The Optimal Operation Of Microgrid Based On Improved Particle Swarm Optimization For Combined Cooling,Heating And Power

Social progress and development are inseparable from energy and environment.Reducing energy consumption in production and environmental protection has become people’s consensus.The CCHP microgrid system has the advantages of flexible operation mode,high energy utilization efficiency and low environmental pollutant emission,which is in line with the trend of coordinated development of energy and environment in the current society.Firstly,this article expounds the working principle and operating characteristics of the components of the system,such as wind turbine,solar photovoltaic,fuel cell,micro gas turbine,absorption refrigerator,heat exchanger and battery,at the same time increase electric chiller,gas boiler as auxiliary units,when the micro gas turbine refrigerating and heating capacity is insufficient can serve as a powerful supplement.Then,according to the driving distance,charging time,the owner’s commuting time,the state of charge and other uncertain factors,the mathematical models of disorderly charging and orderly charging and discharging of electric vehicles were established,and the corresponding load curves of electric vehicles were obtained based on monte carlo random sampling simulation.Afterwards,put forward multi-objective particle swarm optimization algorithm based on gaussian variation and adaptive variable parameters,using dynamic nonlinearity to adjust inertia weight and acceleration factors to solve algorithm which is easy to fall into local optimization and often shocks around global optimal solution at the end of the iteration.considering from the convergence and diversity of Pareto frontier,propose two stage selections of global optimal solution,increase gaussian variation points in external documents,and do gaussian mutation strategy of the probability changes with iterations in the population,use five standard functions to test the new algorithm,evaluate the results produced of different algorithms through three evaluation criteria of convergence,diversity and comprehensiveness,results show GDMOPSO which can improve the convergence and distribution of the algorithm.Finally,research microgrid system combined cooling,heating and power with controllable load--electric vehicle,taking the economic operating cost of the system and pollutant emission as the objective function,according to the balance of electric power,cold power,thermal power,output of each micro-sources,the state of battery and electric vehicle,the interaction power with large power grid,establish an optimal scheduling model of microgrid with multiple objectives,taking typical days in summer and winter as research examples,the scheduling optimization of microgrid system combined cooling,heating and power is carried out by GD-MOPSO algorithm under different control strategies,obtain the optimal output of each energy supply equipment and transactions with the big grid,contrast and analyze optimized configuration results of disorderly charging and orderly charging and discharging of electric vehicles from minimal operating costs and pollutant emissions,the results show that the control of orderly charging and discharging of EV is beneficial to the security and stable operation of CCHP microgrid system.