Competition Map Based Demand Response Strategy of Charging Station for Electric Logistics Vehicles

被引：0

作者：

Tang D. ^{[1
]}

Ni P. ^{[1
]}

Hu Z. ^{[1
]}

Tang Z. ^{[2
]}

Liu Y. ^{[2
]}

Ou Y. ^{[1
]}

机构：

[1] Aostar Information Technology Co., Ltd., Chengdu

[2] School of Electrical Engineering, Sichuan University, Chengdu

来源：

Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2021年 / 45卷 / 21期

关键词：

Charging station; Competition map; Demand response; Electric logistics vehicle (ELV);

D O I：

10.7500/AEPS20210420005

中图分类号：

学科分类号：

摘要：

In view of the current situation that charging stations for electric logistics vehicles (ELVs) in some cities of China have difficulties in carrying out demand response, a competition map based demand response strategy of charging stations for ELVs is proposed. Firstly, a classification method for ELVs is constructed, and the characteristics of ELV users are analyzed according to the charging temporal-spatial characteristics and charging price curve of ELVs, etc. On this basis, the charging very important person (VIP) system for ELV users is constructed based on the competition map, and the incentive mechanism for ELV users to participate in demand response is formed. Secondly, considering the energy storage, electricity price and other factors of the ELV charging station, the demand response strategy of the ELV charging station is constructed, so as to reduce the impact of disorderly charging of the ELVs on the charging station participating in demand response. Finally, the economy of the proposed strategy is compared with that of the Monte Carlo demand response strategy through an example analysis, and results verify the effectiveness and practicability of the proposed demand response strategy. © 2021 Automation of Electric Power Systems Press.

引用

页码：189 / 196

页数：7

共 27 条

[1]

SUN Xiuyan, Carbon reduction, China sets hard targets (beautiful China), People's Daily

[2]

ZHUANG Weichao, QU Linghu, XU Shaobing, Et al., Integrated energy-oriented cruising control of electric vehicle on highway with varying slopes considering battery aging, Science China Technological Sciences, 63, 1, pp. 155-165, (2020)

[3]

YIN Zeyi, WANG Guangzhu, CHENG Zhenxing, Charge control strategy of plug-in hybrid electric vehicle system based on modular multilevel converter, Transactions of China Electrotechnical Society, 35, 6, pp. 1316-1326, (2020)

[4]

CHAUDHARI K, UKIL A, KUMAR K N, Et al., Hybrid optimization for economic deployment of ESS in PV integrated ELV charging station, IEEE Transactions on Industrial Informatics, 14, 1, pp. 106-116, (2018)

[5]

YAO Jianguo, ZHANG Kaifeng, DING Zhetong, Et al., Concept extension and research focus of dynamic demand response, Automation of Electric Power Systems, 43, 14, pp. 207-215, (2019)

[6]

WANG Yi, GU Yi, DING Zhuang, Et al., Charging demand forecasting of electric vehicle based on empirical mode decomposition-fuzzy entropy and ensemble learning, Automation of Electric Power Systems, 44, 3, pp. 114-121, (2020)

[7]

SIMORGH H, DOAGOU-MOJARRAD H, RAZMI H, Et al., Cost-based optimal siting and sizing of electric vehicle charging stations considering demand response programmes, IET Generation, Transmission & Distribution, 12, 8, pp. 1712-1720, (2018)

[8]

CHU C C, XIONG Yingqi, WANG Bin, Et al., Vehicle grid integration for demand response with mixture user model and decentralized optimization, Applied Energy, 231, pp. 481-493, (2018)

[9]

TANG Jia, WANG Dan, JIA Hongjie, Et al., A study of V2G control strategies of aggregated electric vehicles for real-time demand response based on hysteresis model, Power System Technology, 41, 7, pp. 55-60, (2017)

[10]

ZENG Ming, ZHANG Ping, LONG Zhuhan, Et al., Control strategy of electric vehicle participating in demand side response for micro-grid operators, Electric Power Construction, 39, 3, pp. 108-115, (2018)

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