The hybrid renewable energy forecasting and trading competition 2024
该竞赛要求参与者对英国3.6GW风光组合发电量进行日前预测和交易，分析了预测算法和交易策略的表现，并公开数据供后续研究。
The Hybrid Energy Forecasting and Trading Competition challenged participants to forecast and trade electricity generation from a 3.6 GW portfolio of wind and solar farms in Great Britain for three months in 2024. The competition mimicked operational practice, with participants required to submit genuine forecasts and market bids for the day ahead on a daily basis. Prizes were awarded for forecasting performance measured by the pinball score, trading performance measured by total revenue, and combined performance based on rank in the other two tracks. Here, we present an analysis of the participants’ performance and the lessons learned from the competition. The forecasting track reaffirmed the competitiveness of popular gradient boosted tree algorithms for day-ahead wind and solar power forecasting, though other methods also yielded strong results, with performance in all cases highly dependent on implementation. The trading track offers insight into the relationship between forecast skill and value, with trading strategy and underlying forecasts influencing performance. All competition data, including power production, weather forecasts, electricity market data, and participants’ submissions, are shared for further analysis and benchmarking.