Photovoltaic power station generation power prediction method

Abstract

The invention discloses a photovoltaic power station generation power prediction method comprising the steps that six meteorological characteristics are daily extracted by using the historical meteorological data of a photovoltaic power station so that a meteorological characteristic library is established; the daily characteristic data in the meteorological characteristic library are clustered through a KFCM algorithm so as to realize weather type classification, and class marking is performed on the daily power data and the meteorological data; an SVR sub-model is established for each classof power data and meteorological data according to the class mark; the weather type of the target day is identified by using the SVM through the target day weather characteristics provided by numerical weather prediction and the corresponding SVR sub-model is selected; an ARIMA model is established by using the real-time monitoring data of the target day, and real-time prediction of the irradiation intensity and the temperature can be realized by using the rolling prediction model; and the prediction values of the irradiation intensity and the temperature are inputted to the selected SVR sub-model so that the photovoltaic power station power prediction result can be obtained. The photovoltaic power station generation power prediction accuracy can be enhanced.

Description

technical field [0001] The invention relates to a method for predicting the generated power of a photovoltaic power station, which belongs to the technical field of electric power system automation. Background technique [0002] Photovoltaic power generation, as one of the main technical means of solar energy utilization, has developed rapidly at home and abroad in recent years. By the end of 2015, the cumulative global photovoltaic installed capacity reached 227GW. The accumulative installed capacity of photovoltaic power generation in China has reached 43.18GW, of which the photovoltaic power station is 37.12GW, becoming the country with the largest installed capacity of photovoltaic power generation in the world. At the same time, China's new installed capacity in 2015 was 15.13GW, which is also one of the fastest growing countries in the world. The large-scale development and application of photovoltaic power plants have brought serious impacts on the stability of the ...

AI Technical Summary

Problems solved by technology

[0004] There are two main defects in the current photovoltaic power prediction algorithm. First, the accuracy of photovoltaic power prediction cannot be guaranteed. Relatively obvious volatility, and different weather conditions, the degree of volatility is not the same, the randomness of fluctuations seriously affects the accuracy of photovoltaic power forecasting; second, the time scale of forecasting is long, and it is difficult to achieve real-time forecasting

Images