Research On Photovoltaic Array System Under Partial Shadow Based On Improved MPPT Algorithm

In photovoltaic new energy industry,the output P-U characteristic of photovoltaic array under partial shadow is multi peak curve rather than single peak curve.So that finding the appropriate Maximum Power Point Tracking(MPPT)algorithm under partial shadow is the key technology to study the improvement photovoltaic output power.In this paper,the simulation model of photovoltaic cell is firstly established according to the mathematical model,and the output characteristic of photovoltaic array under partial shadow is emphatically analyzed.Meanwhile,the simulation model of photovoltaic array system is built.The traditional MPPT algorithm(disturbance observation method,variable step size disturbance observation method and conductance increment method)is used to simulate and analyze the dynamic illumination and partial shadow illumination of photovoltaic array system.The result which the three algorithms can adapt to the dynamic illumination environment but can not find the maximum power point under the partial shadow is showed by simulation data.Then,particle swarm optimization algorithm is used to simulate and analyze the complex illumination environment of static partial shadow.According to the simulation results,the deviation between the simulation maximum power point and the theoretical value is small,so that this algorithm can track the maximum power point of photovoltaic array.However,slow convergence speed and large fluctuation in the convergence process are caused by the number of iterations of the algorithm.At last,particle swarm optimization algorithm is improved with immune algorithm in this paper,which can absorb the advantages of particle swarm andimmune algorithm.This new algorithm can improve the ability to get rid of local optimal value.The simulation analysis of photovoltaic array system under static partial shadow is carried out with new algorithm.Compared with the simulation results of particle swarm optimization,the search time of immune particle swarm optimization is shorter greatly.In the process of searching,the number of iterations is decreased and the fluctuation amplitude is obviously weakened.The simulation analysis of photovoltaic array system under dynamic partial shadow is carried out with new algorithm.Compared with the simulation results of particle swarm optimization,the maximum power value tracked by the new algorithm is closer to the theoretical value.The result which the immune particle swarm optimization algorithm is an ideal MPPT algorithm for photovoltaic array system under partial shadow can be concluded through the above analysis.Not only the maximum power point in multi peak state can be caught under dynamic partial shadow,but also more advantages can be taken including fast tracking speed,less iteration times and small tracking process fluctuation under static partial shadow.