This paper presents a planning and real-time pricing approach for EV charging stations(CSs).The approach takes the form of a bi-level model to fully consider the interest of both the government and EV charging station...This paper presents a planning and real-time pricing approach for EV charging stations(CSs).The approach takes the form of a bi-level model to fully consider the interest of both the government and EV charging station operators in the planning process.From the perspective of maximizing social welfare,the government acts as the decision-maker of the upper level that optimizes the charging price matrix,and uses it as a transfer variable to indirectly influence the decisions of the lower level operators.Then each operator at the lower level determines their scale according to the goal of maximizing their own revenue,and feeds the scale matrix back to the upper level.A Logit model is applied to predict the drivers’preference when selecting a CS.Furthermore,an improved particle swarm optimization(PSO)with the utilization of a penalty function is introduced to solve the nonlinear nonconvex bi-level model.The paper applies the proposed Bi-level planning model to a singlecenter small/medium-sized city with three scenarios to evaluate its performance,including the equipment utilization rate,payback period,traffic attraction ability,etc.The result verifies that the model performs very well in typical CS distribution scenarios with a reasonable station payback period(average 6.5 years),and relatively high equipment utilization rate,44.32%.展开更多
The construction of charging infrastructure is an important prerequisite for the development of electric vehicles （EVs）. In this paper, the classification of charging vehicle models and charging infrastructure was f...The construction of charging infrastructure is an important prerequisite for the development of electric vehicles （EVs）. In this paper, the classification of charging vehicle models and charging infrastructure was firstly summarized, and the optimal charging mode of each type of EV model and the total electicity demand of charging were then analyzed. Combined with the general principle of the development and application of new energy vehicles in the city H, the model of electric vehicle charging infrastructure planning was designed. The case we proposed fully proved the effectiveness of the model.展开更多
基金supported by the National Natural Science Foundation of China under Grant 51807024。
文摘This paper presents a planning and real-time pricing approach for EV charging stations(CSs).The approach takes the form of a bi-level model to fully consider the interest of both the government and EV charging station operators in the planning process.From the perspective of maximizing social welfare,the government acts as the decision-maker of the upper level that optimizes the charging price matrix,and uses it as a transfer variable to indirectly influence the decisions of the lower level operators.Then each operator at the lower level determines their scale according to the goal of maximizing their own revenue,and feeds the scale matrix back to the upper level.A Logit model is applied to predict the drivers’preference when selecting a CS.Furthermore,an improved particle swarm optimization(PSO)with the utilization of a penalty function is introduced to solve the nonlinear nonconvex bi-level model.The paper applies the proposed Bi-level planning model to a singlecenter small/medium-sized city with three scenarios to evaluate its performance,including the equipment utilization rate,payback period,traffic attraction ability,etc.The result verifies that the model performs very well in typical CS distribution scenarios with a reasonable station payback period(average 6.5 years),and relatively high equipment utilization rate,44.32%.
基金Supported by the 2016 Science and Technology Project of Zhejiang Electric Power Corporation(5211HZ15018V)
文摘The construction of charging infrastructure is an important prerequisite for the development of electric vehicles （EVs）. In this paper, the classification of charging vehicle models and charging infrastructure was firstly summarized, and the optimal charging mode of each type of EV model and the total electicity demand of charging were then analyzed. Combined with the general principle of the development and application of new energy vehicles in the city H, the model of electric vehicle charging infrastructure planning was designed. The case we proposed fully proved the effectiveness of the model.
