Optimal Operation Method For Microgrid In Metro Station

The rapid growth of urban economy has accelerated the development of the subway throughout the country,but the normal operation of the subway needs to consume a lot of energy,resulting in a series of energy crisis and environmental pollution problems.The cooling(heating)energy used by the subway station during operation accounts for 1/4 of the total energy demand of the entire subway system,so the cooling(heating)demand of the subway station is huge.At present,most subway stations mainly provide cooling and heating in the form of electric heating and refrigeration.In today’s environment of energy depletion crisis,the combined cooling,heating and power generation microgrid in subway stations has been put on the agenda with its ability to realize the integration of cooling,heating and power supply,absorbing new energy and improve the utilization rate of energy.In addition,in the process of cooling,heat and power combined microgrid absorbing new energy,it is bound to have an impact on the microgrid system and may also affect the normal operation of the microgrid.Based on this,this paper focuses on the coordinated optimization operation of "source-network-load-storage-vehicle" microgrid based on the combined cold,heat and power supply in subway stations.The main work is summarized as follows:(1)Based on the related concepts of microgrid and combined cooling,heating and power systems,a combined cooling,heating and power microgrid system for subway stations has been established;photovoltaic power generation units,gas turbine units,ground-source heat pump units,gas boiler units,and electric refrigeration have been established The mathematical models of units and absorption refrigeration units provide relevant equipment model support for the research on the optimization operation method of the combined cooling,heating and power microgrid in subway stations.(2)Research on the optimal operation of the combined cooling,heating and power system in subway stations,using the number of intervals to describe the uncertainty of wind and solar output,and establishing an interval linear programming model for the optimized operation of the combined cooling,heating and power system in subway stations based on the number of intervals.The two-stage decomposition method transforms the interval linear programming model into two upper and lower linear programming models without interval numbers.The Cplex+Gurobi mathematical programming solver is used to solve the proposed model,and each unit in the system in the typical day of different seasons is given.The processing conditions and the daily operating costs of different typical days are affected by varying degrees of fluctuations in load,photovoltaic output,and demand response.(3)Considering the uncertainty of distributed new energy output will bring inconvenience to the optimization of microgrid operation.A mathematical model for the coordinated optimization operation of“source-grid-load-storage" of the combined cooling,heating and power microgrid in subway stations considering energy storage devices was established.Random chance constraints were used to deal with the uncertainty constraints in the model.Improve the BP neural network to approximate the uncertain function.Based on the defect of the single control parameter of the original quantum particle swarm algorithm,Q-learning is proposed to improve the quantum particle swarm algorithm and used to solve the proposed planning problem.Comparing the relationship between the convergence accuracy of different algorithms and the parallel computing time for different node microgrids,in the low node microgrid system and the high node microgrid system,the fitness values calculated by the algorithm proposed in this paper are respectively Converges to 0.33 and 0.41,GA algorithm converges to 0.47 and 0.45,PSO algorithm converges to 0.5 and 0.475,respectively;the calculation time of parallel calculation is 3.96 times and 2.77 times faster than that of serial calculation,which verifies that the proposed algorithm is based on Parallel computing stochastic simulation technology and the rationality and effectiveness of the improved algorithm.(4)Considering the randomness and ambiguity of distributed new energy output and electric vehicle charging and discharging power,a mathematical model of coordinated optimization operation of“source-grid-load-storage-vehicle" was established for the combined cooling,heating and power microgrid in subway stations.The random fuzzy chance constraint method is used to deal with the random ambiguity in the model.The proposed model is solved by a hybrid intelligent algorithm based on parallel computing random fuzzy simulation,improved BP neural network and non-dominated sorting genetic algorithm with elite strategy.The comparison of algorithms shows that the Pareto frontier solution of the NSGA II algorithm dominates the Pareto frontier solution of the MOPSO algorithm,the compromise solution satisfaction of the NSGA II algorithm is 0.638,and the MOPSO algorithm is 0.609;the comparison of different fuzzy confidence levels can be obtained,the fuzzy confidence The lower the level is set,the closer the calculation result is to the forefront of Pareto.It can be obtained that the NSGA II algorithm has a better effect in solving the optimization operation problem of the microgrid.