1. Comparing global and regional downscaled NWP models for irradiance and photovoltaic power forecasting: ECMWF versus AROME.
- Author
-
Mayer, Martin János, Yang, Dazhi, and Szintai, Balázs
- Subjects
- *
NUMERICAL weather forecasting , *FORECASTING , *INDEPENDENT system operators , *PREDICTION models , *ELECTRIC power distribution grids , *ANALYSIS of variance - 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. • Global ECMWF outperforms regional AROME for global horizontal irradiance forecasting. • The advantage of ECMWF is reduced if photovoltaic power forecasting is concerned. • Both numerical weather prediction models have the same accuracy for regional forecasting. • Photovoltaic power forecast errors are the highest in winter. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF