Article
Engineering, Civil
Pengcheng You, John Z. F. Pang, Steven H. Low
Summary: This paper investigates the problem of online station assignment for commercial electric vehicles that request battery swapping, and proposes an efficient algorithm that performs well on realistic inputs.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Review
Thermodynamics
Dingsong Cui, Zhenpo Wang, Peng Liu, Shuo Wang, David G. Dorrell, Xiaohui Li, Weipeng Zhan
Summary: This paper provides a comprehensive overview of the operation optimization approaches for EV battery swapping and charging stations. It analyzes the mathematical methods used in the process and examines the current operation mode and optimization objectives. The paper also discusses the merits and drawbacks of previous studies and suggests future research opportunities.
Review
Energy & Fuels
Swapnil R. Revankar, Vaiju N. Kalkhambkar
Summary: Battery Swapping Station (BSS) offers an alternative way to charge Electric Vehicles (EVs), serving as grid scale energy storage with significant potential. It has a broad review of its relation with EVs and power grid, discussing various operations, research on grid integrated BSS, optimization strategies, case studies, as well as challenges and trends. BSS shows promise for the widespread adoption of EVs.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Energy & Fuels
Xianqiu Zhao, Yongbiao Yang, Minglei Qin, Qingshan Xu
Summary: Battery swapping station is upgraded to a battery charging and swapping station integrated with wind power, photovoltaic power, energy storage and gas turbine, creating a microgrid with enhanced flexibility. An integrated model of batteries based on the state of charge interval is introduced, simplifying the modeling process. A distributionally robust optimization model is presented to optimize the day-ahead dispatch considering uncertainties. Case studies demonstrate the effectiveness of the proposed method.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Engineering, Civil
Lili Ran, Yanni Wan, Jiahu Qin, Weiming Fu, Dunfeng Zhang, Yu Kang
Summary: It is important to develop a coordinated battery swapping station (BSS) recommendation method to reduce the cost of electric vehicles (EVs) and optimize the operation of BSS system. This paper proposes a game theory-based approach to recommend suitable BSSs for EVs by considering the battery swapping cost, diversity of BSS capacities, and differentiated demands of EVs. A price function is designed to regulate the swapping price of each BSS, and an iterative algorithm is employed to seek the Nash equilibrium. The proposed approach effectively reduces the average cost of EVs, improves the success rate of battery swapping, and balances the utilization ratio of BSSs compared to the shortest distance approach.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Yongqiang He, Yanjun Zhang, Tian Fan, Xingjuan Cai, Yubin Xu
Summary: This paper proposes a many-objective joint site selection model for battery swapping stations and battery centralized charging stations. The model considers construction cost, coverage rate, investment income, and satisfaction as objective functions, aiming to address the issue of not simultaneously considering the needs of enterprises and users in existing site selection models. A Grid-based evolutionary algorithm with a segmented integer coding strategy is utilized to solve the optimization problem. Experimental results demonstrate the reasonableness and effectiveness of the proposed model.
APPLIED INTELLIGENCE
(2023)
Article
Energy & Fuels
Mingze Zhang, Samson S. Yu, Hanlin Yu, Ping Li, Weidong Li, S. M. Muyeen
Summary: Taking the aggregator as a unit, battery swapping and charging stations (BSCSs) for electric vehicles (EVs) can be aggregated and dispatched by grid operators for demand-side resource regulation. This study proposes an optimization model to maximize the income of BSCS aggregator, which includes load planning, dispatchable capacity scheduling, and incorporates the uncertainty of EV demand. The simulations and results show that the BSCS aggregator with demand-side regulation capacity can increase its income, meet the EV swapping demand, and provide dynamic dispatchable capacity for the grid.
Article
Construction & Building Technology
Min-Der Lin, Ping-Yu Liu, Ming-Der Yang, Yu-Hao Lin
Summary: This study aims to develop an optimized allocation model to solve the problem of stochastic battery swapping demand. Through Monte Carlo simulation to predict battery swapping demand, and using optimizers to determine the best BSS locations to minimize costs.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Engineering, Civil
Haneul Ko, Sangheon Pack, Victor C. M. Leung
Summary: In this paper, an optimal battery charging algorithm is proposed for battery swapping stations to maximize net profit while maintaining high quality of service. The algorithm considers electricity price profiles and EV arrival rates to determine the optimal charging schedule. Evaluation results show a significant increase in net profit compared to price-aware schemes.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Thermodynamics
Ziqi Wang, Sizu Hou
Summary: It is important for electric vehicles (EVs) to swap their depleted batteries in the appropriate battery swapping stations due to the limited number of fully charged batteries. This study proposes a real-time optimization strategy that recommends an optimal station for EVs based on their swapping request, aiming to save time for EV owners and improve the operational efficiency and stability of battery swapping stations and the distribution network. The strategy combines rolling optimization and Lyapunov optimization from two different time scales, and achieves better results in terms of operational performance and solving speed through simulations.
Article
Energy & Fuels
Mingfei Ban, Jilai Yu, Yiyun Yao
Summary: This paper studies a battery swapping-charging system based on wind farms to address the insufficiencies in charging facilities and the reliance of electric vehicles on fossil energy. A joint optimal scheduling model is established and a heuristic method is used to solve the formulated NP-hard problem, verifying the effectiveness of the system and its potential to promote EVs and wind power.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Haifeng Wang, Hongyuan Ma, Chang Liu, Weijun Wang
Summary: An aggregate management strategy for orderly scheduling of Electric Vehicles in the battery swapping station is proposed in this study to address the issue of peak-to-valley difference in the grid, promoting wind and photovoltaic power consumption while shaving peak of the grid. The optimization model effectively realizes the orderly charging of Electric Vehicles, releases peak shaving capacity, absorbs excess wind and photovoltaic power, and reduces costs for LAs and users.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Article
Energy & Fuels
Mohamad Hasan Shaker, Hossein Farzin, Elaheh Mashhour
Summary: This paper presents a framework for optimal planning of battery swapping stations (BSS) in centralized charging mode. In this mode, the batteries are charged at a central charging station (CCS). Then they will be distributed among BSSs. Moreover, there is no charging equipment at BSSs, and depleted batteries are returned to the CCS to recharge. Firstly, a probabilistic model is developed to estimate the power consumption profile of the CCS. Then, a planning framework comprised of linear and nonlinear parts is introduced to minimize the total investment and operation costs.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Engineering, Civil
Shuai Mao, Yan Wang, Quanxue Guan, Yunjian Xu
Summary: This study addresses the joint battery charging and replenishment scheduling problem in a battery swapping charging system, taking into account random electric vehicle arrivals, renewable generation, and electricity prices. The proposed approach integrates structural properties, such as threshold-charging and least demand first structures, to reduce the dimensionality of the action space. Experimental results demonstrate that the proposed approach outperforms various structural charging and replenishment policies as well as a vanilla soft actor-critic algorithm, achieving significant cost savings of 7.16%-78.61% and 6.53%-93.73%.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Thermodynamics
Mingze Zhang, Weidong Li, Samson Shenglong Yu, Kerui Wen, Chen Zhou, Peng Shi
Summary: This paper proposes a double-stage coordinative decision-making framework for battery swapping and charging stations (BSCSs), using distributed robust optimization for multi-timescale battery inventories to maximize annual income. The framework enhances scheduling flexibility of BSCSs, improves regional load characteristics, and has been tested and verified through extensive simulation and comparison studies.
