Spatial-temporal characteristics analysis of solar irradiance forecast errors in Europe and North America
Mingliang Bai,
Peng Yao,
Haiyu Dong,
Zuliang Fang,
Weixin Jin,
Xusheng Yang,,
Jinfu Liu and
Daren Yu
Energy, 2024, vol. 297, issue C
Abstract:
Accurate photovoltaic (PV) power forecast is crucial to power systems. Solar irradiance forecast is the fundamentals of PV power forecast. Current researches merely focus on improving the forecast accuracy. There hasn't been comprehensive study on the spatial-temporal characteristics of solar irradiance forecast errors. Thus, this paper analyzed the error characteristics of solar irradiance forecast provided by European Centre for Medium-Range Weather Forecasts (ECMWF), one of the most accurate numerical weather prediction (NWP) products. ECMWF's forecasts were compared with ERA5 solar irradiance reanalysis data to reveal the error distribution characteristics. Four-year (2017–2020) data from the geographical region bounded by 63°N, −126°W, 21°S, and 36°E (covering most parts of Europe and North America) were studied. Experiments show that solar irradiance forecast errors peak at noon of the local time. Furthermore, correlations between solar irradiance forecast errors and other weather variables were also revealed. Experiments show that solar irradiance forecast errors have negative correlation with low cloud cover forecast errors and positive correlation with air temperature forecast errors. The possible reasons for the correlation relationship were also analyzed in detail. This paper systematically reveals the spatial-temporal characteristics of solar irradiance forecast errors and provides a useful guideline for solar PV system operation.
Keywords: Photovoltaic power forecast; Solar energy; Solar irradiance forecast; Spatial-temporal characteristics; Uncertainty analysis (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:297:y:2024:i:c:s0360544224009605
DOI: 10.1016/j.energy.2024.131187
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