Research On Photovoltaic Power Generation System And Its MPPT Control Strategy

The problem of environmental pollution caused by the continuous depletion of traditional energy and the consumption of primary energy is more and more prominent,which will undoubtedly accelerate the development and utilization of new energy.Photovoltaic power generation system has become one of the hot issues in the field of new energy sources in recent years because of its safety,reliability and economy.However,the output power of PV array is not only related to its own factors,but also affected by the external factors such as illumination intensity,ambient temperature and load.Therefore,it is necessary to maintain the maximum output power of the PV array,which will directly affect the efficiency of the whole PV system.In this paper,the independent photovoltaic power generation system is chosen as the research object,in order to make the PV array can work at the maximum power point when the external environment changes,the following work has been done.Firstly,the working principle of the photovoltaic cell is analyzed,the equivalent circuit of the photovoltaic cell is obtained,and the mathematical model of the photovoltaic array is established and the model is simplified.In order to study the influence of illumination intensity and temperature on the output characteristics of photovoltaic array,a photovoltaic array simulation model has been based on M function,the simulation results show that the output characteristics of PV array are strongly nonlinear.Secondly,after analyzing several common MPPT algorithms such as constant voltage method,perturbation and observation method and conductance increment method in detail,their advantages and disadvantages are pointed out.After expounding the principle of MPPT realized by Boost impedance transformation circuit,the parameter design method of the Boost is given,MPPT model is established based on the Boost circuit,the simulation results show that the feasibility of Boost circuit for photovoltaic array MPPT,and the impedance matching problem is pointed out.This paper selects two typical algorithm that is called perturbation and observation method and conductance increment method to do simulation experiments.From the simulation results,we can know that they can quickly and accurately track the maximum power point when the external environment changes,comparing with the former,the performance of the latter is better than that of the former,but they still cannot take into account both the tracking speed and the steady-state accuracy in the setting of disturbance step.Aiming at that,the incremental conductance method has been improved in this paper,but the practice has proved that the traditional control methods still exist problems.Thirdly,this paper presents a fuzzy control method based on duty cycle perturbation,which takes the duty cycle step value as the unique control quantity,so that the controller structure is simplified,and the cost is saved.According to the amplitude of power change,the control strategy adjusts the duty cycle step value automatically.And the reason of adopting fuzzy control has been explained.The detailed design process of fuzzy self-optimization controller is given,by simulation,both in the dynamic response time or in the steady-state error,the fuzzy control algorithm is better than the traditional control method.Finally,considering the convenience of the realization of the system and the cost of implementation,in this paper,the single chip microcomputer AT89S55 produced by Atmel company is selected as controller of the MPPT control system,and based on AT89S55,the hardware circuit design and software program design of the control system for MPPT are given,combined with the specific electrical parameters of the PV array,we have done three groups of MPPT experimental.The experimental results show that comparing with the incremental conductance method,the tracking time of the system is reduced by 89.47%,and comparing with the perturbation observation method,the steady-state error of the system is reduced by 66.67%.The experimental results show again that the fuzzy control algorithm has better steady-state performance,better dynamic performance and stronger robustness.