Solar energy production: Short-term forecasting and risk management

Cédric Join (1, 2, 3) , Michel Fliess (4, 2) , Cyril Voyant (5, 6) , Frédéric Chaxel (1)

1 CRAN - Centre de Recherche en Automatique de Nancy
2 AL.I.E.N. - ALgèbre pour Identification & Estimation Numériques
3 NON-A - Non-Asymptotic estimation for online systems
4 LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau]
5 SPE - Sciences pour l'environnement
6 Centre hospitalier d'Ajaccio

Electricity production via solar energy is tackled via short-term forecasts and risk management. Our main tool is a new setting on time series. It allows the definition of "confidence bands" where the Gaussian assumption, which is not satisfied by our concrete data, may be abandoned. Those bands are quite convenient and easily implementable. Numerous computer simulations are presented.

Keywords: confidence bands; time series; intelligent knowledge-based systems; forecasts; persistence; solar energy; volatility; risk; normality tests

Domains: Environmental Sciences; Environmental Engineering; Computer Science [cs]; Computational Engineering, Finance, and Science [cs.CE]; Computer Science [cs]; Machine Learning [cs.LG]; Statistics [stat]; Machine Learning [stat.ML]; Quantitative Finance [q-fin]; Risk Management [q-fin.RM]; Computer Science [cs]; Systems and Control [cs.SY]; Engineering Sciences [physics]; Automatic; Mathematics [math]; Optimization and Control [math.OC]

Cédric Join, Michel Fliess, Cyril Voyant, Frédéric Chaxel. Solar energy production: Short-term forecasting and risk management. 8th IFAC Conference on Manufacturing Modelling, Management & Control, MIM 2016, Jun 2016, Troyes, France. ⟨10.1016/j.ifacol.2016.07.790⟩. ⟨hal-01272152v3⟩