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Verification of solar irradiance probabilistic forecasts

  • Philippe Lauret
  • , Mathieu David
  • , Pierre Pinson
    • Université de La Réunion

    Research output: Contribution to journalJournal articleResearchpeer-review

    227 Downloads (Orbit)

    Abstract

    We propose a framework for evaluating the quality of solar irradiance probabilistic forecasts. The verification framework is based on visual diagnostic tools and a set of scoring rules mostly originating from the weather forecast verification community. Two types of probabilistic forecasts are used as a basis to illustrate the application of these verification approaches. The first one consists in ensemble forecasts commonly provided by national or international meteorological centres. The second one originates from statistical methods and produces a set of discrete quantile forecasts, the nominal proportions of which span the unit interval. These probabilistic forecasts are evaluated for two selected sites that experience very different climatic conditions. The first site is located in the continental US while the second one is situated on La Réunion Island. Although visual diagnostic tools can help identify deficiencies in generated forecasts, it is recommended that a set of numerical scores be used to assess the quality of probabilistic forecasts. In particular, the Continuous Ranked Probability Score (CRPS) seems to have all the features needed to evaluate a probabilistic forecasting system and, as such, may become a standard for verifying solar irradiance probabilistic forecasts and by extension probabilistic forecasts of solar power generation.
    Original languageEnglish
    JournalSolar Energy
    Volume194
    Pages (from-to)254-271
    ISSN0038-092X
    DOIs
    Publication statusPublished - 2019

    Keywords

    • Probabilistic solar forecasting
    • Evaluation framework
    • Diagnostic tools
    • Scoring rules
    • CRPS
    • Ignorance Score

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