Improving Solar & Load Forecasts: Reducing the Operational Uncertainty Behind the Duck Chart
Improvement of net-load forecasting to reduce scheduling errors for the California grid.
The project incorporated several forecast improvements by advancing methods for determining BTM system specifications and shading based on measured production inputs, integrating irradiance measurements to improve aerosol optical depth and cloud albedo aspects, and by incorporating near real-time metered PV generation data to fine-tune fleet forecasts of both grid-connected and BTM PV solar. Researchers evaluated three alternative model approaches for extending the CAISO load forecast framework and present the alternative load forecast frameworks for incorporating BTM solar PV forecasts. The study showed that improvements in solar and net load forecasting can provide positive financial impacts in the scheduling and procurement of electricity in the wholesale electric market within the State. The potential savings would have been on the order of $9 million just in the covered period.
This project aimed to reduce the operational uncertainty in both PV and net load forecasts by producing high accuracy forecasts and linking them to net load forecasts at finer time intervals. This increased accuracy in estimation and incorporation within net load forecasts will enable better integration of intermittent PV generation in California and lead to substantial savings in the associated wholesale energy market costs. The results of this agreement contribute to reduced operational uncertainty behind the Duck Chart by producing high accuracy solar generation forecasts for utilities and the CAISO, and linking these generation forecasts to methods for forecasting net loads at higher temporal resolution. This increased fidelity and connection to net load forecasts will provide critical insights to better manage the rapidly evolving grid in California.
Improved net load forecasts reduce the cost of grid regulation required to cover increasing load forecast errors. By reducing the percentage error by just 0.1 percent, the California ISO and California ratepayers can save more th
Reduced requirements for regulation services and spinning reserves will help reduce GHG emissions by an estimated 2.7 million tons per year through reduced use of natural gas fired peaker plants.
The project increases system reliability by significantly increasing the accuracy of solar PV forecasts and the associated net load forecasts. This integration of state-of-the-art solar forecasts into net-load forecasts further e
Key Project Members
Clean Power Research
Clean Power Research
Itron, Inc., dba IBS