and risk differentiated energy products to customers as appropriate;
Optimize GWP’s existing energy portfolio resources; and Protect GWP’s systems, communications, and data against risks associated with cybersecurity.
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The primary goal of this Policy and resulting risk management activities is to strengthen GWP’s ability to provide reliable, sustainable power to its retail customers at stable, predictable rates while managing risks and complying with mandatory regulatory requirements. This goal is best achieved by enabling GWP to transact in different energy commodity markets while monitoring, minimizing, and mitigating associated risks.
Other goals of risk management activities are to:
Maintain risks within desired tolerances for a defined period in the future; Enhance the value of GWP’s assets/resources;
Participate in commodity markets and derivative instruments for hedging and not speculative purposes;
Develop a risk management culture and support GWP’s ongoing strategic planning process;
Manage a portfolio of physical and financial positions to help stabilize the cost of energy with associated risks while maintaining reliable energy supplies for customers and meeting regulatory requirements; Identify, quantify, and monitor market and regulatory risks; 795 of 839
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3 Monitor trading activity to identify and report if policy violations occur and if authority limits are exceeded without proper approval;
Work within the existing organizational structure to implement the Policy; Remain flexible to accommodate changing needs of GWP’s energy portfolio while maintaining control of the overall risk position; and Operate a disciplined program to manage budget, cash flows, margining, and transaction execution.
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Risk governance will follow a top-down approach whereby the GWP Energy Risk Management Committee (ERMC) identifies GWP’s energy risk management objectives and provides energy risk management oversight, consistent with the rates, annual budget, policies, and transaction authorities that are all periodically adopted by the City Council. Supporting controls, policies, and procedures will be implemented and aligned throughout the risk governance structure, with distinct roles and responsibilities that result in an energy risk controlled environment. Governance and controls include the organizational structure, policies, reporting processes, and procedures that support GWP’s business models, risk tolerances, energy supply objectives, and appropriately segregate responsibilities.
The following sections identify and describe the levels within the organization with oversight and direct responsibility for the implementation of this Policy and the resulting program.
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The following organizational chart illustrates the roles and functions responsible for the implementation of risk management activities within this Policy. Also, it identifies the appropriate segregation of duties within GWP for the primary functions that manage energy commodities:
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The City of Glendale City Council shall:
Adopt an electric utility annual budget;
Review and approve retail electric customer rate changes; Review and approve changes to the GWP Electric System Cash Reserve Policy;
Approve transaction authorities for the City Manager and the GWP General Manager established according to the Trading Authority Policy; Approve recommended changes to the Energy Risk Management Policy that establishes an overall framework for evaluation, management, and control of energy risk for GWP.
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The City Manager is responsible for providing the oversight of and support for GWP’s energy risk management philosophies and principles. The City Manager shall:
Establish scope and frequency of any GWP management reporting to the City Council;
Periodically review energy risk exposures and compliance with policies and procedures;
Discuss GWP’s energy risk exposures and the steps GWP management has taken or will take to mitigate, control, and monitor such exposures, as documented in GWP’s Risk Registry;
Require adequate management involvement, financial controls, and systems to monitor, report, and ensure the integrity of this Policy at all levels;
Periodically review this Policy and the related policies as defined in Section 5, and recommend changes proposed by the GWP ERMC to the City Council and/or such other changes as the City Manager deems advisable; and
Approve a Trading Authority Delegation reflecting delegation of trading authority and limits. Periodically review the Trading Authority Delegation and recommend proposed revisions, as needed; and
Serve on the ERMC.
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The GWP General Manager is responsible for the overall direction, structure, conduct, control, mitigation, reporting, and enforcement of GWP’s risk management activities. The GWP General Manager shall:
Establish a risk management culture throughout the organization; Periodically assess the adequacy and functioning of the system of controls over market, credit, and operational risks;
Ensure that all energy risk control activities (e.g., position monitoring, portfolio assessment, credit) are independent of energy purchases and sales;
Approve a Trading Authority Delegation reflecting delegation of trading authority and limits. At a minimum, annually review the Trading Authority Delegation and revise, as needed;
Report to the City Manager on GWP’s energy risk management activities, achievements, and goals;
Annually review with the ERMC and assure compliance with the Energy Risk Management Policy and related policies, as defined in Section 5; Review with the GWP ERMC on GWP’s compliance with its energy risk policies and energy risk management in accordance with the policies; Periodically report, to the City Manager, the risk profile of GWP’s energy portfolio and on the results of energy risk management activities; Have authority to transact within the limits set by the City Council in the Trading Authority Policy;
Approve proper organization, separation, or consolidation of functional activities;
Ensure that the identification and quantification of energy risks and related energy risk mitigation strategies, as documented in GWP’s Risk Registry, are integrated into the GWP strategic planning process; and Establish and maintain an effective working relationship with associated energy service providers; and
Serve on the ERMC.
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Glendale Water & Power 2024 IRP G-11 Glendale Water & Power August 2022 7 Energy Risk Management Policy
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The GWP ERMC has the responsibility for managing the target energy risk profiles and leading GWP’s energy risk management efforts on a path of continuous improvement. The GWP ERMC will provide direction and oversight to GWP concerning power supply planning, transacting, hedging, reporting, and related internal controls; and the development and implementation of policies and procedures consistent with this Policy.
The GWP ERMC establishes a forum for discussion of GWP’s significant energy risks and must develop guidelines required to implement an appropriate energy risk management control infrastructure; this includes implementation and monitoring of compliance with GWP’s energy risk management-related policies, as defined in Section 5. The GWP ERMC executes its energy risk management responsibilities through direct oversight and prudent delegation of its responsibilities to the independent energy risk management function, as well as to other GWP and City of Glendale (CoG) personnel.
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Voting Membership:
The GWP ERMC shall be comprised of six voting members and seven non-voting members.
The six voting members are:
1.City Manager;
2.GWP General Manager (Chair);
3.GWP Chief or Assistant General Manager (Power Management), or as designated by the GWP General Manager;
4.GWP Assistant General Manager (Business Services) or as designated by the GWP General Manager;
5.GWP Energy Risk Manager; and
6.CoG Director of Finance/Information Technology.
Non-voting participants shall include, but not limited to:
1.GWP Integrated Resources Planning Administrator;
2.GWP Trading Manager;
3.GWP Utility Business System Support Administrator;
4.GWP Utility Finance Manager;
5.CoG Attorney;
6.Power Planning Manager; and
7.CoG Internal Audit Manager.
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8 3.4.2 0HHWLQJ7LPLQJ)UHTXHQF\DQG9RWLQJ3URFHGXUHV The GWP ERMC shall meet no less than once per calendar quarter.
Member attendance shall be recorded in the GWP ERMC meeting minutes.
Any voting member of the GWP ERMC can request an emergency meeting of the GWP ERMC to address circumstances or issues that may require immediate attention. n the event any member or participant is unable to attend a GWP ERMC meeting, that member or participant may designate an alternate to attend and vote in his or her absence.
The six voting members shall each have a single vote on matters that come before the GWP ERMC and a voting member, or designee, must participate in the GWP ERMC meeting in order to vote and approve a proposed action. If any three of the voting members, or their designees, are not present at a GWP ERMC meeting, a vote on a proposed action cannot take place. The GWP ERMC will make decisions and take actions by a simple majority vote. If the GWP ERMC reaches an impasse that cannot be addressed through a vote or if a tie vote occurs, the GWP General Manager will make a final decision.
3.4.3 0HPEHU9DFDQFLHV
In cases where a committee member vacates the GWP ERMC, the GWP General Manager will resolve the GWP ERMC vacancy by making a discretionary interim appointment.
The GWP General Manager will designate a Secretary to the GWP ERMC to document all meetings and actions taken by the GWP ERMC in meeting minutes that will be distributed to GWP ERMC members for their review and approval. The Secretary need not be a member of the GWP ERMC.
Approved meeting minutes will be distributed by the Secretary to the GWP ERMC members.
3.4.4 *:3(QHUJ\5LVN0DQDJHPHQW&RPPLWWHH5HVSRQVLELOLWLHV The GWP ERMC is responsible for:
Aligning energy risk management with City Council approved budgets, rates, policies and transaction authorities;
Setting a clear strategy and goals for hedging market price risk via the Hedge Policy; reviewing and approving risk management strategies and hedging plans to be implemented by GWP;
Establishing the scope of energy portfolio and risk management activities, the purpose for engaging in transactions, and the appropriate risk tolerances consistent with strategic direction;
Establishing the strategic direction and risk threshold for retail load energy needs and wholesale transactions; reviewing and approving 801 of 839
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9 proposed energy risk management strategies for strategic fit, evaluate risk exposure consistent with energy risk tolerances, and reporting and control requirements. The GWP ERMC shall ensure that approved strategies are consistent with GWP’s approved strategic business plan, energy risk management objectives, approved energy risk tolerance guidelines, and compliance with energy risk policies;
Reviewing reports by the independent energy risk management function concerning policy and procedural compliance and taking appropriate action to mitigate losses or increased risks, if any, as necessary; Providing oversight and direction for specific projects including new markets, RFP development and review of RFP responses for physical and financial energy, fuel, related transportation transactions, and tools and systems needed to manage the risks of participation in energy markets;
Discussing elements of energy risk management best practices and developing an GWP ERMC opinion of their specific practicality; Overseeing the implementation and review of related Standard Operating Procedures and changes to them;
Conducting other activities relevant to the implementation and oversight of this Policy and related policies, as defined in Section 5, and procedures;
Recommending to the GWP General Manager the proper organizational structure, separation or consolidation of functional risk management activities;
At least, annually, review GWP’s energy risk management program and Risk Registry due to changes in business practices, improved procedures, GWP’s philosophy and strategy, or market changes; and ensuring continued compliance with its established guidelines; Reviewing this Policy and related policies as defined in Section 5, on an annual basis and recommending changes to this Policy to the City Manager for submittal to the City Council for approval; and Approving and periodically reviewing the related policies defined in Section 5.
802 of 839
G. Energy Risk Management Policy
Glendale Water & Power 2024 IRP G-14
Energy Risk Management Policy
Glendale Water & Power August 2022
10 3.5 *:3&+,()25$66,67$17*(1(5$/0$1$*(5
32:(50$1$*(0(17
The GWP Assistant General Manager or designee, as relates to Power Management Services, oversees the “front office,” reports directly to the GWP General Manager, and responsible for GWP’s overall energy supply. The GWP Assistant General Manager (Supply) shall:
Develop and maintain retail load forecasts and retail fuel and purchase power budgets;
Assure compliance with this Policy and related policies, as defined in Section 5, by the Energy Trading Manager and Marketers, Analysts and Schedulers, Real-time Traders or Authorized Agents, and the GWP Power Contacts Manager involved in energy risk management activities; Establish a review and approval process to provide timely responses to issues arising from day-to-day operations;
Oversee the development of hedge strategies to manage GWP’s energy exposure;
Recommend hedge strategies to the GWP ERMC that address GWP’s plans to manage its energy exposure;
Oversee the development of procedures for Energy Marketers, Schedulers, and Real-time Traders as needed;
Support and assist in the preparation of reports listed in Section 6.1, Reporting Requirements; and
Serve on the GWP ERMC.
3.6 *:3$66,67$17*(1(5$/0$1$*(5
%86,1(666(59,&(6
The GWP Assistant General Manager or designee, as relates to Business Services, oversees the “back office,” reports directly to the GWP General Manager, and responsible for GWP’s marketing development and operations activities. The GWP Assistant General Manager (Business Services) shall:
Oversee the responsibilities of the GWP Utility Manager (Financial) and GWP Business Systems Support Manager;
Provide management oversight for the direction and coordination of customer service activities with other sections of the utility; Direct marketing and public information activities of the utility. Oversee the development, implementation, promotion, evaluation, and modification of GWP customer relations, marketing, demand-side management, utility conservation, renewable energy, and revenue enhancing programs across all customer segments;
Direct the activities of support service functions for the utility; Prepare written reports and correspondence, and recommend procedural changes to improve efficient operation of the section;
Prepare and monitor GWP budget and overall financial health of the utility; 803 of 839
G. Energy Risk Management Policy
Glendale Water & Power 2024 IRP G-15
Energy Risk Management Policy
Glendale Water & Power August 2022
11 Lead the utility wide change management effort with respect to smart grid and related innovation. Responsible for the development and implementation of strategic and technology work plans;
Direct personnel and activities in the development of distributed resources, dynamic rates, including time of use, critical peak, and real time pricing, demand response, smart appliance, consumer device, advanced storage, peak-shaving, new web based services, and other smart grid program options for empowering consumers;
Assure compliance with the Energy Risk Management Policy and related policies, as defined in Section 5; and
Serve on the GWP ERMC.
3.7 *:3,17(*5$7('5(6285&(63/$11,1*$'0,1,675$725
The GWP Integrated Resources Planning Administrator reports directly to the authority under section 3.5 and plans, directs, supervises, and reviews the development, identification, and administration of power resources; plans, directs, supervises and reviews the development, negotiation, monitoring, administration, and settlement of transactions related to power resource contracts; and plans, directs and supervises participation in regulatory, legal and project administration efforts. The GWP Integrated Resources Planning Administrator shall:
Direct activities related to the preparation of forecasts of energy requirements and peak demands;
Direct the development of analytical studies related to power supply economics, generation, forecasting, regulatory and legislative impacts; Direct the City's power supply projects including generation, transmission and marginal costing studies;
Direct the preparation of utility data to assist in negotiating power marketing agreements and power purchases;
Direct contract negotiations to fill power supply requirements and to resolve power supply issues;
Direct the preparation of reports for regulatory agencies; Direct the development and maintenance of forward wholesale market information systems;
Direct the development and implementation of forward strategies; Negotiate and administer joint power resource development projects, regional transmission and power generating projects;
Analyze proposed litigation settlements and negotiate the settlement of disputes;
Coordinate the legal review of proposed contractual arrangements; Evaluate and report performance and compliance of existing power contracts;
804 of 839
G. Energy Risk Management Policy
Glendale Water & Power 2024 IRP G-16
Energy Risk Management Policy
Glendale Water & Power August 2022
12 Responsible for the development of the annual budget and long-term power cost forecasts;
Assist in the development of overall policies, plans, and objectives; and Prepare comprehensive written and oral reports and presentation recommendations; and
Participate on the GWP ERMC.
3.8 *:3(1(5*<75$',1*0$1$*(5
The GWP Energy Trading Manager reports directly to the authority under section
3.5 and exercises technical, administrative, and management responsibility over staff performing energy trading. The GWP Energy Trading Manager shall:
Represent the “front office” in GWP’s energy risk management organization; The “front office” is responsible for energy trading, operations, portfolio optimization, load forecasting, transaction and scheduling, generating resource optimization, and hedging;
Assure daily compliance with the Energy Risk Management Policy and related policies, as defined in Section 5, and timely responses to issues arising from day-to-day operations;
Execute and manage energy transactions (purchases, sales, and hedges) in accordance with approved hedge strategies and within the requirements specified in the Trading Authority Delegation;
Understand the types of transactions individuals may engage in to manage the energy portfolio;
Adhere to the transaction approval process;
Actively acquire and analyze market intelligence and assist in developing hedge strategies;
Prepare transaction analyses and reports;
Communicate market intelligence within GWP’s risk management organization; and
Participate on the GWP ERMC.
805 of 839
G. Energy Risk Management Policy
Glendale Water & Power 2024 IRP G-17 Glendale Water & Power August 2022 13 Energy Risk Management Policy
3.9 *:332:(53/$11,1*0$1$*(5
The GWP Power Planning Manager reports directly to the authority under section
3.5 and supervises the analysis, forecasting and planning activities for the electric utility's integrated resources established by GWP management. The GWP Power Planning Manager represents the “front office” in GWP’s energy risk management organization. The GWP Power Planning Manager shall:
Evaluate resource needs to meet forecasted loads and load patterns and performs technical and economic analysis of resource options; Perform modeling, analysis, and forecasting of load patterns and resource utilization;
Interpret and evaluate economic analyses, planning data, and study results;
Assist in evaluating opportunities for power supply acquisition and power project participation;
Assist in negotiating contracts to fill power supply requirements and to resolve power supply issues;
Evaluate market data and opportunities for power supply acquisition and power project participation;
Prepare and supervise preparation of technical and administrative reports and recommendations including the annual long-range power supply plan (integrated resource plan) and reports to regulatory bodies; Develop and recommend policies and procedures to ensure that power planning/marketing activities comply with NERC/WECC requirements and contractual provisions;
Develop and recommend procedures to effectively carry out optimization of the City's resource, transmission, and load portfolio; Assist with development of the annual budget;
Prepare and supervise preparation of reports and graphic displays for use in presentation of study results and recommendations; and Participate on the GWP ERMC.
806 of 839
G. Energy Risk Management Policy
Glendale Water & Power 2024 IRP G-18 Glendale Water & Power August 2022 14 Energy Risk Management Policy
3.10 *:3(1(5*<5,6.0$1$*(5
GWP’s Independent Risk Management Function is led by the GWP Energy Risk Manager. The GWP Energy Risk Manager represents the “middle office” in GWP’s energy risk management organization. The responsibilities of the GWP Energy Risk Manager include ensuring reports covering GWP’s energy portfolio position and credit exposures are prepared and reporting compliance with energy risk management policies and procedures. The GWP Energy Risk Manager also leads the development and review of business processes and internal control improvements throughout the energy transaction lifecycle. The GWP Energy Risk Manager will provide risk assessment input to the hedge planning and transacting activity, but will maintain a strict separation of duties.
The GWP Energy Risk Manager will brief the GWP General Manager, as requested, regarding recent GWP energy risk management activities.
The GWP Energy Risk Manager will serve as facilitator of the GWP ERMC and reports directly to the GWP General Manager. In addition, the GWP Energy Risk Manager shall:
Perform responsibilities delegated by the GWP ERMC;
Serve, organize and conduct the GWP ERMC meetings;
Engage the EMRC in discussions regarding emerging risks, events and developments that could expose GWP to potential losses; Develop, recommend, and administer risk management processes and procedures, including best practice procedures;
Provide and administer energy risk management education/training to GWP management and staff;
Review energy risk management activities and risk controls, and recommend modifications of controls to meet changing business needs; Review adequacy and accuracy of reports, and report any deficiencies to the GWP ERMC. Recommend actions to address deficiencies; Assess energy risks to GWP in aggregate, by business unit, and by material business activity;
Ensure compliance, review, and recommend changes to the Energy Risk Management Policy and related policies, as defined in Section 5, and energy risk management procedures, as appropriate;
Monitor compliance of transactions with GWP’s Trading Authority Policy and Trading Authority Delegation and monitor GWP’s portfolio for compliance with GWP’s Hedge Policy;
Report to the GWP ERMC and GWP General Manager on GWP’s compliance with its energy risk policies and energy risk management in accordance with policies;
Manage credit exposure in compliance with the GWP Credit Policy; Report mark-to-market forward energy transactions for credit exposure purposes;
807 of 839
G. Energy Risk Management Policy
Glendale Water & Power 2024 IRP G-19
Energy Risk Management Policy
Glendale Water & Power August 2022
15 Review and evaluate proposed longer-term transactions to be executed by GWP and ensure adequate analysis has been performed with proper assessment and mitigation of any such risk consistent with energy risk management objectives, risk tolerance guidelines, and energy risk management policies, including the financial, legal, credit, regulatory, reliability, and operational impacts;
Ensure the responsibilities of the GWP ERMC, as outlined in the Policy, are fulfilled;
Provide advice regarding the effectiveness of tools used or evaluated to assist in energy risk management for measuring, monitoring, and reporting performance;
Validate the tools and data used throughout GWP to measure, monitor, and report risk;
Support periodic internal audits of GWP risk control policies, processes and procedures with CoG Internal Audit to ensure overall operational compliance;
Conduct periodic review and update of the GWP Risk Registry, including status of mitigation plans and risk prioritization, and ensure effective strategies are in place to mitigate the top energy risks; Review and advise the GWP ERMC and the GWP General Manager of risk exposures in the GWP Risk Registry;
Ensure Standard Operating Procedures and Allegro Business Process Documents for each of the functional areas that fall under the Policy umbrella are maintained and updated, as necessary;
Be responsible for the oversight and effectiveness of GWP’s energy risk management policies, procedures, and trading control environment; Review and recommend, to the GWP ERMC, changes to functional activities, as appropriate, to ensure proper segregation of duties; Provide a timely summary of GWP ERMC accomplishments for the past year and goals for the upcoming year to the GWP ERMC and GWP General Manager;
Lead and assist in the preparation of reports listed in Section 6.1, Reporting Requirements;
Participate, as required, on committees and working groups such as risk management, legislative, regulatory, and cybersecurity; and Report regularly to the GWP ERMC, the following information, at a minimum, but not limited to:
oPortfolio modeling risk measures (1-60 months);
oPower cost projections and confidence intervals;
oProduction output and operational concerns;
oCredit and contract risk exposures;
oHedging strategies;
oEnergy policy and procedural violations;
oRegulatory and reliability compliance;
oBusiness continuity;
808 of 839
G. Energy Risk Management Policy
Glendale Water & Power 2024 IRP G-20
Energy Risk Management Policy
Glendale Water & Power August 2022
16 oPhysical and cyber security in coordination with the City’s Information Systems Department;
oUpdates to the GWP Risk Registry; and
oOther Key Performance Indicators that support effective energy risk management
3.11 *:332:(5&2175$&760$1$*(5
The GWP Power Contracts Manager reports directly to the authority under section 3.5 and recommends, negotiates, and prepares the City's power resource contracts and agreements in accordance with the direction and goals established by GWP management. The GWP Power Contracts Manager represents the “middle office” in GWP’s energy risk management organization. The GWP Power Contracts Manager shall:
Actively participate in regulatory, legal, and project administration efforts. Identify and assist in the negotiation and evaluation of contracts, including resource purchases and sales, transmission, natural gas, transportation, renewables and emissions, settlement, interconnection, interchange, development, participation, operation, and agreements;
Monitor and support the GWP’s participation in utility industry’s federal, state, and local regulatory authority activities;
Review, evaluate, revise, and author contracts, regulatory filings, and legal filings related to the GWP's energy resource operations; Review and ensure the GWP is in compliance with contractual terms and is receiving similar compliance from contracting parties in accordance with prepared task lists, schedules and loss calculations, procedures, and guidelines for administering and evaluating all energy resource related agreements;
Evaluate existing and proposed contractual arrangements and recommend desirable modifications for the purpose of optimizing the GWP's benefits;
Analyze and recommend resource-operating strategies and assist in the creation of contractual guidelines for related resource functions; and Support strategies related to legal disputes.
Assign appropriate funding based on contract terms and budget; and Notify GWP Management if it is anticipated that there will be inadequate funds available in the budget to transact;
Adhere to confirmation process by confirming trades executed under enabling agreements;
Manage the counterparty approval, credit, and collateral management processes;
Develop and manage Power Management’s budget for bulk power, gas, transmission, transportation, environmental commodities, and related contractual services;
809 of 839
G. Energy Risk Management Policy
Glendale Water & Power 2024 IRP G-21
Energy Risk Management Policy
Glendale Water & Power August 2022
17 Oversee trade capture and validation activities including actualization of trades, etags, generation resource data, and review accuracy, completeness, and timeliness of data in the trading system; Monitor and manage Renewable Energy Credits as it relates to creation, transfer, and retirement for RPS Compliance;
Carbon Allowance allocations, offsets, and mandatory greenhouse gas emissions reporting and verification;
Assure compliance with the Energy Risk Management Policy and related policies, as defined in Section 5;
Serve as “Energy Risk Manager” back-up; and
Participate on the GWP ERMC.
3.12 *:387,/,7<),1$1&(0$1$*(5
The GWP Utility Manager reports directly to the authority under section 3.6 and manages the “back office” in GWP’s energy risk management organization.
The Back Office, as part as the GWP Finance, provides settlement services; documents the required accounting treatment of forward transactions; and provides the related valuation of these transactions to enable the preparation of invoices and reporting of forward transactions in GWP’s financial statements in accordance with prevailing accounting rules. The GWP Utility Manager shall:
Oversee and monitor the back office for transactional analysis and accuracy;
Develop and apply accounting policies to financial transactions; Oversee the settlement of transactions (verification, accounts payable/receivable process);
Manage the counterparty approval, credit, and collateral management processes;
Correctly classify and report transactions. (Certain transactions may differ in their reporting requirements, depending on whether they qualify as “existing assets, liabilities, and firm commitments” or “anticipated transactions” for hedge accounting. CoG Finance shall determine how transactions are classified for reporting purposes and ensure that hedges are accounted for in accordance with generally accepted accounting principles.);
Be responsible for Dodd-Frank compliance;
Provide appropriate funding. (CoG Finance shall maintain control procedures over electronic funds transfer for payments and collections. This is intended to ensure that cash payments are properly disbursed and authorized trades are independently confirmed and processed.); and Notify GWP Management and the Power Contracts Manager if GWP Finance anticipates there will be inadequate funds available in the budget to transact.
810 of 839
G. Energy Risk Management Policy
Glendale Water & Power 2024 IRP G-22
Energy Risk Management Policy
Glendale Water & Power August 2022
18 Supports CoG Finance in preparing the Comprehensive Annual Financial Report that complies with the accounting requirements promulgated by the Governmental Accounting Standards Board (GASB);
Participate, as required, on finance committees and working groups; Assure compliance with the Energy Risk Management Policy and related policies, as defined in Section 5; and
Participate on the GWP ERMC.
Under no circumstances will members of the GWP Finance be given the authority to enter into any energy transactions on behalf of the utility.
3.13 *:387,/,7<%86,1(666<67(06833257$'0,1,675$725
The GWP Business Systems Support Manager reports directly to the authority under section 3.6 and has the responsibility of managing, directing, and coordinating the planning and implementation of major utility technology projects.
GWP’s Business Systems Support Manager shall:
Manage, support, and maintain the Energy Trading and Risk Management (ETRM) applications, databases, backups, and redundancies; Conduct quarterly audits of ETRM users access and provide reporting to management as needed;
Maintain OATI security and certificate management;
Administer all aspects of IT security with firewall monitoring; Develops and maintains GWP cybersecurity training, procedures, and policies;
Participate, as required, on cybersecurity committees and working groups. Coordinate information technology activities with City’s Information Services;
Assure compliance with the Energy Risk Management Policy and related policies, as defined in Section 5; and
Participate on the GWP ERMC
3.14 &,7<2)*/(1'$/(),1$1&(
The Finance Department provides timely, accurate, clear and concise information to the City Council, City Manager, GWP General Manager, GWP ERMC, and various City Departments and is dedicated to managing the City’s resources in a fiscally conservative manner. City of Glendale’s Director of Finance/Information Technology shall:
Provide support and assistance on GWP financial and budgetary issues; Provide long range financial planning functions including revenue and operational expense projections;
811 of 839
G. Energy Risk Management Policy
Glendale Water & Power 2024 IRP G-23
Energy Risk Management Policy
Glendale Water & Power August 2022
19 Provide recommendations on operations effectiveness measures, and revenue strategies;
Review existing and proposed ordinances, statues, resolutions, and other documents;
Direct the City’s energy risk management functions including litigation, insurance, and external auditors;
Confer on financial policies and procedures;
Assure compliance with this Policy and related policies, as defined in Section 5; and
Serve on the GWP ERMC.
3.15 &,7<2)*/(1'$/(/(*$/
The City Attorney's Office is committed to providing professional, quality legal services that ultimately protect the interests of the City of Glendale, its departments, and the City Council. City of Glendale’s City Attorney shall:
Review the Policy and the related policies, as defined in Section 5, and recommend updates as appropriate in compliance with the City Charter and applicable law;
Negotiate master/enabling agreements with counter-parties as directed by the authority under section 3.5 and GWP Power Contracts Manager; Assess legal enforceability of contracts with applicable laws and regulations;
Assure compliance with the Energy Risk Management Policy and related policies, as defined in Section 5; and
Participate on the GWP ERMC.
3.16 &,7<2)*/(1'$/($8',7
The City of Glendale Internal Audit assists the City in improving operations by providing independent audits and consulting services designed to add value and promote transparency, accountability, efficiency and effectiveness. The City of Glendale’s Internal Audit Manager shall:
Verify proper segregation of external and internal reporting, energy risk management, accounting, treasury, and trading duties and maintenance of files;
Sample and review activities for compliance with related policies and procedures;
Document and report audit findings to GWP ERMC, including compliance with and discrepancies from this Policy and the related policies, as defined in Section 5, as well as any other irregularity which could expose GWP to financial or operational risk; and
812 of 839
G. Energy Risk Management Policy
Glendale Water & Power 2024 IRP G-24
Energy Risk Management Policy
Glendale Water & Power August 2022
20 Participate on the GWP ERMC.
3.17 &21)/,&72),17(5(67$1'&203/,$1&(
Potential conflict of interest by persons directly affected by this Policy is covered by State law and City of Glendale’s citywide Conflict of Interest Charter Code.
All City of Glendale employees who hold positions mentioned in this Policy or perform functions described herein shall not enter into, or direct others to enter into, any energy transactions or other related transactions other than on behalf of GWP, the City of Glendale, or its authorized agents.
6&23(2)%86,1(66$&7,9,7,(6*29(51('%<7+,6
32/,&<
The scope of this Policy is designed to address the management of the energy risks associated with GWP, as documented in GWP’s Risk Registry. The GWP Risk Registry is a comprehensive list of risks that affect GWP’s short-term business operations and long-term strategic planning and is maintained by the GWP Energy Risk Manager. The GWP Risk Registry is comprised of Tier1, Tier 2, and Tier 3 risks distinguished by business category and prioritized by impact and likelihood. GWP and CoG personnel have been identified as the owners of each risk and are responsible for developing strategies to mitigate each risk. The number of risks may vary dictated by business and market changes. The GWP Risk Registry reporting requirement is outlined in Section 6.1. 5(/$7('32/,&,(6$1'5(*,675<
Supporting related policies and registry are identified below. Responsibility for their approval, modification, oversight, and compliance shall be consistent with the organization and governance of this Policy (Section 3). *Denoted CoG City Council responsibility for final approval.
GWP Trading Authority Policy*
GWP Trading Sanctions Policy
GWP Credit Policy
GWP Hedge Policy
GWP Business Continuity Policy
GWP Cyber Security Policy
GWP Risk Registry
GWP Electric Cash Reserves Policy*
813 of 839
G. Energy Risk Management Policy
Glendale Water & Power 2024 IRP G-25
Energy Risk Management Policy
Glendale Water & Power August 2022
21 5(3257,1*
Reports required by this Policy communicate the operational, market, and credit risks assumed by GWP, and provide information to evaluate the portfolio performance and the effectiveness of the energy risk management program. The reports should be used as a basis for management discussions to determine future energy transactions and strategy.
6.1 5(3257,1*5(48,5(0(176
Management reporting will act as a formal means of communicating the performance of energy transactions and management decisions. On an ongoing basis, management and staff must also establish sufficient communications among parties with responsibilities relative to this Policy.
The following table identifies the reports that must be generated, their normal frequency, report access or distribution, and the originator of the report:
7DEOH±5HSRUWLQJ5HTXLUHPHQWV
5HSRUW 5HSRUW$FFHVV
1RUPDO
)UHTXHQF\ 2ULJLQDWRU
Load/Resource
Balance
GWP ERMC Members and
Participants
All Transaction Implementation
Staff
Monthly GWP Energy Risk
Manager
Trade Data Report GWP ERMC Members and
Participants
All Transaction Implementation
Staff
Monthly
(Updated
Daily)
GWP Energy Risk
Management Section
Mark-to-Market
Report
GWP ERMC Members and
Participants
All Transaction Implementation
Staff
Monthly
(Updated
Daily)
GWP Energy Risk
Management Section
Counterparty Credit
Exposure Report
GWP ERMC Members and
Participants
All Transaction Implementation
Staff
Monthly
(Updated
Daily)
GWP Energy Risk
Management Section
814 of 839
G. Energy Risk Management Policy
Glendale Water & Power 2024 IRP G-26
Energy Risk Management Policy
Glendale Water & Power August 2022
22 Risk Registry and
Risk Mitigation
Activities (1)
GWP ERMC Members and
Participants
All Transaction Implementation
Staff
T1- Monthly
T2- Quarterly
T3 - Annually
GWP Energy Risk
Manager
Portfolio Modeling
Report
GWP ERMC Members and
Participants
All Transaction Implementation
Staff
Monthly GWP Energy Risk
Management Section
(1)As required in Section 3.3, GWP General Manager Responsibilities, the GWP General Manager shall report to the City Manager, annually, on the risk profile of the energy portfolio and on the results of energy risk management activities.
32/,&<5(9,(:
Following approval of this Policy, the GWP ERMC shall periodically, no less than annually, review the Policy and the related policies, as defined in Section 5, and recommend updates as appropriate in coordination with the GWP General Manger. Examples of events prompting updates to this Policy and related policies and reviews are changes in regulatory requirements, significant changes in the resource portfolio, significant changes in variable energy prices of alternative resources, changes in regulations, and reliability concerns. 352&('85(6
Standard Operating Procedures (SOP) and Desk Procedures shall be developed for each functional area to provide specific operating criteria and parameters for day-to-day energy risk management activities as needed. The operating criteria and parameters shall be updated as frequently as appropriate to reflect changes in market conditions and staffing levels. All procedures shall be reviewed approved by management and monitored and reviewed by the GWP ERMC. 815 of 839
Glendale Water & Power 2024 IRP H-1
H. Utility Modernization Report
The GWP Utility Modernization Report 2020 begins by explaining the background and historic evolution that has led to the current situation that demands utility modernization, and commits GWP to embracing its transformation. Written by Stephen Zurn, GWP’s General Manager, the report outlines the modernization initiatives taken by Glendale’s Electric Division and Water Division. The report describes how GWP is transforming its operations and instituting programs in critical topic areas such as: § Solar solutions program § Renewable energy investments § Distribution system upgrades § Municipal street lighting conversions § Business system modernization and automation § In-home display and thermostat program § Electric vehicle infrastructure § Mobile source air pollution reduction partnership § Electric motorcycles for police § Fiber optic network § Voltage reduction program § Clean energy program § Commercial and residential demand response and thermostat program GWP not only understands the need for a resilient, reliable, and secure power grid to meet the ever demanding needs that the transformation in the energy industry demands, but is also taking steps to keep pace by modernizing its operations and engaging its customers in the process. 816 of 839
H. Utility Modernization Report
Glendale Water & Power 2024 IRP H-2
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817 of 839
H. Utility Modernization Report
Glendale Water & Power 2024 IRP H-3
2 !"#$%&'()*'+,%%,-.'/#0'1"".'02".3'3-',.4".3,5,6"'0-%#$',.03#%%#3,-.0'0,.4"'3/"' 2$-7$#+'1"7#.',.'8998:';<=',0'-."'->'3/"'%#03'?3,%,3,"0',.'3/"'$"7,-.'3/#3' 4-.3,.?"0'3-',.4".3,5,6"'3/"',.03#%%#3,-.'->'$-->3-2'0-%#$:'@0';<='%--A0',.3-' -B"$,.7'#'5,$3?#%'2-C"$'2%#.3'#.D'0-%#$'2$-7$#+'-23,-.'#0'2#$3'->',30'E%"#.' F."$7&'=$-7$#+0G',3'2$-2-0"0'3-'03-2'3/"'H-%#$'H-%?3,-.0'2$-7$#+'0-'3/#3' 4?03-+"$0'4#.'3#A"'#D5#.3#7"'->'#'+-$"'+-D"$.,6"D'#22$-#4/'3-'0-%#$' "."$7&',.5"03+".30:'
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H. Utility Modernization Report
Glendale Water & Power 2024 IRP H-5
4 5
!"#$%"#&'%%"()*+#,-&'./(0#-(#&-(1"%)/(0#$**#*/02).#/(#$(3#$%-'(3#)2"## 3-4()-4(#$%"$#$(3#-(#5$6-%#)2-%-'02,$%".#)2%-'02-')#)2"#&/)+#)-#789.:# !2"(#)2$)#/.#&-5;*")"3#4"#4/**#5-1"#)-#&-(1"%)#)2"#%"5$/(/(0#*/02).#/(## %"./3"()/$*#$%"$.:#<2"."#&-(1"%./-(.#4/**#.$1"#)2"#=/)+#-,#>*"(3$*"#-1"%## ?@@#A!B#-,#"("%0+#;"%#+"$%:
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820 of 839
H. Utility Modernization Report
Glendale Water & Power 2024 IRP H-6
4 5
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821 of 839
H. Utility Modernization Report
Glendale Water & Power 2024 IRP H-7
6 7
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822 of 839
H. Utility Modernization Report
Glendale Water & Power 2024 IRP H-8
6 7
!"#$"%&'(&)*++(,'&-./,01)-.2&.*340,)&(5&060/',-/&1.7&+6*28-.89:4,-7&& ;09-/60)<&=90&>$?@&A-66&/(.',-4*'0&*+&'(&BCD&(5&'90&/()'&(5&+*46-/6:&& 1//0))-460&"#$"&-.)'1661'-(.)&1.7&*+&'(&CED&(5&'90&'('16&"#$"&/()'&5(,&& +,-;1'0&1//0))&"#$"<&
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823 of 839
H. Utility Modernization Report
Glendale Water & Power 2024 IRP H-9
8 9
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824 of 839
H. Utility Modernization Report
Glendale Water & Power 2024 IRP H-10
8 9
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825 of 839
H. Utility Modernization Report
Glendale Water & Power 2024 IRP H-11
10 11
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826 of 839
H. Utility Modernization Report
Glendale Water & Power 2024 IRP H-12
10 11
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12#.,3'4$(-#)5,+(,2%)6)7.28)9:.,#4)
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827 of 839
H. Utility Modernization Report
Glendale Water & Power 2024 IRP H-13
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828 of 839
Glendale Water & Power 2024 IRP I-1
I. Energy Efficiency Program Results
Every year, California’s POUs collaborate to develop cost-effective energy efficiency programs and report those results to their customers and the CEC. The POUs publish these results in Energy Efficiency in California’s Public Power Sector. The 2023 report was the 17th edition. During fiscal year 2022, the POUs collectively expended $223 million on energy efficiency programs for their communities, including low-income customers, resulting in 362 GWh of net annual energy savings with 4,268 GWh of net lifecycle energy savings and reducing peak demand by 71 MW. Table 35 lists GWP’s energy efficiency savings for 2022. Gross Peak Savings (kW) Gross Annual Savings (kWh) Gross Lifecycle Energy Savings (kWh) Net Peak Savings (kW) Net Annual Energy Savings (kWh) Net Lifecycle Energy Savings (kWh) Net Lifecycle GHG Reductions (Tons) 1,510 11,316,344 64,239,265 1,504 11,281,064 63,746,054 19,524 Table 35. Energy Efficiency Program Results Table 36 lists GWP’s energy efficiency program costs, including the Program Administrator Cost and the Total Resource Cost. Total Utility Cost PAC TRC Utility ($/kWh) $3,162,930 $2.26 $1.37 $0.071 Table 36. Energy Efficiency Program Costs For more information, see Chapter 8. Energy Efficiency Programs and Initiatives. 829 of 839
I. Energy Efficiency Program Results
Glendale Water & Power 2024 IRP I-2
Table 37 lists GWP’s energy efficiency program results by end use for 2022.
Table 37. Energy Efficiency Program Results by End Use
EE in California’s Public Power Sector: 17th Edition — 2023 A-67
TABLE 1. GWP EE Program Results by End Use
Summary by End Use Resource Savings Summary Cost Test Results End Use Gross Peak
Savings (kW)
Gross Annual
Savings (kWh)
Gross Lifecycle
Energy Savings
(kWh)
Net Peak
Savings (kW)
Net Annual
Energy Savings
(kWh)
Net Lifecycle
Energy Savings
(kWh)
Net Lifecycle GHG
Reductions (Tons)
Total Utility
Cost PAC TRC Utility
($/kWh)
Appliance & Plug Loads 1 48,292 600,914 1 30,604 385,470 139 $46,119 0.87 0.84 0.163 Building Envelope 4 6,431 102,311 1 1,801 28,647 10 $3,750 1.43 0.93 0.191 HVAC - Cooling 1,055 1,142,666 16,281,759 1,053 1,138,006 16,208,886 5,225 $1,367,184 1.93 0.82 0.118 Lighting - Indoor 92 421,974 5,133,096 92 413,992 5,005,385 1,557 $85,858 7.67 2.08 0.023 Lighting - Outdoor 0 69,051 1,450,071 0 69,051 1,450,071 653 $16,308 10.65 10.65 0.017 Miscellaneous 358 9,627,130 40,662,314 358 9,627,130 40,662,314 11,938 $1,643,161 2.21 2.21 0.059 Service & Domestic Hot Water 0 800 8,800 0 480 5,280 2 $551 0.85 0.55 0.139 EE Subtotal 1,510 11,316,344 64,239,265 1,504 11,281,064 63,746,054 19,524 $3,162,930 2.26 1.37 0.071 EE and Low Income Subtotal 1,510 11,316,344 64,239,265 1,504 11,281,064 63,746,054 19,524 $3,162,930 2.26 1.37 0.071
All 0 4,062,000 8,124,000 0 4,062,000 8,124,000 1,878 $137,606 2.72 2.72 0.034 T&D Subtotal 0 4,062,000 8,124,000 0 4,062,000 8,124,000 1,878 $137,606 2.72 2.72 0.034 C&S, T&D and Electrification
Subtotal 0 4,062,000 8,124,000 0 4,062,000 8,124,000 1,878 $137,606 2.72 2.72 0.034
Utility Total 1,510 15,378,344 72,363,265 1,504 15,343,064 71,870,054 21,402 $3,300,536 2.28 1.40 0.068 830 of 839
I. Energy Efficiency Program Results
Glendale Water & Power 2024 IRP I-3
Table 38 lists GWP’s energy efficiency program results by sector for 2022.
Table 38. Energy Efficiency Program Results by Sector
EE in California’s Public Power Sector: 17th Edition — 2023 A-68
TABLE 2. GWP EE Program Results by Sector
Summary by Sector Resource Savings Summary Cost Test Results Sector Gross Peak
Savings (kW)
Gross Annual
Savings (kWh)
Gross Lifecycle
Energy Savings
(kWh)
Net Peak
Savings (kW)
Net Annual
Energy Savings
(kWh)
Net Lifecycle
Energy Savings
(kWh)
Net Lifecycle GHG
Reductions (Tons)
Total Utility
Cost PAC TRC Utility
($/kWh)
Commercial 460 2,750,418 33,199,428 460 2,750,418 33,199,428 10,243 $868,658 4.59 1.38 0.035 Other 777 69,051 1,450,071 777 69,051 1,450,071 653 $917,575 0.37 0.37 0.978 Residential 273 8,496,875 29,589,766 267 8,461,595 29,096,555 8,628 $1,376,697 2.05 1.99 0.073 EE Subtotal 1,510 11,316,344 64,239,265 1,504 11,281,064 63,746,054 19,524 $3,162,930 2.26 1.37 0.071 EE and Low Income Subtotal 1,510 11,316,344 64,239,265 1,504 11,281,064 63,746,054 19,524 $3,162,930 2.26 1.37 0.071
Residential 0 4,062,000 8,124,000 0 4,062,000 8,124,000 1,878 $137,606 2.72 2.72 0.034 T&D Subtotal 0 4,062,000 8,124,000 0 4,062,000 8,124,000 1,878 $137,606 2.72 2.72 0.034 C&S, T&D and Electrification
Subtotal 0 4,062,000 8,124,000 0 4,062,000 8,124,000 1,878 $137,606 2.72 2.72 0.034
Utility Total 1,510 15,378,344 72,363,265 1,504 15,343,064 71,870,054 21,402 $3,300,536 2.28 1.40 0.068 831 of 839
I. Energy Efficiency Program Results
Glendale Water & Power 2024 IRP I-4
Table 39 lists GWP’s energy efficiency program results by building type for 2022.
Table 39. Energy Efficiency Program Results by Building Type
EE in California’s Public Power Sector: 17th Edition — 2023 A-69
TABLE 3. GWP EE Program Results by Building Type
Summary by Building Type Resource Savings Summary Cost Test Results Building Type Gross Peak
Savings (kW)
Gross Annual
Savings (kWh)
Gross Lifecycle
Energy Savings
(kWh)
Net Peak
Savings (kW)
Net Annual
Energy Savings
(kWh)
Net Lifecycle
Energy Savings
(kWh)
Net Lifecycle GHG
Reductions (Tons)
Total Utility
Cost PAC TRC Utility
($/kWh)
All 996 1,496,004 17,146,554 996 1,494,579 17,130,881 5,518 $1,510,102 1.42 1.43 0.119 Office - Large 241 1,327,027 17,542,127 241 1,327,027 17,542,127 5,388 $279,986 7.79 0.95 0.022 Residential 268 8,452,518 29,031,568 265 8,433,956 28,743,475 8,504 $1,337,855 2.08 2.02 0.072 Residential - Single-Family 5 40,795 519,016 2 25,502 329,571 113 $34,987 1.08 1.10 0.146 EE Subtotal 1,510 11,316,344 64,239,265 1,504 11,281,064 63,746,054 19,524 $3,162,930 2.26 1.37 0.071 EE and Low Income Subtotal 1,510 11,316,344 64,239,265 1,504 11,281,064 63,746,054 19,524 $3,162,930 2.26 1.37 0.071
All 0 4,062,000 8,124,000 0 4,062,000 8,124,000 1,878 $137,606 2.72 2.72 0.034 T&D Subtotal 0 4,062,000 8,124,000 0 4,062,000 8,124,000 1,878 $137,606 2.72 2.72 0.034 C&S, T&D and Electrification
Subtotal 0 4,062,000 8,124,000 0 4,062,000 8,124,000 1,878 $137,606 2.72 2.72 0.034
Utility Total 1,510 15,378,344 72,363,265 1,504 15,343,064 71,870,054 21,402 $3,300,536 2.28 1.40 0.068 832 of 839
Glendale Water & Power 2024 IRP J-1
J. City Council Clean Energy Resolution
On August 16, 2022, the Glendale City Council unanimously approved “a resolution establishing goals for solar energy installations by Glendale Water & Power customers and clean energy targets, establishing a City Council subcommittee, and directing staff to take actions in furtherance thereof.” The resolution essentially states three goals for GWP to work toward attaining: § Future GWP investments in producing energy, to the maximum extent possible, be from “clean, renewable, or non-carbon-emitting resources excluding renewable biofuels not already permitted or approved”. The resolution further sets a target date for this goal as “no later than 2035”. § At least 10 percent of GWP customers adopt solar and energy storage systems by 2027. § Additional demand management measures be developed with a minimum total peak dispatchable and peak-load-reducing capacity of 100 MW. The resolution also authorized GWP to engage with a consultant to analyze the steps needed to attain these goals and to work toward attaining them. 833 of 839
J. City Council Clean Energy Resolution
Glendale Water & Power 2024 IRP J-2
834 of 839
J. City Council Clean Energy Resolution
Glendale Water & Power 2024 IRP J-3
835 of 839
J. City Council Clean Energy Resolution
Glendale Water & Power 2024 IRP J-4
836 of 839
J. City Council Clean Energy Resolution
Glendale Water & Power 2024 IRP J-5
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J. City Council Clean Energy Resolution
Glendale Water & Power 2024 IRP J-6
838 of 839
J. City Council Clean Energy Resolution
Glendale Water & Power 2024 IRP J-7
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