IISE PG&E Energy Analytics Challenge 2024: Forecasting Day-Ahead Electricity Prices.

AbstractElectricity price forecasting is one of the cornerstones of modern-day power system operation. Over the last two decades, the field has seen many methodological advancements. On one end, traditional statistical methods remain widely prevalent in today’s energy industry, as they have proven consistently to “stand the test of time.” On the other end, emerging predictive techniques (e.g., machine and deep learning) have demonstrated immense potential. Yet, due to limited benchmarking studies, the magnitude of improvement realized by such emerging methods relative to their statistical counterparts is not entirely clear. In response, two technical divisions of the Institute of Industrial & Systems Engineers (IISE) partnered with the Pacific Gas and Electric Company (PG&E)—one of the largest utility companies in the United States—in order to organize an electricity price forecasting challenge in 2024. Using three years of pricing signals and exogenous information from California’s electricity market, the competition challenged teams of researchers and practitioners to design their own models and submit forecasts for day-ahead electricity prices, which were independently evaluated against a test set that has been reserved from all teams. This paper introduces the challenge, as well as an overview of the methods used by the top-performing contestants. A distilled summary of the key insights and lessons learned by the challenge organizers is then presented, together with their relevance to the topic of electricity price forecasting. This is then followed by recommendations for future similarly focused competitions. To accelerate the research and development on this important topic, all data used in the challenge have been made publicly available by the challenge organizers. [ABSTRACT FROM AUTHOR]