MPPT Algorithm For Photovoltaic Array Under Local Shading Based On Adaptive Particle Swarm Optimization

In recent years,people’s demand for energy has increased,and various environmental problems have accompanied them,and people have become very interested in the use of renewable energy.In the process of photovoltaic power generation,photovoltaic cells cannot maintain uniform light at all times.When unevenness or shading occurs,it will cause battery mismatch and hot spot effects.This will increase the loss of photovoltaic cells and cause irreversible damage to them in severe cases.Affected by this,the output P-V characteristic curve of the photovoltaic array no longer shows a single peak,but shows multiple peaks,so the maximum power point tracking algorithm is not effective.Therefore,it is of practical significance to study the MPPT technology under partial shading.First of all,this article introduces the working principle of photovoltaic cells,analyzes the different mathematical models used in different applications,and then builds a simulation model of a single photovoltaic cell on the MATLAB/Simulink platform,and then builds a part of the photovoltaic cell in series and parallel.Simulation model of photovoltaic cells in shaded state.The mechanism of the multi-peak phenomenon of photovoltaic cells when partial shading occurs is described in detail,and the output characteristic curve when shading is analyzed through simulation.Secondly,this paper conducts theoretical research on traditional MPPT technology and particle swarm algorithm,obtains the output characteristic curve of traditional algorithm through MATLAB/Simulink simulation,and obtains the advantages and disadvantages of each algorithm and the applicable occasions after comparison.This leads to the improved adaptive particle swarm algorithm used in this article.In this paper,the parameters of the particle swarm algorithm are improved,voltage and duty cycle are selected as the new particles,the inertia weight is changed to the nonlinear dynamic weight,the learning factor is changed to the adaptive learning factor,and the algorithm is applied to the algorithm through the MATLAB/Simulink platform The performance under partial shading is analyzed and compared with the perturbation method,it is concluded that the algorithm has the advantages of higher accuracy and faster speed.Finally,the analysis of experimental results shows that the tracking time of the disturbance observation method is 0.03 s,the improved particle swarm algorithm based on voltage and duty cycle is 0.05 s and 0.32 s,and the steady-state oscillation power percentage is 0.9,0.4,and 0,respectively.And the disturbed observation method does not have the ability to deal with shadows.That is to say,it is concluded that compared with the traditional method,the improved particle swarm algorithm proposed in this paper has a significant effect on solving the multi-peak problem caused by shading,and the oscillation is small,which can effectively improve the efficiency of photovoltaic power generation.