Day-Ahead Electricity Price Forecasting Using a Multivariate Group Lasso Method
The CING-LEAR model is a multivariate statistical method designed to forecast day-ahead electricity prices by accounting for complex cross-hour feature group effects. It uses a Group Lasso formulation to jointly select relevant features across all hourly forecasts, leading to improved point and probabilistic accuracy compared to existing methods.