Economic Dispatch Of Microgrid Based On Improved Quantum Particle Swarm Optimization

At present,the transformation of China’s economic growth mode and the adjustment of industrial structure have had a profound impact on the energy power system.In order to meet the practical needs of energy security and low-carbon development,the development of microgrid technology has become an important way to optimize power production mode and promote renewable energy consumption.As a comprehensive integration technology including renewable distributed generation,microgrid has flexible power generation mode and can bring considerable benefits to the energy market.However,microgrid involves the comprehensive utilization of multiple energy sources,the joint scheduling of microgrid has gradually become one of the key issues for scholars.Firstly,the economic dispatch model of microgrid was established.The output mode and power generation costs of wind turbine,photovoltaic cell,micro gas turbine,fuel cell and battery were analyzed,and the output model and costs model of the unit were constructed respectively.Based on the above model,the dispatching model of grid connected and isolated grid were constructed respectively,including objective function and constraint conditions.The objective function comprehensively considered the operation costs and environmental maintenance costs of microgrid,and the constraint conditions mainly included upper and lower limits of unit output,ramp rate constraint,battery charging and discharging constraint.Secondly,this paper improved the quantum particle swarm optimization algorithm.Based on the standard algorithm,this paper introduced differential evolution operator and weighting coefficient,and gave the specific algorithm flow.The introduction of differential evolution operator could improve the global search ability of the algorithm,and the introduction of weighting coefficient could improve the accurate convergence ability of the algorithm.Two algorithms were applied to the standard test function for experimental simulation,which proved the effectiveness of the above improvement measures.Thirdly,the economic dispatch strategies of connected grid and isolated grid were proposed.Based on the priority of ensuring the local consumption of clean energy in the system and meeting the load required by the system,the output of other units should be coordinated to realize the comprehensive maximization of environmental protection and economic benefits.Finally,the effectiveness of the algorithm was verified.Based on the microgrid dispatching strategy,the improved quantum particle swarm optimization algorithm was applied to the proposed dispatching model,and the dispatching results were analyzed.The results showed that the performance of the improved quantum particle swarm optimization algorithm was better,the convergence speed of the algorithm was faster in the early stage of optimization,and the performance of the algorithm jumping out of the local optimal solution was better in the middle and late stage of optimization,and finally a lower dispatching costs can be found.Therefore,the improved algorithm proposed in this paper had a certain reference value for solving the economic dispatch problem of microgrid.