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Non-parametric probabilistic forecasts of wind power: Required properties and evaluation

Abstract : Predictions of wind power production for horizons up to 48-72 h ahead comprise a highly valuable input to the methods for the daily management or trading of wind generation. Today, users of wind power predictions are not only provided with point predictions, which are estimates of the conditional expectation of the wind generation for each look-ahead time, but also with uncertainty estimates given by probabilistic forecasts. In order to avoid assumptions on the shape of predictive distributions, these probabilistic predictions are produced from non-parametric methods, and then take the form of a single or a set of quantile forecasts. The required and desirable properties of such probabilistic forecasts are defined and a framework for their evaluation is proposed. This framework is applied for evaluating the quality of two statistical methods producing full predictive distributions from point predictions of wind power. These distributions are defined by a number of quantile forecasts with nominal proportions spanning the unit interval. The relevance and interest of the introduced evaluation framework are discussed.
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Submitted on : Monday, October 11, 2010 - 4:47:47 PM
Last modification on : Friday, August 5, 2022 - 12:36:01 PM

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Pierre Pinson, Henrik Aa. Nielsen, Jan K. Moller, Henrik Madsen, Georges Kariniotakis. Non-parametric probabilistic forecasts of wind power: Required properties and evaluation. Wind Energy, Wiley, 2007, 10 (6), pp.497-516. ⟨10.1002/we.230⟩. ⟨hal-00525361⟩



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