Optimization Of MPPT Control Algorithm On PV Generation System

In order to solve the pressure of environmental pollution and shortage of energy, the solar energy as the most environmentally friendly, the most convenient and sustainable new energy, has a huge development potential, concern. Photovoltaic power generation industry has also been rapid development, however, the high cost of photovoltaic systems and low conversion efficiency is a serious obstacle to the process of photovoltaic industry. How to improve the conversion efficiency of photovoltaic power generation system has become the focus of attention and research, Therefore, as an important means of improving energy efficiency, photovoltaic power generation maximum power point tracking technology came into being. Based on PV cell characteristic and all kinds of control algorithm of a lot of analysis and research, creative proposed will leapfrog particle swarm neural network algorithm is applied to the photovoltaic maximum power point tracking control and the use of intelligent algorithm strong self learning ability and nonlinear fitting ability and fault tolerance and other advantages, in combination with constant pressure control method, photovoltaic maximum power point tracking efficiency is greatly improved.According to the principle and characteristics of the photovoltaic cell, the battery model was built in MATLAB/SIMULINK, and the U-I and U-P characteristic curves of the battery were simulated and analyzed. Providing a foundation for modeling of photovoltaic control system.According to the characteristics of photovoltaic power generation system analysis of the MPPT control principle and process,. Analysis and select the suitable DC / DC boost circuit, then control algorithms and ideas of various classic methods, especially on the control period and step selection made detailed theoretical derivation. Respectively in MATLAB to build photovoltaic MPPT control system model, simulation analysis of various algorithms use occasions, and its advantages and disadvantages, based on based on shuffled frog leaping particle swarm neural network intelligent control algorithm.Then,introduced in detail of neural network and the leapfrog particle swarm algorithm principle and methods of optimizing, and in MATLAB write control algorithm, is built based on MPPT leapfrog particle swarm neural network control system model. The simulation results show that, this intelligent algorithm in dynamic response speed, steady state accuracy and anti-jamming ability etc. are superior to those of traditional control method, control effect is outstanding.