Application Of Swarm Intelligence Algorithm In Photovoltaic Power Generation

With the increasing of the population and the rapid development of economy,the energy of human needs is increasing.However,after nearly half a century of large-scale exploitation of traditional energy sources such as oil and coal,the stock has already been exhausted.Therefore,the development and utilization of new energy will inevitably become the future development trend.In the new energy,solar energy is an ideal alternative energy source to replace traditional energy with its advantages of no environmental pollution,convenient utilization and renewable energy.Due to the photovoltaic(pv)system is a nonlinear system,some of the optimization problem using the traditional optimization methods almost can not get ideal results,and swarm intelligence algorithm can well make up for the defect of the traditional optimization method,therefore,the research group of intelligent algorithm in the application of photovoltaic power generation is of great significance.First of all,this paper proposes a new algorithm: the lions algorithm.The basic flow of the algorithm is described,and the convergence of the algorithm is proved.The influence of each parameter on the convergence performance of the algorithm is analyzed.The global optimization ability of the algorithm is tested by using the test function,and compared with other group intelligent algorithms.Secondly,the output characteristic of pv is analyzed.Because the traditional MPPT cannot track the maximum power effectively under partial masking condition.In order to solve the problem of MPPT in partial masking condition,this paper presents the application of the lions algorithm in MPPT.The actual tracking effect is verified by simulation and experiment.Finally,based on the study of the control strategy of dual closed-loop grid-connected inverter,this paper makes an in-depth study of the system PI parameters.The PI parameters of the grid-connected inverter are used by using the proposed lions algorithm.