Short-Term Temperature Forecasting on a Several Hours Horizon

Prédiction de température à court-terme pour horizon de plusieurs heures

Louis Desportes (1) , Pierre Andry (1) , Inbar Fijalkow (1) , Jérôme David (2)

1 ETIS - UMR 8051 - Equipes Traitement de l'Information et Systèmes
2 Zent

Outside temperature is an important quantity in building control. It enables improvement in inhabitant energy consumption forecast or heating requirement prediction. However most previous works on outside temperature forecasting require either a lot of computation or a lot of different sensors. In this paper we try to forecast outside temperature at a multiple hour horizon knowing only the last 24 hours of temperature and computed clear-sky irradiance up to the prediction horizon. We propose the use different neural networks to predict directly at each hour of the horizon instead of using forecast of one hour to predict the next. We show that the most precise one is using one dimensional convolutions, and that the error is distributed across the year. The biggest error factor we found being unknown cloudiness at the beginning of the day. Our findings suggest that the precision improvement seen is not due to trend accuracy improvement but only due to an improvement in precision.

Domaines: Informatique [cs]; Apprentissage [cs.LG]; Traitement du signal et de l'image [eess.SP]

Louis Desportes, Pierre Andry, Inbar Fijalkow, Jérôme David. Short-Term Temperature Forecasting on a Several Hours Horizon. ICANN 2019, Sep 2019, Munich, Germany. ⟨10.1007/978-3-030-30490-4_42⟩. ⟨hal-02280784⟩