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

Pierre Pinson, Henrik Aalborg Nielsen, Jan Kloppenborg Møller, Henrik Madsen, Georges Kariniotakis

    Research output: Contribution to journalJournal articleResearchpeer-review


    Predictions of wind power production for horizons up to 48-72 hour 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 future 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 nonparametric 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.
    Original languageEnglish
    JournalWind Energy
    Issue number6
    Pages (from-to)497-587
    Publication statusPublished - 2007


    Dive into the research topics of 'Non-parametric probabilistic forecasts of wind power: required properties and evaluation'. Together they form a unique fingerprint.

    Cite this