Optimal Scheduling of Electric Vehicles Charging and Discharging Strategy Based on Real-Time Price Considering Multi-party Interest

被引:1
作者
Xie, Haixiang [1 ]
Gao, Shan [1 ]
机构
[1] Southeast Univ, Sch Elect Engn, Nanjing 214135, Peoples R China
基金
国家重点研发计划;
关键词
multiobjective optimization; distribution network operator; charging station operator; EV user; real-time price; improved sparrow search algorithm; LOAD; UNCERTAINTY;
D O I
10.1002/tee.23819
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In order to mitigate the negative impact brought by the large-scale grid connection of EVs, it is highly significant to study the optimal charging scheduling strategy of EVs. In this paper, a multiobjective optimization model of ordered charging and discharging with the participation of distribution network operator (DNO), charging station operator (CSO) and EV users is established, which maximize the interest of three parties. At the same time, the real-time price (RTP) based on the change in load rate is designed and compared with the time-of-use (TOU) price model to analyze the impact of both on the interests of all parties. At last, the sparrow search algorithm (SSA) is introduced and three improvements are made. The results demonstrate that different charging modes of EVs and charging price models will affect the balance of interests of the three parties, while the improved SSA performs better under different users' response rates. (c) 2023 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.
引用
收藏
页码:1111 / 1119
页数:9
相关论文
共 19 条
[11]   Nodal charging demand forecast of EVs considering drivers' psychological bearing ability based on NMC-MCS [J].
Ma, Qiao ;
Tong, Xiangqian ;
Huang, Jingjing ;
Wang, Peng ;
Li, Junhuai .
IET GENERATION TRANSMISSION & DISTRIBUTION, 2022, 16 (03) :467-478
[12]   Multi-Objective Optimization of Combined Heat and Power Industrial Microgrid [J].
Mehrabadi, Elham Sheikhi ;
Sathiakumar, Swamidoss .
JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME, 2020, 142 (05)
[13]   Multi-objective optimal scheduling of microgrid with electric vehicles [J].
Mei, Yu ;
Li, Bin ;
Wang, Honglei ;
Wang, Xiaolin ;
Negnevitsky, Michael .
ENERGY REPORTS, 2022, 8 :4512-4524
[14]   Balanced charging strategies for electric vehicles on power systems [J].
Moon, Sang-Keun ;
Kim, Jin-O .
APPLIED ENERGY, 2017, 189 :44-54
[15]   A Chaos Sparrow Search Algorithm with Logarithmic Spiral and Adaptive Step for Engineering Problems [J].
Tang, Andi ;
Zhou, Huan ;
Han, Tong ;
Xie, Lei .
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES, 2022, 130 (01) :331-364
[16]   Optimal scheduling of electric vehicles charging in battery swapping station considering wind- photovoltaic accommodation [J].
Wang, Haifeng ;
Ma, Hongyuan ;
Liu, Chang ;
Wang, Weijun .
ELECTRIC POWER SYSTEMS RESEARCH, 2021, 199
[17]   A model predictive control approach in microgrid considering multi-uncertainty of electric vehicles [J].
Wu, Chuanshen ;
Gao, Shan ;
Liu, Yu ;
Song, Tiancheng E. ;
Han, Haiteng .
RENEWABLE ENERGY, 2021, 163 :1385-1396
[18]   A bi-level optimization model for electric vehicle charging strategy based on regional grid load following [J].
Yang, Xiaolong ;
Niu, Dongxiao ;
Sun, Lijie ;
Ji, Zhengsen ;
Zhou, Jiancheng ;
Wang, Keke ;
Siqin, Zhuoya .
JOURNAL OF CLEANER PRODUCTION, 2021, 325
[19]   Coordinated control for voltage regulation of distribution network voltage regulation by distributed energy storage systems [J].
Zhang D. ;
Li J. ;
Hui D. .
Protection and Control of Modern Power Systems, 2018, 3 (01)