2025/05/06 by Marie Bruguet, Arthur Thomas, Ronan Le Saout · 1 voice
Energy · Engineering · #Building Energy and Comfort Optimization #Energy Load and Power Forecasting #Energy, Environment, and Transportation Policies
paper · doi:10.1177/01956574251330845
openalex publication_date 2025/05/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/22
This paper addresses the challenge of adjusting energy consumption data for weather variations by introducing a novel General Weather Indicator (GWI). The GWI combines multiple weather variables, including temperature, wind, sunlight, rain, and cloudiness, using a novel econometric approach that applies K-means for threshold identification and LASSO for variable selection. Through an empirical analysis of sectoral electricity and natural gas consumption in France, we demonstrate that the GWI outperforms the standard HDD approach by addressing three main concerns: the lack of statistical criteria for defining the base temperature, the reliance solely on temperature as the weather variable, and the assumption of a constant base temperature over time and space. Based on these results, we propose an analysis of the sectoral functional form and an estimation of weather elasticities for energy demand in France at both the monthly and daily levels. JEL Classification: C32, E61, P28, Q47