A new PV generation power prediction model based on GA-BP neural network with artificial classification of history day

Abstract

PV power generation has such shortcomings as volatility, intermittency and so on. When it connects to the power grid, it will adversely affect the power system. So it is important to predict the power of PV power generation system accurately. The more similar the weather condition is, the more similar the generation of photovoltaic power generation system is. This paper proposes a new PV Generation Power Prediction model Based on GA-BP Neural Network with Artificial Classification of History Day. Firstly, we classify historical weather data artificially. Then, we establish different PV Generation Power Prediction model for each weather type using BP neural network and genetic algorithm (GA-BP neural network). At last, the power of the forecast day is predicted by the GA-BP neural network which is for the weather type of the forecast day.