Electricity Forecasting

Electricity forecasting aims to accurately predict future electricity demand and generation, crucial for efficient grid management and renewable energy integration. Current research emphasizes improving forecasting accuracy and interpretability through advanced machine learning techniques, including graph neural networks that leverage spatial relationships in decentralized grids, and interactive generalized additive models that incorporate expert knowledge. These efforts are driven by the need for robust and reliable forecasting in the face of increasing complexity and uncertainty within power systems, ultimately impacting grid stability, resource allocation, and market efficiency.