Research On Maximum Power Point Tracking Control Strategy Of Photovoltaic Power Generation System

The depletion of traditional energy and the environmental pollution problems caused by using traditional energy seriously restrict the sustainable development of human society.It is imperative to change the old energy structure and develop clean renewable energy.Solar energy is internationally recognized as the most ideal alternative energy,with great predominance of development.Photovoltaic power generation is one of the major methods for acquiring solar energy and it has become a research focus in the world.In order to improve the utilization of solar energy,the maximum power point tracking control method is usually used to ensure the maximum output of the photovoltaic power generation system.Therefore,this thesis focuses on the maximum power point tracking control strategy of the photovoltaic power generation system.On the basis of consulting a large number of domestic and foreign references,this thesis analyzes and compares several classical maximum power point tracking control strategies.After that,perturbation and observation method is chosen as the basic algorithm to solve the maximum power point tracking control problem and it has been carried on deep analysis and research.According to the tracking principle of perturbation and observation method,we can see that there is a contradiction between tracking speed and tracking accuracy of the system.Under the control of traditional perturbation and observation method,the system has significant oscillation near the maximum power point.And the system is prone to misjudgment when the environment changes drastically.In order to solve these problems,this paper proposes a self-optimizing perturbation and observation method based on hysteresis comparison by analyzing the output characteristics of photovoltaic cells.Aiming at solving the contradiction of the tracking speed and tracking precision caused by fixed step-size in traditional perturbation and observation method.Based on the similarity between the slope rule of U-P output characteristic curve and the demand rule of system disturbance step size,the proposed algorithm utilizes the self-optimizing method to determine the size of the perturbation step-size in real time.This method ensures that the tracking speed and the tracking accuracy of the control system meet the requirements,while the oscillation at the maximum power point can be avoided effectively.Aiming at the problem of the misjudgment of system,the hysteresis comparison is utilized to determine the perturbation direction in the proposed algorithm,which can effectively avoid the misjudgment of the system and reduce the unnecessary power loss.Finally,this thesis utilizes Matlab/Simulink software to build a simulation model of photovoltaic power generation system based on maximum power point tracking control with DC-DC circuit as the main circuit.By comparing and analyzing the simulation output results of several control methods,the experiments verify the speediness,accuracy and superiority of the control system based on the self-optimizing perturbation and observation method based on hysteresis comparison.