Coordinated Power And Transportation System Operation And Pricing Towards Shared-Mobility-on-Demand Fleet

With the rapid development of electric vehicles(EVs)and the concept of sharing economy,shared electric vehicles show advantages in controllability.If the new transportation model could be developed on a large scale,it would certainly become an important way to promote energy conservation and emission reduction as well as realize the coordination between transportation system and power system.However,the power and transportation coupled system for shared electric vehicles presents unique characteristics on multiple levels.Compared with traditional private EVs,the control strategy of shared EVs is more complex,which needs to consider the coupling of multiple issues.Therefore,this paper aims to optimize shared electric vehicle loads from three dimensions,including power network,transportation network and power-transportation network,for the purpose of fully excavating the flexibility on the demand side.The main work is summarized as follows:As for the pricing and optimization of EV load in power system,this paper focus on its flexibility as demand response resources from the view of the power system operator.It can be found that the EV load participates in demand side mangement by means of load aggregation,where the aggregated load can be divided into power-type flexible load and energy-type flexible load,the EV load included.By summarizing the existing distributed demand response resources pricing methods,this paper finds out the limitations and designs a pricing mechanism based on benefit-sharing concept,which avoids the difficulty of obtaining accurate utility function or comfort function.On the basis of the proposed pricing mechanism,a mathematical model is established and an iteration-based chance-constrained algorithm is designed to solve the problem.Finally,a case study is given to verify the effectiveness and significance of the pricing mechanism.As for the pricing and optimization of shared EV load in traffic system,the classification and characteristics of shared EVs are firstly discussed in this paper.Then,based on the network flow theory,an extended road network system is established,which can simultaneously represent the scheduling and charging behaviors of shared EV.Considering the relationship between users’ demand for rides and transportation price,the pricing decision model of transportation system operators is constructed.Based on the above modeling contents,the optimization modeling of charging navigation,vehicle rebanlance.demand service and other sub-problems of shared EV fleets is completed.Finally,the part of case study verifies the correctness of the optimization results of above subproblems,as well as the influence of traffic price on traffic load and charging load,which proves that the model can be applied to large-scale transportation systems.Our work provides a research basis for the future development of shared electric vehicle fleets in China.As for the pricing and optimization of shared EV load in the power-transportation coupling system,this paper mainly considers the game equilibrium problem between charging network and transportation network operators.Firstly,in the charging network,the rooftop photovoltaic resources of each charge station are considered,and the uncertainty is analyzed based on the distributionally robust algorithm.Combined with conditional value at risk,the optimization decision model of charge station operators under the constraint of opportunity is constructed,and the decision model is linearized.On the basis of this decision model and the research in the previous chapter,the multi-leader-one-follower Stacklberg game model is constructed,and the solution is carried out based on the best response function,where the equilibrium of the game model is verified.Finally,the example analysis is given to verify the optimization results of the traffic system and the power system.The correctness of the model and the influences of optimizied traffic price and charging price on the charging load distribution are analyzed.By comparing and analyzing different pricing mechanisms,the effect of the cooperative optimization model and the convergence of the algorithm are proved,which offers a research foundation for the future development of the power-transportation coupling system based on shared electric vehicle fleets.