Research On Output Characteristics Of PV Array And Maximum Power Point Tracking Algorithm

Electricity plays an important role in human life and is the main driving force for the development of science and technology,social and economic leaps.However,the traditional fossil energy power generation method is not sustainable and will also pollute the environment.Therefore,countries around the world have begun to develop new energy sources such as solar power generation technology.In view of the characteristics that the output power of photovoltaic cells is affected by environmental factors,scholars have proposed the maximum power point tracking(MPPT)technology of photovoltaic arrays to ensure the maximum power output of photovoltaic cells.For the photovoltaic array modeling research,this paper first obtains a four-parameter engineering model based on the physical model of the photovoltaic cell through engineering calculations,and builds the model through Simulink software for simulation analysis.According to the experimental results,the correctness of the model is verified.Photovoltaic cells exhibit the characteristics of a single peak under constant environmental conditions.The influence of different light intensity and ambient temperature on the output characteristics of photovoltaic cells is analyzed.Then a simulation model of the SP structure photovoltaic array was built,the cause of the hot spot effect and the role of the bypass diode were analyzed,and the simulation experiment under partial shading environment was performed on the Simulink platform,and the multi-peak curve of the photovoltaic array was summarized Laws,explored the influence of different shade distributions on the output power of photovoltaic arrays.For the research of photovoltaic maximum power point tracking control algorithm,this article first demonstrates the feasibility of achieving maximum power point tracking control by adjusting the duty cycle of the DC/DC converter,and then specifically analyzes the constant voltage method,the disturbance observation method and the optimization principle of the three algorithms of the conductance increment method.Aiming at the defect that the maximum power point tracking control of the disturbance observation method is easy to fail under partial shading,this paper designs the gray wolf algorithm-disturbance observation method(GWO-P&O)maximum power point tracking coordinated control method.The simulation results show that when applied to multi-peak optimization,GWO-P&O can find the maximum power more effectively than the disturbance observation method.Although GWO-P&O can effectively track the maximum power of multiple peaks,the gray wolf optimization-perturbation observation method has the disadvantages of slow tracking speed and poor stability,resulting in continuous power oscillations.Therefore,this paper focuses on the shortcomings of the basic gray wolf algorithm.The factor a and the control coefficient c are improved,the dynamic weight adjustment method is introduced to balance the local search and the global search,and the cuckoo search algorithm is used to randomly step the position of the leader wolf in the gray wolf algorithm to avoid the retention of elites in the later iterations The strategy caused the gray wolf algorithm to fall into the local optimum.An improved gray wolf optimization-cuckoo(MGWO-CS)hybrid algorithm was designed,and it was applied to the photovoltaic maximum power point tracking control for the first time.In order to verify the reliability of the algorithm,this paper sets up three different environmental conditions,and compares simulations with the gray wolf(GWO)algorithm,the cuckoo(CS)algorithm and the GWO-P&O method.The experimental results show that the MGWO-CS algorithm tracking speed Fast,high precision of optimization,applied to MPPT control can effectively track the maximum power point with low power loss,which is of positive significance for improving the efficiency of photovoltaic array power generation.