Adjusting to the new SOD framework can be complicated and confusing without tools to simplify the process. Ascend’s PowerSIMMTM Slice of Day solution provides the analytics to optimize RA SOD reporting and includes key features such as:
As LSEs analyze options to meet RA requirements, they need to model potential additions to existing portfolios to understand how it impacts their RA position in the SOD context. Figure 1 shows the RA position in a month-hour grid with and without energy storage in the model. Initially, there are shortfalls in late afternoon during summer months. The energy storage shifts the midday long positions to the evening hours when it is needed.
Diving deeper into the month of August, Figure 2 shows the detailed RA positions where solar capacity causes a long position in the midday hours that can be shifted with energy storage. The RA requirement peaks during the 18:00 hour when storage provides the necessary capacity to meet the requirement.
California’s new SOD framework adds reporting burdens to LSEs and creates a need for hourly long-term resource planning. PowerSIMM™ Slice of Day natively models the new economics of capacity by including the RA requirements within the modeling environment, enabling LSEs to plan resources effectively while mitigating costs and compliance risks.
In 2022, the California Public Utilities Commission (CPUC) reformed its RA accounting methodology to better account for the contributions of variable energy resources and duration limited resources. The CPUC transitioned to a month-hour '12x24 - Slice of Day' approach meant to reflect a more comprehensive view of grid reliability. The methodology employs:
The SOD framework requires LSEs to demonstrate that they have enough capacity to satisfy their gross load profile, including planning reserve margin, during all 24 hours on the California Independent System Operator’s (CAISO) 'worst day,' defined as the day of the month that contains the hour with the highest coincident peak load forecast in that month. Future iterations of the SOD may define the “worst day” differently.
SOD represents a major shift in the RA construct for CPUC regulated LSEs by moving from a monthly RA requirement based on ELCC accredited capacity values to an hourly requirement based on exceedance values. LSEs must adjust to the new filing requirements and understand how the changes affect planning decisions in long-term planning. SOD also impacts resource value – which can vary widely to different LSEs based on how it fits into the specific portfolio of any given LSE.
Though the SOD framework was conceived to produce a straightforward approach to accounting for renewable and storage contributions to RA, implementing SOD has revealed several issues for LSEs:
The value (and price) of RA for each month-hour slice will be a function of how short the system is from the target reserve quantity for that specific month-hour. The revenue that a resource receives in turn will reflect how much it improves grid reliability during these strained month-hours, like previous ELCC-derived results. When looking to forecast the value of RA, Ascend evolves capacity prices forward in line with forecasted energy revenues and cost trajectory for storage while also accounting for the spreading of RA value across more hours under SOD RA.
The exceedance methodology creates a month-hour matrix that determines RA contributions from solar and wind production based upon historical data. For example, a 70% exceedance value states a renewable resource can reasonably generate the quantity of power observed in 70% of historical time intervals for a given month-hour. For a solar resource that has a 70% exceedance value of 100 MW at 2pm, the data show at least 100 MW of generation in 70% of historical observations. Each resource’s value depends on its region-specific generation. For example:
In general, LSEs and other stakeholders have indicated that the exceedance methodology reflects the specifics of the location and the resource.
SOD has significantly reduced the RA value of standalone storage relative to previous accounting frameworks. In SOD, energy storage provides RA value by shifting excess RA to hours when the RA capacity is needed. Previously, LSEs could count four-hour duration standalone storage at the full nameplate value towards meeting their RA requirements. However, under the SOD framework, storage's RA contribution lies in its ability to shift RA value from hours with excess RA to shortfall hours. In this manner, the SOD framework ensures storage has charging resources to provide RA value.
For instance, under SOD:
Many LSEs procured energy storage as part of the Midterm Reliability Procurement Order. Under the SOD, these LSEs now find that they are oversubscribed on storage, leading them to focus on acquiring RA-generating resources such as wind, geothermal, gas, or solar.
In terms of battery storage optimization, the CPUC RA Showing Template offers limited capabilities. The current version of the template cannot optimize RA shifting with energy storage if the LSE has an hour with RA shortfall.
Thermal generation receives RA accreditation based on its maximum output in SOD. A current exception to this rule is gas peaker plants that fall under the Cost Allocation Mechanism (CAM). Per CPUC requirements, CAM peaker units have a nine-hour daily run limitation. Therefore, the RA Showing Template only allows CAM peakers to provide RA for up to nine hours but does not include tools to optimally determine the nine hours when the resource provides the most value in coordination with energy storage and other portfolio resources.
The new RA SOD requires that LSEs adjust to a new method of accounting for resource contribution to RA. Given the changes in how resources will be accredited, LSEs should integrate the RA SOD methodology in resource evaluation and planning decisions. PowerSIMM’s RA SOD module provides the necessary tools for the integration of RA SOD accounting with models for evaluation and planning.
Adjusting to the new SOD framework can be complicated and confusing without tools to simplify the process. Ascend’s PowerSIMMTM Slice of Day solution provides the analytics to optimize RA SOD reporting and includes key features such as:
As LSEs analyze options to meet RA requirements, they need to model potential additions to existing portfolios to understand how it impacts their RA position in the SOD context. Figure 1 shows the RA position in a month-hour grid with and without energy storage in the model. Initially, there are shortfalls in late afternoon during summer months. The energy storage shifts the midday long positions to the evening hours when it is needed.
Diving deeper into the month of August, Figure 2 shows the detailed RA positions where solar capacity causes a long position in the midday hours that can be shifted with energy storage. The RA requirement peaks during the 18:00 hour when storage provides the necessary capacity to meet the requirement.
California’s new SOD framework adds reporting burdens to LSEs and creates a need for hourly long-term resource planning. PowerSIMM™ Slice of Day natively models the new economics of capacity by including the RA requirements within the modeling environment, enabling LSEs to plan resources effectively while mitigating costs and compliance risks.
In 2022, the California Public Utilities Commission (CPUC) reformed its RA accounting methodology to better account for the contributions of variable energy resources and duration limited resources. The CPUC transitioned to a month-hour '12x24 - Slice of Day' approach meant to reflect a more comprehensive view of grid reliability. The methodology employs:
The SOD framework requires LSEs to demonstrate that they have enough capacity to satisfy their gross load profile, including planning reserve margin, during all 24 hours on the California Independent System Operator’s (CAISO) 'worst day,' defined as the day of the month that contains the hour with the highest coincident peak load forecast in that month. Future iterations of the SOD may define the “worst day” differently.
SOD represents a major shift in the RA construct for CPUC regulated LSEs by moving from a monthly RA requirement based on ELCC accredited capacity values to an hourly requirement based on exceedance values. LSEs must adjust to the new filing requirements and understand how the changes affect planning decisions in long-term planning. SOD also impacts resource value – which can vary widely to different LSEs based on how it fits into the specific portfolio of any given LSE.
Though the SOD framework was conceived to produce a straightforward approach to accounting for renewable and storage contributions to RA, implementing SOD has revealed several issues for LSEs:
The value (and price) of RA for each month-hour slice will be a function of how short the system is from the target reserve quantity for that specific month-hour. The revenue that a resource receives in turn will reflect how much it improves grid reliability during these strained month-hours, like previous ELCC-derived results. When looking to forecast the value of RA, Ascend evolves capacity prices forward in line with forecasted energy revenues and cost trajectory for storage while also accounting for the spreading of RA value across more hours under SOD RA.
The exceedance methodology creates a month-hour matrix that determines RA contributions from solar and wind production based upon historical data. For example, a 70% exceedance value states a renewable resource can reasonably generate the quantity of power observed in 70% of historical time intervals for a given month-hour. For a solar resource that has a 70% exceedance value of 100 MW at 2pm, the data show at least 100 MW of generation in 70% of historical observations. Each resource’s value depends on its region-specific generation. For example:
In general, LSEs and other stakeholders have indicated that the exceedance methodology reflects the specifics of the location and the resource.
SOD has significantly reduced the RA value of standalone storage relative to previous accounting frameworks. In SOD, energy storage provides RA value by shifting excess RA to hours when the RA capacity is needed. Previously, LSEs could count four-hour duration standalone storage at the full nameplate value towards meeting their RA requirements. However, under the SOD framework, storage's RA contribution lies in its ability to shift RA value from hours with excess RA to shortfall hours. In this manner, the SOD framework ensures storage has charging resources to provide RA value.
For instance, under SOD:
Many LSEs procured energy storage as part of the Midterm Reliability Procurement Order. Under the SOD, these LSEs now find that they are oversubscribed on storage, leading them to focus on acquiring RA-generating resources such as wind, geothermal, gas, or solar.
In terms of battery storage optimization, the CPUC RA Showing Template offers limited capabilities. The current version of the template cannot optimize RA shifting with energy storage if the LSE has an hour with RA shortfall.
Thermal generation receives RA accreditation based on its maximum output in SOD. A current exception to this rule is gas peaker plants that fall under the Cost Allocation Mechanism (CAM). Per CPUC requirements, CAM peaker units have a nine-hour daily run limitation. Therefore, the RA Showing Template only allows CAM peakers to provide RA for up to nine hours but does not include tools to optimally determine the nine hours when the resource provides the most value in coordination with energy storage and other portfolio resources.
The new RA SOD requires that LSEs adjust to a new method of accounting for resource contribution to RA. Given the changes in how resources will be accredited, LSEs should integrate the RA SOD methodology in resource evaluation and planning decisions. PowerSIMM’s RA SOD module provides the necessary tools for the integration of RA SOD accounting with models for evaluation and planning.
Ascend Analytics is the leader provider of market intelligence and analytics solutions for the energy transition. The company's offerings enable decision makers in power development and supply procurement to maximize the value of planning, operating, and managing risk for renewable, storage, and other assets. From real-time to 30-year horizons, their forecasts and insights are at the foundation of over $50 billion in project financing assessments. Ascend provides energy market stakeholders with the clarity and confidence to successfully navigate the rapidly shifting energy landscape.