Probabilistic Seasonal and Decadal Forecasts for the Electricity System Using Linear Inverse Modeling
Providing a sustained, quality-controlled dataset for hourly data and illumination of climate-related temperature trends
In 2019, the research team improved and optimized forecasting algorithms; processed and analyzed hourly weather data for trends and relevant quantities; reviewed peer-reviewed atmospheric science literature to identify additional determinants of predictability in seasonal temperature; produced and uploaded datasets for use by the CEC's Demand Analysis Office, the Cal-Adapt development team, and other energy sector stakeholders; and participated in a final meeting in which technical results were shared with the Demand Forecast Office. Finally, the research team submitted a final report for publication, began work on a peer-reviewed publication, and participated in knowledge transfer to support a workshop where hourly data will be discussed by IOUs, CEC, CPUC, and other energy sector stakeholders to illuminate how best to provide access to the data on Cal-Adapt.
This project made three primary climate data advancements: (1) developed a curated, quality-controlled repository of hourly weather observations at 39 locations across California for the period 1973-2019, (2) provided recommendations for how to best use the data and supporting documentation, and (3) offered guidance on hosting a periodically updated database of quality-controlled, hourly temperature observations on Cal-Adapt. Data products utilized in this work supported development of a statewide data repository, providing energy sector stakeholders with regular ultra-high resolution data products that are needed to help California meet its renewable energy and climate goals. Additionally, the project assessed and quantified the extent to which the state of the Pacific Ocean can be used as a basis for generating predictions of temperature in California. The project then outlined an approach for making such predictions operational. The data and analyses produced and performed in this project meet the stated needs of investor-owned utilities, publicly-owned utilities, and state agencies to provide insight into the effects of sub-daily weather on the electrical system.
Improved weather data has the potential to allow for reduced cost of electricity if utilities can leverage information provided to improve supply and electricity acquisition purchase decisions. Additionally, access to a stable, q
This work provides a stable quality-controlled record curated for California’s energy sector. Providing this information to energy system stakeholders through Cal-Adapt will foster a more stable energy system for ratepayers, by a
Key Project Members
The Regents of the University of California, San Diego