Abstract
The optimal location and size of charging stations are important considerations in relation to the large-scale application of electric vehicles (EVs). In this context, considering that charging stations are both traffic service facilities and common electric facilities, a multi-objective model is built, with the objectives of maximizing the captured traffic flow in traffic networks and minimizing the power loss in distribution networks. There are two kinds of charging stations that are considered in this paper, and the planning of EV charge stations and distribution networks is jointly modelled. The formulated multi-objective optimization problem is handled by a fuzzy membership function. The genetic algorithm (GA) is used to solve the objective function. In case studies, a 33-node distribution system and a 25-node traffic network are used to verify the effectiveness of the proposed model. The location and capacity of two kinds of charging stations are designed in the case studies, after which the impact of the battery on the captured traffic flow is analyzed as well.
Highlights
With the development of the global economy, the demand and consumption of energy in various countries have been growing steadily
The results showed that the location and the size of fast charging stations were important for reducing the electric vehicles (EVs) energy loss and station electrification cost
As the service of fast charging station (FCS) is based on a first-come first-served (FCFS) rule, the waiting time for EVs that have just arrived is determined by the mean arrival rate λPK
Summary
With the development of the global economy, the demand and consumption of energy in various countries have been growing steadily. The authors in [10] proposed an optimal control method, with centralized V2G participation in system frequency modulation, and analyzed the problem of maximizing the benefit, considering the energy constraint of the EV battery. In terms of the decentralized network access mode, a distributive autonomous strategy for frequency modulation was proposed in the work of [15] This method considered the demand of EVs and modulated the frequency according to the frequency deviations. The authors in [29] proposed a novel real-time charging control strategy for EVs, which effectively solved the problem of EVs randomly accessing the power grid.
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