Prediction Effect Assessment of Solar PV Power Generation
Based on the same period meteorological data and the solar PV power output data from December 01, 2010 to March 16, 2011(the station is located at 30°N and 114°E nearby) issued by the PV power station in HUST, the relationship between the PV electricity generation and meteorological factors is established. The PV electricity generation is forecasted by using linear regression method, principle prediction method and neural networks. The test results indicate that all the relative coefficient of the solar PV power prediction and the actual power output passed the reliability of 0. 001 significant inspections with the above mentioned methods; these methods are valued for prediction electricity generation; linear regression method is the best prediction method.
solar energyphotovoltaic power generationpower predictioneffect evaluation
NETL
NSTL
万方数据
维普
