| Energy shortage and environmental pollution are becoming the major problems that mankind needs to overcome in the 21 st century.As an important pillar industry of national economy,automobile industry has important influence on the development of social and environment.As an emerging industry,new energy vehicles represented by Electric Vehicles(EVs)play an important role in promoting energy conservation,emission reduction and mitigating environmental problems.However,the rapid development of EVs also brings challenges to the safety and stability of the grid operation.The huge charging demand of EVs will aggravate the load fluctuation of the grid.The optimal scheduling of EVs' charging and discharging processes is an effective way to improve the safety and stability of the Smart Grid(SG).Based on the game theory,this paper studies the interaction between SG and EVs,formulates the optimization model and pricing mechanism for EVs to participate in the demand side response of SG,realizes the optimization and regulation of the grid operation state.The main research contents of this paper are introduced as follows:Firstly,this paper analyzes the important content of EVs participating in Demand Response(DR)of the SG,discusses the types and characteristics of EV in the market,establishes the battery charging and discharging model,and analyzes the charging mode of EV and the characteristics and constraints of Vehicle to Gird(V2G)technology.This paper analyzes the DR model from the perspective of architecture and mechanism,and presents the characteristics and usages of DR under different architectures and mechanisms.Game theory is an important mathematical theory to solve the complex and coupling relationship in DR,the Sequential game and Stackelberg game are modeled and analyzed,and the definition of Nash equilibrium is given.Secondly,based on the Sequential game and V2 G theory,the optimal model of Plug-in Electric Vehicles(PEVs)participating in smart grid DR is established.This model aims to optimize PEV's participation in demand response process.By designing a PEV multi-factors considered priority mechanism combining with the demand-side pricing mechanism based on PEVs' regulation quantities,and considering the situation that PEV repeatedly participates in load regulation,the load fluctuation of the smart grid can be stabilized on the basis of satisfying the benefit of the Aggregator(AGG),so as to maximize the regulation benefit of individual PEV users.The regulation effect and the performance under dynamic events of this model are analyzed and verified through the establishment of multi-group comparison simulations.Finally,the concept of classification modeling is introduced in the work to divide EVs in the market into Private EVs(PrEV)and Public EVs represented by the Electric Taxi(ET).Then,according to the characteristics of the two types of EVs,the Monte Carlo and Stackelberg game are used to construct the load model of EVs,the charging load of PrEV can be obtained,and the over-threshold voltage fluctuation of each grid node can be calculated based on IEEE-14 bus system.With the aim of reducing voltage fluctuation,the voltage-load model of each node is established to obtain the load regulation quantity to suppress the voltage fluctuation.Finally,the Stackelberg game model between the ETs and battery changing/swapping stations is established,and the voltage regulation quantity is taken as the index.The simulation results show that the above method can reduce the over-threshold fluctuation of node voltage,increase the daily average operating revenues of ETs,and narrow the income gap between the stations. |
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