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• W4328101718 endingPage "162979" @default.
• W4328101718 startingPage "162979" @default.
• W4328101718 abstract "Development of solar energy is one of the key solutions towards carbon neutrality in China. The output of solar energy is dependent on weather conditions and shows distinct spatiotemporal characteristics. Previous studies have explored the photovoltaic (PV) power potential in China but with single models and low-resolution radiation data. Here, we estimated the PV power potential in China for 2016-2019 using an ensemble of 11 PV models based on hourly solar radiation at the resolution of 5 km retrieved by the Himawari-8 geostationary satellite. On the national scale, the ensemble method revealed an annual average PV power potential of 242.79 kWh m-2 with the maximum in the west (especially the Tibetan Plateau) and the minimum in the southeast (especially the Sichuan Basin). The multi-model approach shows inter-model spreads of 6 %-7 % distributed uniformly in China, suggesting a robust spatial pattern predicted by these models. The seasonal variation in general shows the largest PV power generation in summer months except for Tibetan Plateau, where the peak value appears in spring because the high cloud coverage dampens the regional solar radiation in summer. On the national scale, the deseasonalized PV power potential shows a high correlation with cloud coverage (R2 = 0.71, p < 0.01) but a low correlation with aerosol optical depth (R2 = 0.08, p < 0.05). Sensitivity experiments show that national PV power potential increases by 0.55 % per 1 W m-2 increase of radiation and 0.79 % per 1 m s-1 increase of wind speed, but decreases by 0.46 % per 1 °C increase of air temperature. These sensitivities provide a solid foundation for the future projection of PV power potential in China under climate change." @default.
• W4328101718 created "2023-03-22" @default.
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• W4328101718 date "2023-06-01" @default.
• W4328101718 modified "2023-10-06" @default.
• W4328101718 title "Assessment of solar energy potential in China using an ensemble of photovoltaic power models" @default.
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• W4328101718 doi "https://doi.org/10.1016/j.scitotenv.2023.162979" @default.
• W4328101718 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36948316" @default.
• W4328101718 hasPublicationYear "2023" @default.
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