Short-term photovoltaic power generation prediction method considering correlation degree of weather and meteorological factors
A technology of meteorological factors and photovoltaic power generation, applied in forecasting, neural learning methods, calculations, etc., can solve the problem of low accuracy in historical day selection
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[0076] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings.
[0077] Such as figure 1 and figure 2 As shown, the present invention discloses a short-term photovoltaic power generation forecast that takes into account the degree of correlation between weather and meteorological factors, which includes the following steps:
[0078] S1. Divide weather types into clear sky, cloudy weather, haze weather, and rainy weather, and meteorological factors into solar radiation intensity, temperature, wind speed, air relative humidity, and atmospheric aerosol index, standardize the data, and remove them by iForest algorithm bad data;
[0079] S2. Find the Pearson correlation coefficient between the photovoltaic power generation power and each meteorological factor under different weather types, and normalize the Pears...
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