The purpose of this solicitation is to fund research that improves the accuracy and operational value of tools used to forecast Behind-the-Meter (BtM) resources. These improvements will enable grid operators and electricity market participants to more effectively plan their generation reserves, capacity, and real-time operations, supporting a more reliable, efficient, cleaner, and cost-effective energy system for California ratepayers.
California’s grid operators rely on electricity demand forecasting models to accurately predict systemwide and local electricity needs. These forecasts are essential for ensuring grid reliability and operational efficiency, and the California Independent System Operator (CAISO) uses them to inform market mechanisms, schedule generation reserves, and finetune real-time dispatch and ancillary services. Load serving entities (LSEs) use forecasts to determine procurement needs in wholesale markets while investor-owned utilities (IOUs) use them to maintain power quality and service reliability. Market participants also depend on accurate forecasts to optimize operations and ensure the availability of low-cost resources.
Traditional forecasting methods primarily rely on historical trends and real-time weather data. However, the growing adoption of distributed energy resources (DERs) such as solar photovoltaic (PV) systems, battery energy storage systems (BESS), and electric vehicles (EVs) has introduced new challenges. Many of these DERs are located behind the customer meter and are not directly visible to grid operators. These BtM resources greatly impact the net load and reduce the accuracy of existing forecasting methods, a challenge often referred to as ”Masked Load.
According the the CEC's Q&A document, while the maximum available funding is $3 million and the minimum request is $1 million (with the required 20% match), only one award will be made under this solicitation. The selected project must comprehensively address all the project focus areas outlined in the solicitation. The final award amount will be based on the funding requested by the highest-scoring application that meets all the requirements.
Inscríbase 
