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Forecasting the energy produced by a windmill on a yearly basis
Authors:Alain Bensoussan  Pierre Rapha?l Bertrand  Alexandre Brouste
Affiliation:1. School of Management, University of Texas, Dallas, TX, USA
2. The Hong-Kong Polytechnic University, Hung Hom, Kowloon, Hong-Kong
3. Department of Financial Engineering, Ajou University, Suwon, Gyeonggi-do, South Korea
4. INRIA Saclay, 91893, Orsay Cedex, France
5. Laboratoire de Mathématiques, UMR 6620 CNRS and Université Clermont-Ferrand, Aubière Cedex, France
6. Laboratoire Manceau de Mathématiques, Université du Maine, Le Mans Cedex, France
Abstract:The objective of this article is to study as extensively as possible the uncertainties affecting the annual energy produced by a windmill. In the literature, the general approach is to estimate the mean annual energy from a transformation of a Weibull distribution law. Then the issue is reduced to estimating the coefficients of this distribution. This is obtained by classical statistical methods. Therefore, the uncertainties are mostly limited to those resulting from the statistical procedures. But in fact, the real uncertainty of the random variable which represents the annual energy cannot been reduced to the uncertainty on its mean and to the uncertainties induced from the estimation procedure. We propose here a model, which takes advantage of the fact that the annual energy production is the sum of many random variables representing the 10?min energy production during the year. Under some assumptions, we make use of the central limit theorem and show that an intrinsic uncertainties of wind power, usually not considered, carries an important risk. We also explain an observation coming from practice that the forecasted annual production is always overestimated, which creates a risk of reducing the profitability of the operation.
Keywords:
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