Rearch On Intelligent Control For Maximum Power Point Tracking Of Photovoltaic Generation System Of The Highway

In recent years,the highway construction is developing rapidly in China,and mileage of highway is increasing fastly.A lot of highway projects along the places which have difficulties in power supply.Then how to control the energy consumption effectively and use the renewable energy rationally have become a research hotspot in highway construction.With the development of photovoltaic technology,people begin to apply it to the construction of highway engineering.The photovoltaic technology is widely used in power supply system of the mechanical and electrical equipment along the highway,as well as the power supply system of the highway tunnel lighting.The maximum power point tracking(MPPT)which is one of the key technology in photovoltaic generation system has played an extremely important role in improving the overall efficiency of the system.Therefore,in this article,for the purpose of optimizing the efficiency of photovoltaic generation system,based on the research line of the control technology of MPPT,a thorough theoretical and simulation experimental research is launched.This article briefly describes the application development of the photovoltaic technology as well as the research situation of MPPT technology in China and abroad.A model of photovoltaic cells is established by using the software Matlab and the simulation research on output characteristics of photovoltaic cells are carried out.The influences of different temperature and solar irradiance on the maximum output power of photovoltaic cells were also analyzed.In this article,the principles of frequently-used perturb and observe method and incremental conductance method are analyzed in detail,and a simulation model of MPPT is established.Meanwhile,it focuses on the working principles of several intelligent control methods which used frequently,such as fuzzy control,genetic algorithm and neural network.Aiming at the problems that quantification factor,scaling factor tune difficulty and poor adaptability of the controller exist in using traditional fuzzy control for maximum power point tracking of photovoltaic generation system,an intelligent integrated control method is proposed.The method uses improved genetic algorithm to obtain the initial value of the quantification factor and scaling factor.Then,in order to overcome the defects of poor adaptability of traditional fuzzy controller and the degradative performance for MPPT of photovoltaic,which caused by fixed parameters' value,the strategy adds a two stage fuzzy parameter self-adjuster,two stage fuzzy inference method is adopted to adjust these parameters online.Finally in order to accelerate the speed of parameter adjustment,the second fuzzy inference rules are memorized by neural network.Therefore,it can make full use of the neural network's massively parallel processing ability,adjusting the traditional fuzzy controller's quantification factor and scaling factor online quickly and dynamically.The characteristics of several DC-DC conversion circuit which used frequently are analyzed briefly.By comparing and analyzing the advantages and disadvantages of these circuits,we choose the Boost conversion circuit in this article.The simulation models for maximum power point tracking of the photovoltaic generation system which based on incremental conductance method,traditional fuzzy control method and intelligent integrated control method are established by the software Matlab/Simulink.The comparative simulation researches of the three kinds of maximum power point tracking algorithm which under standard condition,dynamic illumination and dynamic temperature are carried out.The simulation results show that the maximum power value which tracked by the proposed method is the highest.And the method has fast response and good steady-state performance,too.The results also verified the superiority and effectiveness of the method.