An Interpretable Multi-target Regression Method for Hierarchical Load Forecasting

Abstract

Accurate energy load forecasting provides good decision support for energy management. Current energy load forecasts focus more on forecast accuracy without exploring the similar patterns and correlations of energy load demand between regions. Our proposed interpretable hybrid multi-target regression approach provides more explanatory abilities for each region's energy load prediction. After combining the correlation between forecast targets and hierarchical forecast information, our model achieves a high forecast accuracy that the mean square error is reduced by three quarters compared to LightGBM's independent prediction for each region on the GEFCom 2017 dataset.