Multi-objective Dispatch Of Microgrid Based On Dynamic Fuzzy Chaotic Particle Swarm Optimization

With the constant improvement of the world economy and the further optimization of energy structure,the ratio of distributed renewable energy sources such as wind power and solar energy will increase sharply.So Microgrid which is used to control distributed energy sources has great potential.At the same time,with the technological innovation and cost reduction of electric vehicles,a large number of electric vehicles will access to grid in the future,including the Microgrid.Dispatch of Microgrid including electric vehicles belongs to multi-objective,multi-variable,multi-constraint condition and strong nonlinear optimized problem,which had not been solved very well.Therefore,Microgrid dispatching of electric vehicles will become an important research in power system.Based on the analysis of mathematical model about the micro source and electric cars,I proposed dynamic fuzzy chaotic particle swarm optimization to research the multi-objective dispatch of Microgrid including electric vehicles.Firstly,I respectively introduce the basic principles and mathematical models of the micro-sources such as wind power system,photovoltaic power system,microturbine,fuel cell power system and storage components such as battery.Secondly,In view of problem that the traditional particle swarm algorithm easily traps in local superior,in the initialization I introduce combination of the Chebyshev maps and the Logistic map,and in the process of particle update I introduce the Logistic map,which increases the ergodicity of particles and strengthens global optimization of algorithm.According to the problem of inertia weight in the process of particle swarm updating,the strategy is changing the inertia weight with iteration number.Based on above,I propose an algorithm which names improved Chaotic Mapping Particle Swarm Optimization(CMPSO).Then using the standard Particle Swarm Optimization(PSO),Chaos Particle Swarm Optimization(CPSO),CMPSO on Ackley 's function,Beale' s function,Goldstein-Price function and Bukin function N.6,the results show the superiority of CMPSO.Thirdly,according to multi-objective decision-making method of weighting and fuzzy membership,I put forward dynamic fuzzy multi-objective decision-making method,which uses dynamic objective function and fuzzy theory to solve the defects of the subjective weight.In view of the problem that traditional multi-objective particle swarm algorithm is easy to fall into local most superior,I put forward dynamic Fuzzy Chaos Particle Swarm Optimization(FCPSO)to deal with multi-objective scheduling of Microgrid,combining with CMPSO.Then I establish a scheduling of Microgrid with the goal of running cost and environmental cost.Results of simulation show that FCPSO has higher efficiency and better effect.Finally,by studying the regulation of electric vehicles charging and discharging,I get mathematical model of mileage,charging time,charging and discharge in disorderly mode for Batter Electric Vehicles(BEVs).A multi-objective scheduling of Microgrid including BEVs with the goal of running cost and environmental cost is established.The standard Particle Swarm Optimization(PSO),Chaotic Particle Swarm Optimization(CPSO)and dynamic Fuzzy Chaotic Particle Swarm Optimization(FCPSO)were used to solve this model.The simulation results show that optimization of the algorithm and addition of electric vehicles to Microgrid dispatching can save some cost.