Research On MPPT Control Of Photovoltaic Power Generation System Based On Improved Whale Algorithm

Photovoltaic power generation equipment is usually installed outdoors in the changeable environment,and the photovoltaic power generation system is often covered by clouds,dust,etc.,which causes the output power characteristic curve of the photovoltaic power generation system to show a multi-peak characteristic,making it difficult to track and control the maximum power point tracking(MPPT).In order to solve the problems of the failure of the MPPT algorithm under partial shadows and the slow tracking speed,this thesis conducts research on the photovoltaic power generation MPPT control strategy.First,based on the analysis of the existing photovoltaic power generation system architecture,this thesis chose the module-integrated photovoltaic power generation system as the research object.By building a photovoltaic cell simulation model to simulate the partial shadow environment,the output characteristic curve was obtained.the DC-DC converter in the photovoltaic power generation system was analyzed again,and the synchronous boost circuit converter with more flexible control was simulated and studied.Then,the perturbation observation method and the conductance increment method were simulated,and it was concluded that the traditional algorithm could not achieve MPPT control in a partially shaded environment.Due to the poor performance of the intelligent algorithm in the tracking effect,This thesis studied the Whale Optimization Algorithm(WOA)with outstanding optimization capabilities.Due to the weak global optimization ability of WOA,premature convergence occurred in the multi-peak optimization problem,resulting in optimization failure.Therefore,the Levi flight algorithm with strong global search capability was combined with the whale algorithm to propose a hybrid The Levi flight-whale algorithm selects the algorithm through the greedy criterion to realize the MPPT control of photovoltaic power generation in the case of partial shadow occlusion;in order to improve the efficiency of MPPT control,the convergence factor based on the cosine function was derived to update the distance to further improve the speed of the algorithm optimization.the particle swarm algorithm,gray wolf algorithm,WOA and Improved Whale Algorithm(IWOA)were tested through standard single-peak and multi-peak test functions,by analyzing the advantages and disadvantages of algorithms in solving optimization problems,it was verified that IWOA is more suitable for multi-peak optimization problems.Then,the MPPT control strategy using direct duty cycle was proposed,and convergence criteria and restart criteria were designed to cope with drastic changes in the external environment.An photovoltaic power generation MPPT control simulation platform based on the synchronous Boost converter was built.Through simulation analysis of particle swarm optimization,WOA and IWOA,the superiority of WOA in full illumination,partial shadow occlusion and shadow mutation environment is verified and the effectiveness of the improvement strategy is verified.Finally,a photovoltaic power generation MPPT control experimental platform based on STM32 was built on the basis of simulation,the design of a 300 W synchronous boost converter was completed,and the feasibility of the synchronous boost converter was verified.Through MPPT control experiments in a simulated shadow occlusion environment,it was proved that the algorithm can reduce power loss and improve photovoltaic power generation efficiency.