Solar energy production: Short-term forecasting and risk management

Cédric Join; Michel Fliess; Cyril Voyant; Frédéric Chaxel

doi:10.1016/j.ifacol.2016.07.790

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

Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

4 LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau]

5 SPE - Sciences pour l'environnement

6 Centre hospitalier d'Ajaccio

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

Document type :

Conference papers

Domain :

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]

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Submitted on : Saturday, September 3, 2016 - 10:08:23 AM
Last modification on : Wednesday, March 27, 2019 - 4:41:27 PM
Long-term archiving on: Monday, December 5, 2016 - 9:16:42 AM

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