Research On Maximum Power Tracking Algorithm And System For Photovoltaic Power Generation

With the advancement of science and technology and the improvement of human living standards,traditional energy sources based on fossil raw materials have been unable to meet people’s ever-increasing living needs.Therefore,large-scale development and utilization of new energy sources are used to protect the environment on which humankind depends and realize energy.sustainable development.Solar energy is a renewable energy source and attracts attention due to its rich resources,clean and pollution-free advantages.Photovoltaic power generation is the main form of solar energy utilization.However,because the output characteristics of photovoltaic arrays are affected by the external light intensity and temperature,the working point cannot Stable operation at the maximum power point will reduce the conversion efficiency of the system and make it impossible to maximize the use of solar energy.Therefore,it is of practical significance to study the maximum power tracking algorithm of photovoltaic power generation system to improve the system conversion efficiency.This paper starts from the principle of solar photovoltaic power generation system and analyzes in detail the working principle,physical and mathematical models and output characteristics of photovoltaic cells.Based on this,the working principle of MPPT control is given.The principle and working flow of several commonly used MPPT methods,such as perturbation observation method,conductance increment method,constant voltage method,neural network method,etc are analyzed Disadvantages.The disturbance observation method does not require high accuracy of the sensor,and the tracking algorithm is relatively simple and easy to implement;however,the selected step length cannot simultaneously take into account the accuracy and speed.In addition,oscillations at both sides of the highest point of the power cause partial oscillations.When the power loss and the external environment change greatly,it is likely to cause some misjudgment.In order to make these traditional control methods improve their shortcomings on the premise of maintaining advantages,the tracking speed and control accuracy of the system can be improved.This paper proposes combining fuzzy logic control and adaptive transformation based on the traditional disturbance observation method.Step size,LMS-based adaptive variable step size and other intelligent algorithms,and using MATLAB/Simulink combined with photovoltaic cell simulation model to simulate the improved algorithm.At the same time,the simulation results of the traditional algorithm and the improved algorithm are analyzed and compared.Simulation results show that the improved algorithm proposed in this paper can improve the tracking control effect to some extent.Based on the theory and simulation analysis,this paper designs a photovoltaic power generation system controller based on STM32F103T8U6.Combining the characteristics of the improved algorithm and the performance requirements of the system,the hardware part mainly includes the STM32F103T8U6 minimum system,IGBT driver circuit,signal conditioning circuit and power supply circuit;using the KeiluVison3 software development environment,the software design part of the algorithm control program.