Capacity Evaluation of Electric Bus Load Participating in Peak Shaving of New Urban Power Grid

被引：0
|
作者：
Zhang R. [1 ]
Yu J. [1 ]
机构：
[1] School of Electrical Engineering and Automation, Harbin Institute of Technology, Heilongjiang Province, Harbin
来源：
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | 2022年 / 42卷
基金：
中国国家自然科学基金;
关键词：
electric bus; load aggregator; multi time scale; new urban power grid; peak shaving response capability;
D O I：
10.13334/j.0258-8013.pcsee.221015
中图分类号：
学科分类号：
摘要：
The new urban power grid (NUPG) under the dual carbon background needs to tap the peak shaving capacity of electric bus (EB) load (EBL) in multiple time scales. Based on the evaluation framework of EBL participating in NUPG peak shaving capability and the analysis of the response characteristics of charge or change mode, an EBL peak shaving capability evaluation model related to the resource allocation and use process in multiple time scales was constructed. For the day ahead scheduling time scale, EBL was used to make up for the capability of peak shaving and supply and demand mismatch caused by anti peak regulation factors. For the intra day pre scheduling time scale, the evaluation model of the remaining capacity of EBL after undertaking the peak shaving task and the ability to continuously respond to the peak shaving instruction was established. Focusing on the online scheduling time scale, the ability evaluation model of EBL rapid response to NUPG emergency peak shaving demand and continuous response was established, and the method of optimizing EBL peak shaving ability based on load aggregator mode was given. Finally, taking EB in a city as an example, the peak shaving capacity was evaluated based on the method. The results show that the method can quickly quantify the change trend of available peak shaving capacity related to the EBL distribution and use process at different time scales, such as day ahead, day in, online, etc., which verifies the effectiveness of the EBL peak shaving capacity evaluation model. © 2022 Chinese Society for Electrical Engineering. All rights reserved.
引用
收藏
页码：82 / 94
页数：12
相关论文
共 21 条
  • [1] HUANG Yuhan, DING Tao, LI Yuting, Decarbonization technologies and inspirations for the development of novel power systems in the context of carbon neutrality[J], Proceedings of the CSEE, 41, S1, pp. 28-51, (2021)
  • [2] Xi presided over the ninth meeting of the financial and economic commission of the CPC central committee
  • [3] HE Zhengyou, LI Bo, LIAO Kai, Key technologies for protection and control of novel urban power grids[J], Proceedings of the CSEE, 40, 19, pp. 6193-6207, (2020)
  • [4] LU Mengqian, More than 14800 electric buses have been put into operation in Guangzhou, and more than 5600 special charging piles for public transport have been built
  • [5] LI Ruixue, HU Zechun, Stochastic optimization strategy for daily operation of electric bus charging station with PV and energy storage[J], Power System Technology, 41, 12, pp. 3772-3780, (2017)
  • [6] XIAO Bai, ZHU Jiaxun, JIANG Zhuo, Planning of electric bus charging station considering vehicle charging scheduling mechanism[J], Electric Power Automation Equipment, 42, 1, pp. 148-155, (2022)
  • [7] YANG Jianwei, YANG He, ZHANG Xialin, A charging optimization strategy on charging and swapping station for electric buses based on optimization of switching rules and matching of buses and batteries[J], Proceedings of the CSEE, 39, 8, pp. 2337-2347, (2019)
  • [8] CHEN Lijuan, QIN Meng, GU Shaoping, Optimal dispatching strategy of electric bus participating in vehicle-to-grid considering battery loss[J], Automation of Electric Power Systems, 44, 11, pp. 52-60, (2020)
  • [9] ZHANG Yapeng, MU Yunfei, JIA Hongjie, Response capability evaluation model with multiple time scales for electric vehicle virtual power plant[J], Automation of Electric Power Systems, 43, 12, pp. 94-103, (2019)
  • [10] Rui XIE, Wei WEI, Qiuqei WU, Optimal service pricing and charging scheduling of an electric vehicle sharing system[J], IEEE Transactions on Vehicular Technology, 69, 1, pp. 78-89, (2020)
123