Research on Electricity Price Forecasting Model in the Electricity Spot Market Based on Multi-source Data Fusion

To address the challenges of electricity price fluctuations influenced by multiple factors and the limitations of single-model predictions in the electricity spot market, this study constructs a multi-source data fusion analysis framework. By incorporating key factors into feature dimensions and integrating three algorithms—LSTM, Random Forest, and XGBoost—into a time series model, we develop electricity price prediction models. Comparative experiments are conducted to validate the performance of each model.