Based On Ga Bpnn Photovoltaic Maximum Power Point Tracking Control Research

In order to alleviate the increasingly serious energy crisis and the worsening ecological environment caused by traditional energy consumption, At present, The application of new energy resources is increasingly becoming the focus of the research and development of all countries in the world. Solar energy have green, safety, renewable, and many other advantages, thus received the attention of scientists, Convert solar energy into electric energy, is an important use of solar energy.But at present, the photovoltaic power generation of low efficiency, high cost factors have seriously restricted the promotion and use of the photovoltaic power generation system.In order to improve the conversion efficiency, Maximum power point tracking is an important method.This paper introduced intelligent control into the maximum power point tracking,by using the neural networks’ fitting and prediction ability and genetic algorithm optimization outstanding characteristics,combined with constant pressure control method is very good way to realize the maximum power point tracking of the photovoltaic power generation system.The main work of this paper are as follows:(1) A brief introduction of the status quo and development trend of photovoltaic power generation,also introduced the principle and the equivalent circuit of the photovoltaic cells.In the Matlab/Simulink environment set up photovoltaic cell model,through the simulation get U-I U-P dynamic change curve,Analysis what are the change of output power of the photovoltaic cells with the change of external conditions.(2) First expounded photovoltaic MPPT principle, then simulation analysis of its realization way,more detailed analysis of the classical algorithm and to establish the simulation model.Second combined with front battery model,set up complete pv MPPT simulation model.Then simulation analysis the advantages and disadvantages of the classical algorithm,put forward a new control method, based on genetic algorithm to optimize the BP neural network of photovoltaic maximum power point tracking control.(3) Briefly describes the BP neural network and genetic algorithm principle, proposes use of BP neural network prediction photovoltaic maximum power point voltage,in order to make the error more ideal, we use genetic algorithm to optimize the BP neural network,then combined with constant pressure control principle,put forward a new control algorithm, improved constant pressure pv MPPT control based on GA-BPNN algorithm.(4) Modular processing the BP neural network, this network is a good optimization with genetic algorithm, then combined with photovoltaic MPPT simulation model,build a improvement photovoltaic MPPT simulation model based on GA-BPNN algorithm and simulation analysis.The results show that this control algorithm can fast accurate for maximum power point tracking accurately, stability is better, precision is higher.Combined with Labview software,build Labview display interface, collecting different weather conditions, and the results is verified again no matter in what the weather conditions this maximum power point tracking method has very good effect.