Optimal Planning of Electric Vehicle Charging Stations Considering User Satisfaction and Charging Convenience

Abstract

To solve the problem of layout design of charging stations in the early stage of the electric vehicle industry, the user’s satisfaction and the charging convenience are considered. An electric vehicle charging station site-selection model is established based on the kernel density analysis of the urban population. The goal of this model is maximum electric vehicle user satisfaction and the highest charging convenience. Then, according to model characteristics, the immune algorithm is designed and optimized to solve the model. The optimization of the immune algorithm includes two aspects. On the one aspect, judging that the stop condition is added in the mutation link. On the other aspect, two mutation operators are designed in the optimized immune algorithm. Finally, the simulation example is determined by a three-step method in Jinan City. The results show that the electric vehicle charging station site-selection model in this paper can better meet user needs compared with traditional models. Compared with the traditional immune algorithm, the convergence speed of the optimized immune algorithm is improved, and the proposed algorithm is superior to the traditional immune algorithm in terms of stability and accuracy.

Impact of Reactive Power from Public Electric Vehicle Stations on Transformer Aging and Active Energy Losses

“…There is a large number of papers dealing with the optimal structure of EVCSs, which refers to number of charging spots, types of charging and technology of chargers themselves [53][54][55]. In this paper, the charging demand of EVCSs is obtained using the number of EVs that arrive at the EVCS during 24 h as an input.…”

Research on location selection of electric vehicle charging facilities based on hybrid algorithm

“…From an optimization perspective, existing optimal layout models for charging facilities can be categorized into three types. The first type focuses on the user's viewpoint, considering models such as minimizing electric vehicle charging costs and maximizing charging satisfaction [2,3] . The second type considers the perspective of charging station operators, with models aimed at minimizing annual operating costs [4,5] .…”

A data-driven approach of layout evaluation for electric vehicle charging infrastructure using agent-based simulation and GIS

“…3 However, the shortage and unreasonable layout of electric vehicle charging infrastructure (EVCI) have severely restricted the development of China’s new energy car industry. 4 Shenzhen, as the largest-scale and widest application of pure electric buses and taxis in China, had approximately 20,000 electric taxis (ETs) in 2019, but the ratio to the EVCI is only 1:3. Some public charging stations (CSs) have serious queuing problems due to the improper layout of public EVCI, while some other stations have low utilization rates.…”

“…12 The EV types studied in the literature include electric buses, 13 taxies, 7 private cars, 14 and trucks, 15 while most research focuses on the planning of public fast CSs in urban environments. From the perspective of operation research, the EVCI location problem can be regarded as selecting the appropriate points in the candidate set to optimize certain objectives, which usually include one or more of the following goals: (a) reducing the overall cost (e.g., constructure cost, operation cost, electricity cost, and environmental cost), 2,16 (b) increasing EV user satisfaction (service range and distance, search time, and queuing time), 4,6,9 (c) improving EVCI utilization, 17,18 and (d) optimizing power grid performance (e.g., peak-load shifting and reduction in power losses). 19,20 With the rapid development of mobile Internet, Internet of Things and Intelligent Transportation Systems, EV trajectory, traffic, and geographic information system (GIS) data have been increasingly used in the application of mathematical optimization methodologies to EVCI location problems.…”