Energy Forecasting
This page gathers projects and articles focusing on mathematical modeling and machine learning applications for forecasting energy systems, including probabilistic electricity price forecasting, load forecasting, and renewable energy generation.
Probabilistic Electricity Price Forecasting (Part 3)
Bootstrapped residuals and split conformal prediction for DK1 day-ahead prices, adapted from skforecast's guides and evaluated with the same walk-forward cross-validation as Part 2, including a head-to-head comparison against QR and QRF.
Probabilistic Electricity Price Forecasting (Part 2)
Implementing Quantile Regression and Quantile Regression Forest for DK1 day-ahead prices, evaluated with walk-forward cross-validation: real code, real results, and what changes once a single train/test split becomes four folds spread across different seasons.
Probabilistic Electricity Price Forecasting (Part 1)
An introduction to probabilistic electricity price forecasting: the European and Danish power markets, quantiles and prediction intervals, Quantile Regression and Quantile Regression Forest, and evaluation metrics such as Pinball Loss, CRPS, and the PIT histogram.