Yan Jin1,*, Dingmei Wang2, Ruiping Zhang1, Haiying Dong1
Energy Engineering, Vol.119, No.5, pp. 1923-1940, 2022, DOI:10.32604/ee.2022.018750
Abstract Aiming at the low spatial resolution of meteorological data output from a numerical model in photovoltaic power prediction, a geographically weighted statistical downscaling method considers the influence factors such as normalized vegetation index (NDVI), digital elevation model (DEM), slope direction, longitude and latitude is proposed. This method is based on the correlation between meteorological data and NDVI, DEM, slope direction, latitude and longitude, and introduces DEM and local Moran index to improve the regression model, and obtains 100 * 100 m high-resolution meteorological spatial distribution data. Finally, combining the measured data of the study area and the established EOF iterative downscaling… More >
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