基于样本双重筛选的光伏发电功率预测

PV power generation has characteristics such as volatility,intermittence,but the more similar the weather condition is,the more similar the generation law of PV power generation system is. Firstly,the power singular value was removed to complete the preliminary screening through setting up the relations between irradiance and power. Secondly, the correlation coefficient between power and various meteorological factors such as irradiance,temperature and cloudiness,etc. was calculated,and then the meteorological factors with bigger correlation coefficient were collected to evaluate the similarity between historical days and the forecast day. The most similar historical days from the predicted day was extracted as training samples to complete the secondary screening. At last,the power of PV power generation was predicted using BP neural network and genetic algorithm. The results show that the method has high prediction accuracy.