Research And Application Of MPPT Based On Improved Sparrow Search Algorithm

Photovoltaic power generation has the obvious characteristics of cleanliness and environmental protection,and it has a long lifespan after one-time investment.However,in the case of changes in light and other environmental factors,the power generation of photovoltaic power generation systems will fluctuate significantly.At this time,the conventional maximum power point tracking algorithm may fall into local optimum and cannot be effectively tracked,which eventually leads to the reduction of system power generation efficiency and generated electrical energy.Therefore,in a complex environment,it has important meaning to quickly and precisely find the optimal operating point for the effective improvement of photovoltaic power generation efficiency.The main research contents are as follows:(1)Principle analysis of photovoltaic power generation system and establishment of photovoltaic cell model.The simulation model of photovoltaic cells established to analyze the variation of output characteristics when the ambient light intensity and temperature change.The output characteristics of photovoltaic array in local shading environment are analyzed,and a 3×2 photovoltaic array simulation model is built.The simulation results show that the output power of photovoltaic array presents multi-peak characteristics in local shading environment.(2)The basic principle of maximum power point tracking(MPPT)and the conventional MPPT algorithm are introduced.The photovoltaic static and dynamic simulation analysis of the three conventional MPPT algorithms are carried out by Matlab/Simulink software.The simulation results show that three algorithms can find the maximum output power in static simulation,but the tracking accuracy is insufficient.In dynamic simulation,only particle swarm algorithm can find the maximum output power,but the oscillation amplitude is large after stability.(3)Research on Sparrow Search Algorithm(SSA).Aiming at the problems existing in the conventional MPPT algorithms,this paper adopts the sparrow search algorithm for optimization,and further improves it.In order to verify the applicability of the SSA algorithm in MPPT,the photovoltaic array model is built for photovoltaic static and dynamic simulation analysis.The simulation results show that SSA algorithm can find the optimal value in both simulation modes.After stabilization,the output power oscillation amplitude is small and the tracking accuracy is high,which verifies the applicability of SSA algorithm.(4)Research on Improved Sparrow Search Algorithm(ISSA)and its application in MPPT.Aiming at the shortcomings of the SSA algorithm,the location update strategy is introduced to optimize the location of discoverers and followers in the population so as to improve the global search ability of the algorithm.Tent chaotic mapping is introduced to make the initial position of the population uniform,and the diversity of the algorithm population is improved in the late iteration to improve the global development ability of the algorithm.The random walk strategy is introduced to continuously disturb the population in the iterative process,thereby improving the ability of the algorithm to identify the local optimal value.The ISSA algorithm is compared with the other three intelligent algorithms by using 20 standard test functions.The simulation results show that ISSA algorithm with optimization strategy has obvious advantages in convergence and stability.The MPPT simulation model based on ISSA algorithm is built.Aiming at verifying the feasibility of the algorithm,the static and dynamic simulation comparisons are carried out with the particle swarm algorithm and SSA algorithm.The simulation results show that ISSA algorithm can search the maximum power more quickly and accurately,which verifies the applicability and effectiveness of the multi-strategy improved algorithm in MPPT.