Coordinated And Optimized Management Of Multi-Microgrid Group In Consideration Of Battery Health

With the continuous increase in the installed capacity of renewable energy and the maturing of microgrid technology in China,microgrids with different operating modes and scales will inevitably appear in the power system.In this case,in order to reduce the coordination pressure in the power system,it is necessary to study the regional autonomous system,namely the multi-microgrid group system.In addition,the energy storage system plays a very important role in the multi-microgrid group scheduling,and more attention should be paid to the healthy and reasonable operation of the energy storage system in the multi-microgrid group.Therefore,it is of great significance to study the coordinated and optimized management of the multi-microgrid group in consideration of battery health in this paper.The main work of this paper is described as follows:First,the network structure and network mode of the multi-microgrid group are analyzed,and the network structure and network mode to be adopted in this article are determined.Based on the above networking characteristics,the coordinated control system of the multi-microgrid group is studied,the hierarchical coordinated control structure of the multi-microgrid group based on the multi-agent system is constructed,which provides an efficient and feasible control system for optimization scheduling of multi-microgrid group.Second,the operating principles and characteristics of the DG in the microgrid are studied,and the output power models of wind and photovoltaic power generation units,the fuel cost models of fuel cells and diesel generators,and the mathematical models of energy storage systems are established.Considering the impact of charging and discharging process on the battery life,an improved throughput method considering the weight of life loss is proposed,and the battery life model is constructed.In addition,the battery cost model is further studied,and the ratio of 2 times absolute value of discharge power to total throughput is proposed to calculate the loss cost,which can avoid the situation that the battery is not charged or charged less in order to lower the cost.At the same time,the state of charge is also included in the calculation formula of battery cost loss,so as to further improve the battery cost model and lay a foundation for further research.Then,in order to avoid the battery running in the state of low charge for a long time and limit the number of charging and discharging cycles of small current,the charging and discharging optimization strategy considering the state of charge is put forward.Based on the function of time-of-use electricity price as "peak reduction and valley filling",a scheduling strategy of multi-microgrid group considering time-of-use electricity price is proposed.Then,the AC multi-microgrid group consisting of wind turbine,photovoltaic,battery,diesel engine,and fuel cells is taken as the research object.With the minimum daily operation cost of the multi-microgrid group as the optimization objective,the optimization scheduling model of the multi-microgrid group is constructed under the conditions of satisfying relevant constraints,and the model which is solved by the improved particle swarm optimization algorithm.Finally,the cases of separate grid connection and coordinated grid connection of multi-microgrid group are compared and analyzed through numerical simulation,as well as whether the optimization of energy storage of multi-microgrid group is considered.The results show that the coordinated grid-connection of multi-microgrid group can effectively improve the energy utilization rate and the overall economy;after considering the energy storage optimization,the utilization efficiency of the storage battery is improved,the life loss of the unit charge and discharge capacity is reduced,the overall operation mode of the storage battery is more reasonable,and the total daily operation cost of the multi-microgrid group is reduced,which verifies the rationality and effectiveness of the proposed multi-microgrid group optimization scheduling model in consideration of the battery health.