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Comparing global and regional downscaled NWP models for irradiance and photovoltaic power forecasting: ECMWF versus AROME

  • Martin János Mayer*
  • , Dazhi Yang
  • , Balázs Szintai
  • *Corresponding author for this work
  • Budapest University of Technology and Economics
  • School of Electrical Engineering and Automation, Harbin Institute of Technology
  • Hungarian Meteorological Service

Research output: Contribution to journalArticlepeer-review

Abstract

Inspecting the literature, much effort has been placed on the verification of irradiance forecasts from numerical weather prediction (NWP) models, as such forecasts are thought to have profound implications on the photovoltaic (PV) power forecasts, which in turn affects grid operators' confidence in integrating such power into the electricity grid. However, perhaps due to the proprietary nature of PV plants and lack of access to state-of-the-art NWP model output, only few have had the chance to conduct head-to-head comparisons of global mesoscale and regional downscaled NWP models, in terms of how their irradiance forecast inaccuracies propagate to PV power forecasts. In this regard, this work presents such a study, in which irradiance and PV power forecasts from the European Centre for Medium-Range Weather Forecasts' High-Resolution (HRES) and Météo-France's Application of Research to Operations at Mesoscale (AROME) models are thoroughly verified against the ground-based measurements from 32 research-grade radiometry stations and 94 actual PV plants in Hungary. A wide range of techniques and case studies concerning verification is herein considered, including variance ratio analysis, Murphy–Winkler decomposition, point-versus-areal verification, and seasonal verification. Despite that the results are too numerous to be summarized in a few sentences, the overarching observation from the verification exercise is that the performance of irradiance forecasts can only be used to infer that of PV power forecasts to a certain extent, which contrasts the conventional wisdom.

Original languageEnglish
Article number121958
JournalApplied Energy
Volume352
DOIs
StatePublished - 15 Dec 2023
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • AROME
  • ECMWF
  • Numerical weather prediction
  • Photovoltaic power
  • Solar irradiance
  • Verification

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