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DOE OSTI · 1855782

Probabilistic Cloud Optimized Day-Ahead Forecasting System Based on WRF-Solar (Final Report)

Sengupta, Manajit·Jimenez, Pedro A.·Kim, Ju-Hye·Yang, Jaemo·Xie, Yu
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Abstract

The most persistent challenge in both intraday and day-ahead solar forecasting is to get numerical weather prediction models to produce the right type of clouds with the right frequency at the right time and place. Another challenge is to understand and communicate the forecast uncertainty. The objective of this project was to develop an optimized ensemble-based solar irradiance forecasting system that will (1) demonstrably improve the current state-of-the-art solar forecasts from the deterministic Weather Research and Forecasting-Solar (WRF-Solar) model and (2) provide probabilistic forecasts for grid operations. This probabilistic solar forecasting system, referred to as the WRF-Solar Ensemble Prediction System (WRF-Solar EPS), aims to significantly enhance both the intraday and the day-ahead solar forecasting capability for grid operations. This technical report summarizes the work performed in the past 3 years through a collaboration between the National Renewable Energy Laboratory and the National Center for Atmospheric Research as part of the U.S. Department of Energy's Solar Forecasting 2 program that aims to improve the accuracy of solar energy forecasts and enable increased deployment of solar energy on the electric grid.

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14 SOLAR ENERGY24 POWER TRANSMISSION AND DISTRIBUTIONday-ahead forecastensemble predictionNSRDBWRF-Solar EPS

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Sengupta, Manajit, Jimenez, Pedro A., Kim, Ju-Hye, Yang, Jaemo, Xie, Yu. 2022-03-14. Probabilistic Cloud Optimized Day-Ahead Forecasting System Based on WRF-Solar (Final Report). https://doi.org/10.2172/1855782

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