Analysis of WRF-solar in the estimation of global horizontal irradiation in Amapá, northern Brazil

Global horizontal irradiance (GHI) was simulated using version 4.3.1 of the WRF-Solar model over the state of Amapá in the northern region of Brazil. The performance of the Fast All-sky Model for Solar Applications (FARMS) algorithm, called WsolarAPf, was evaluated. The algorithm proposed by the Bas...

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Veröffentlicht in:Renewable energy 2024-11, Vol.235, p.121361, Article 121361
Hauptverfasser: Amorim, Ana Cleide Bezerra, de Almeida Dantas, Vanessa, dos Reis, Jean Souza, de Assis Bose, Nicolas, Emiliavaca, Samira de Azevedo Santos, Cruz Bezerra, Luciano André, de Matos, Maria de Fátima Alves, de Mello Nobre, Mariana Torres Correia, Oliveira, Leonardo de Lima, de Medeiros, Antônio Marcos
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Sprache:eng
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Zusammenfassung:Global horizontal irradiance (GHI) was simulated using version 4.3.1 of the WRF-Solar model over the state of Amapá in the northern region of Brazil. The performance of the Fast All-sky Model for Solar Applications (FARMS) algorithm, called WsolarAPf, was evaluated. The algorithm proposed by the Baseline Surface Radiation Network was used to treat hourly data from the automatic meteorological station of the National Institute of Meteorology in the city of Macapá-AP. Two cumulus parameterizations were needed to represent the rainy and less rainy periods. The modeling used input data from ERA5 reanalysis. Using cluster analysis, it was possible to estimate the typical meteorological year representative for a large area. The use of the FARMS algorithm reduced the relative RMSE of the GHI during winter (JJA) and austral spring (SON), from 26 % to 16 % in austral winter and from 17 % to 12 % in austral spring. The average daily maximum of GHI occurs at 13:00 local time during all seasons, and WRF-Solar showed it at 13:00 and 14:00 in the rainy season and 12:00 and 13:00 in the less rainy season. The suggestion to explore the development of an optimal combination of the two model predictions can be implemented using FARMS.
ISSN:0960-1481
DOI:10.1016/j.renene.2024.121361