Multi-objective Optimal Scheduling Of Microgrid Based On Improved Particle Swarm Optimization Algorithm

With the continuous development of new energy technology,microgrid technology has been widely applied.Microgrid is a small power generation and distribution system composed of micro gas turbines,fuel cells,energy storage systems,and loads.The advantage of this system is that due to the random characteristics of distributed power sources and loads,it can interact with the large power grid,avoiding the dependence of the large power grid operation on large capacity energy storage devices,and also reducing the adverse effects caused by fluctuations and random loads.Therefore,it is necessary to install various distributed power sources and energy storage devices in the microgrid.In the process of microgrid optimization scheduling,multi-objective particle swarm optimization algorithm can optimize multiple objective functions simultaneously,so that each objective function can obtain the optimal solution,thereby minimizing system cost,minimizing environmental pollution,and maximizing power supply reliability.The MPSO algorithm has good global search ability and strong local search ability,but is sensitive to the initial particle swarm position.Therefore,in multi-objective particle swarm optimization,introducing an external file saving strategy into the algorithm can improve the search speed and convergence accuracy of the algorithm.Due to the current lack of research on the characteristics and load characteristics of distributed power sources in microgrids,it is difficult to establish a multi-objective optimization model for microgrids.This article proposes a multi-objective optimization scheduling method based on particle swarm optimization algorithm,providing a new approach for microgrid planning.In this regard,this article proposes a multi-objective optimization scheduling model for microgrids based on modified particle swarm optimization algorithm.The specific work is as follows:(1)The paper introduces five common power generation units in microgrid,including wind power generation,photovoltaic power generation,diesel generator,micro gas turbine and energy storage battery,and analyzes the output models of different distributed power sources.Then,different optimal control strategies are given for the system in grid-connected and off-grid mode.(2)The problem that particle swarm optimization algorithm is prone to premature convergence is improved by changing the inertia factor and learning factor of particle swarm optimization algorithm from static to dynamic.The performance of the improved particle swarm optimization algorithm is tested by two classical functions.The simulation results show that the convergence performance of the improved particle swarm optimization algorithm is improved to some extent.(3)According to the established optimal scheduling model of the micro grid,complete the case verification analysis,and apply the improved multi-objective particle swarm optimization algorithm to the typical summer and winter examples to achieve the optimal objective function.Under different decision objectives,the multi-objective microgrid 24 hours a day scheduling optimization is carried out,and the optimal scheduling analysis results are obtained.Through the comparison of four different operation strategies,it can be concluded that the improved particle swarm optimization algorithm can complete the optimal scheduling work of micro grid,and show good performance.At the same time,the comparative analysis of multi-objective and single objective optimization scheduling is carried out,and the advantages of multi-objective optimization scheduling can be obtained.