Research On Optimal Scheduling Of MTPSS System Based On MOPSO Algorithm

My country’s electrified railways have long mileage,wide coverage,and many models in service,making them a major energy user in the power system.Under the guidance of "low carbon and green" and the response of national policies,the combination of electrified railway and new energy has become an inevitable trend of development.In order to fully realize the low-carbon and green development of the traction power supply system,it is necessary to build a new type of traction power supply system,focus on the connection of new energy to the traction power supply system,and carry out multi-faceted and in-depth research.This dissertation intends to carry out the research on the optimal scheduling problem of the Multi-Source Traction Power Supply System(MTPSS)including power quality monitoring and comprehensive economic cost planning.The research work of this dissertation is as follows:First of all,through the complexity and particularity of the structure of the traction power supply system,the uncertainty of the operating conditions of the high-power traction load and other factors,the multiple access methods of new energy sources are compared and analyzed,and the most suitable access method is selected as the MTPSS system.The grid structure is based on the Matlab/Simulink simulation software,and the simulation model of the MTPSS system including wind power generation system,photovoltaic power generation system,hybrid energy storage system,traction power supply system,and traction load are built on the Matlab/Simulink simulation software.Secondly,by analyzing the fluctuation,randomness and intermittency of wind and light output,the Variational Mode Decomposition(VMD)should be performed on the compensation power of the Hybrid Energy Storage System(HESS)in the MTPSS system.Decomposition,and use the Sparrow Search Algorithm(SSA)to optimize its decomposition process.The decomposed Intrinsic Mode Function(IMF)is divided by Hilbert Transformation(HT),and the high-frequency and low-frequency components of the power signal are reconstructed.The energy characteristics are respectively allocated to the supercapacitors and batteries in the hybrid energy storage to realize the hybrid energy storage configuration of wind and solar complementary.Then,considering the power quality problems of the traction power supply system after multi-source access and the economic cost of investing in the construction of a new traction power supply system,on this basis,a dual goal of minimizing the power quality index coefficient of the traction power supply system and the minimum comprehensive operating cost is established.The optimization function was established,and the model was constrained by the balance of supply and demand and the output limit of new energy.A multi-objective optimal scheduling model was established with the MTPSS system as the research object.Then,the optimal scheduling model is solved in Matlab by using the Multi-Objective Particle Swarm Optimization(MOPSO)algorithm,and finally the multi-source optimal scheduling output results of the MTPSS system are obtained,and other issues to analyze.Finally,after the simulation analysis,the optimal solution set for the optimal scheduling problem of the MTPSS system based on the MOPSO algorithm designed in this dissertation is obtained.The optimization results show that the wind and solar energy are effectively absorbed,and the coordinated and optimized output of wind and solar energy storage meets the fluctuating power demand of the load,economic costs are reduced,and alleviates the more prominent power quality problems before the optimization.