Research On Daily Operation Optimization Of AC/DC Hybrid Microgrid Based On Improved Grey Wolf Algorithm

Distributed power sources will cause a series of problems when they are connected to the large power grid,making the distributed energy sources unable to be fully utilized.In order to give full play to the advantages of distributed energy,microgrid technology came into being.Microgrid technology is the most effective strategy to solve the problems generated when distributed power sources are connected to the large power grid.It can well absorb the scattered clean energy to generate electricity,and it can also improve the flexibility and reliability of power supply to the load.As a hot topic in microgrid-related research,the operation optimization of microgrid refers to the reasonable coordination of the output of various micro sources in the system within an optimized time scale,so as to achieve various expected goals such as economy and reliability of system operation.Therefore,the operation optimization of microgrid has important research value.This article first builds a typical AC/DC hybrid microgrid system,which includes photovoltaic power generation,wind turbines,diesel generators,and energy storage systems.The mathematical model of each micro-source is introduced in detail.According to the actual operating conditions,the AC/DC hybrid microgrid has two operating states:grid-connected and islanding.The possible operating modes of the system under different operating states are analyzed.Taking the minimum daily operating cost of the system as the goal,the objective function under different operating conditions is established,the constraint conditions are taken into account and the corresponding processing strategies are given,and the strategies to be followed in the daily operation optimization of the AC/DC hybrid microgrid under different operating conditions are discussed.Then,the existing typical intelligent optimization algorithm particle swarm optimization algorithm and genetic optimization algorithm are briefly introduced,and the principle and mechanism of the gray wolf optimization algorithm are discussed in detail.The original gray wolf optimization algorithm guide mechanism strategy is backward,and it is easier to fall into the local area.Due to the shortcomings of optimization,poor optimization accuracy and slow convergence speed,this paper introduces a dynamic weight ratio mechanism strategy to improve the original gray wolf algorithm.In order to verify the feasibility and superiority of the improved gray wolf algorithm,the original gray wolf algorithm,particle swarm algorithm and genetic algorithm are selected as the comparison objects,and six benchmark test functions are used for simulation analysis.The simulation results verify that the improved strategy using the dynamic weight ratio mechanism is feasible,and the improved gray wolf algorithm has the best performance.Finally,the daily operation optimization solution process of AC/DC hybrid microgrid based on the improved gray wolf algorithm is given.Taking an AC/DC hybrid microgrid system in a certain area as an example,three typical days of spring and autumn,summer and winter scenarios are selected.In the network operation state and the island operation state,respectively,the improved gray wolf algorithm is applied to solve the daily operation optimization mathematical model of the system 10 times,and the optimal solution is selected as the reference basis for the daily operation optimization of the system.The experimental results show that the improved gray wolf algorithm can better optimize the daily operation of the AC/DC hybrid microgrid.