Research On Multi-Objective Optimized Operation Of Integrated Optical Storage And Charging System Based On Demand Response

In recent years,energy and environmental problems such as global energy shortage,serious pollution and climate change have attracted more and more attention.As a "green" means of transportation,electric vehicles are growing rapidly.At the same time,photovoltaic power generation has become the focus of new energy development because of its safety and cleanliness.With the rapid development of energy storage technology and electric charging technology,the integrated optical storage and charging system,which integrates photovoltaic power generation system and energy storage system and electric vehicle charging pile in situ,has emerged as the times require.How to optimize the operation of integrated photovoltaic storage and charging system and improve the operation efficiency and economy has become one of the research hotspots.This thesis analyzes the structure of the integrated optical storage and charging system and establishes the mathematical model of each component.The demand response strategy is implemented in the isolated island and grid-connected operation scenarios,and the multi-objective optimization operation of the integrated optical storage and charging system is studied.In the case of isolated island operation scenario of the integrated optical storage system,based on the elasticity coefficient of electricity price,the optimization model of peak-cutting and valley-filling with load is established,and the double-objective problem is transformed into single-objective problem by weight coefficient,which is solved by genetic algorithm.The results show that the time-sharing price strategy can avoid the excessive peak load,improve the load distribution curve and guide the electric vehicle to charge in an orderly manner.In the case of grid-connected operation of integrated optical storage and charging system,this thesis proposes an optimal operation strategy considering load peak-valley transfer under time-sharing electricity price.On this basis,an optimization model aiming at minimum load peak-valley difference and minimum operating economic cost is established.Through comparing and analyzing the simulated binary crossover operator in the NSGA-? of fast non-dominated sorting genetic algorithm with elite strategy,a normal distributed crossover operator is proposed for NSGA-?,and the improved algorithm is used to solve the optimization model.By comparing the Pareto frontier and optimization results in four scenarios,it is proved that the implementation of demand response strategy in the integrated optical storage system can effectively reduce the load peak and valley difference...