Research On Collaborative Optimization Operation Of Coupled Electric Power And Traffic Network Based On Traffic Equilibrium Theory

Transportation industry is another big consumer of fossil energy besides power generation industry.Under the dual pressure of environmental pollution and energy shortage,realizing the transition of transportation electrification has become a main direction of future development.However,with the development and popularization of electric vehicles(EVs),the interaction between urban transportation system and power distribution system has been strengthened,and their operation state has gradually evolved from independent to highly coupled.In this case,the operation scheme considering single system constraints can not meet the requirements of maximizing social benefits,and the coordinated operation of the two systems has become an urgent problem.Based on this,from the perspective of system interconnection,this dissertation focuses on the study of the collaborative optimization operation of coupled electric power and traffic network(CEPTN)based on traffic equilibrium theory.The details are as follows:Firstly,taking plug-in fast charging station(FCS)as the main charging mode,this paper focuses on the elastic response behavior of EV users to charging waiting time and charging price,and a distributed coordinated operation model for the CEPTN are proposed with elastic charging demand considering the profits of both traffic users and power distribution network(PDN).This model employs a traffic assignment model considering mixed user equilibrium to describe the distribution of traffic flow,and uses an optimal power flow model based on second-order cone relaxation to calculate the power flow distribution.And then,it is solved iteratively by the designed distributed coordinated operation algorithm.A case study is performed to verify the advantages of the proposed model and algorithm in improving the power flow distribution of PDN and alleviating traffic congestion,meanwhile,the effects of the elastic charging behavior of EVs on the coordinated operation of the CEPTN are analyzed.Secondly,the state of charge and mileage limit of EVs are further considered,and a more refined traffic network model is established.It is composed of two parts: an effective path generation model and a traffic assignment model,and is solved by a specially designed adaptive algorithm.Considering different backgrounds of plug-in FCS and dynamic wireless charging station(WCS),a distributed coordinated operation model of the CEPTN with the mileage limit of EVs is proposed.A case study is performed to verify the effectiveness of the proposed model and algorithm,and investigate the effects of two charging modes and penetration level of EVs on the coordinated operation of the CEPTN.Thirdly,aiming at the problem that the urban traffic network(UTN)and PDN are blocked at the same time in the late peak period under the DWC mode,which is caused by the shift of EVs charging demand peak to commuting hours,resulting in the coincidence of traffic peak and power load peak,the time flexibility of traffic demand and power demand is deeply explored,and a multi-period traffic assignment model and optimal power flow model are established.Meanwhile,a distributed coordinated operation model of the CEPTN and its corresponding intelligent management system are proposed considering the characteristics of traffic demand time-shifting and regular load demand response.The effectiveness of the proposed model is verified by simulation examples and the impact of time-shifting traffic demand and regular load demand on the coordinated operation of the CEPTN is analyzed.Finally,aiming at the uncertainty problem caused by stochastic path behavior of EVs and traffic demand prediction error on the coordinated operation of the CEPTN,in the scenario of centralized management of coupling network,considering the interests of UTN,PDN and traffic users,a coordinated operation model of the CEPTN is proposed based on hybrid stochastic user equilibrium(SUE)/ information gap decision theory(IGDT)method.The presented model consists of two stages.The first stage is a collaborative optimization model of the CEPTN with the random path behavior of EVs.On the basis of the first stage,the second stage establishes a risk decision model considering the prediction error of the traffic demand.The effectiveness of the presented model and method are verified by simulation examples,and the impacts of stochastic path behavior of EVs and traffic demand prediction error on the coordinated operation of the CETN are analyzed.