Day-Ahead Energy Price Forecasting with Machine Learning: Role of Endogenous Predictors

Forecasting, Journal Year: 2025, Volume and Issue: 7(2), P. 18 - 18

Published: April 9, 2025

Accurate Day-Ahead Energy Price (DAEP) forecasting is essential for optimizing energy market operations. This study introduces a machine learning framework to predict the DAEP with 24 h lead time, leveraging historical data and forecasts available at prediction time. Hourly from California Independent System Operator (January 2017 July 2023) were integrated exogenous engineered endogenous features. A custom rolling window cross-validation, validation blocks sliding daily across 2372 folds, evaluates an Extreme Gradient Boosting (XGBoost) model’s performance under diverse conditions, achieving median mean absolute error of 6.26 USD/MWh root squared 8.27 USD/MWh, variability reflecting volatility. The feature importance analysis using Shapley additive explanations highlighted dominance features in driving time relatively stable conditions. Forecasting runtime 10 AM on prior day was used assess model uncertainty. involved training random forest, support vector regression, XGBoost, feed forward neural network models, followed by stacking voting ensembles. results indicate need ensemble evaluation beyond static train–test split ensure practical utility varied dynamics. Finally, operationalizing forecast bidding decisions real-time prices presented discussed.

Language: Английский

Game-theoretic evolution in renewable energy systems: Advancing sustainable energy management and decision optimization in decentralized power markets

Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 217, P. 115776 - 115776

Published: April 23, 2025

Language: Английский

Leveraging Evolutionary Game Theory for Cleaner Production: Strategic Insights for Sustainable Energy Markets, Electric Vehicles, and Carbon Trading

Journal of Cleaner Production, Journal Year: 2025, Volume and Issue: unknown, P. 145682 - 145682

Published: May 1, 2025

Language: Английский