Research on Spot Electricity Price Forecasting for Proxy Purchasing Considering Supply and Demand Side Uncertainties

SGCC-Henan MSC, 450052 Zhengzhou, China

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Abstract

With the development of China's electricity spot market and proxy purchasing, sharp price fluctuations due to supply-demand uncertainties pose key risks. To improve forecasting accuracy for purchasing decisions, this study examines spot price prediction under such uncertainties. It analyzes market clearing mechanisms and identifies supply-side uncertainties (renewable output, conventional generation costs) and demand-side uncertainties (load elasticity, economic cycles). A multi-dimensional factor system covering meteorological, economic, systemic, and market aspects is established. Integrating the time-series advantages of LSTM with the uncertainty-handling capability of robust optimization, a hybrid forecasting model balancing accuracy and adaptability is proposed. Empirical tests using Shandong's spot market data show the model's MSE, MAE, and MAPE decrease to 286.32, 14.25, and 1.73%, respectively, outperforming traditional LSTM and random forest models. The model effectively addresses forecasting challenges under uncertainties and supports cost control and risk management in proxy purchasing.