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CVaR-Constrained Optimal Bidding of Electric Vehicle Aggregators in Day-Ahead and Real-Time Markets

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成果类型:
期刊论文
作者:
Yang, Hongming;Zhang, Sanhua;Qiu, Jing*;Qiu, Duo;Lai, Mingyong;...
通讯作者:
Qiu, Jing
作者机构:
[Zhang, Sanhua; Yang, Hongming; Dong, ZhaoYang; Qiu, Duo; Lai, Mingyong] Changsha Univ Sci & Technol, Hunan Prov Engn Res Ctr Elect Transportat, Sch Elect & Informat Engn, Changsha 410114, Hunan, Peoples R China.
[Zhang, Sanhua; Yang, Hongming; Dong, ZhaoYang; Qiu, Duo; Lai, Mingyong] Changsha Univ Sci & Technol, Smart Distribut Network, Sch Elect & Informat Engn, Hunan Prov Key Lab Smart Grids Operat & Control, Changsha 410114, Hunan, Peoples R China.
[Qiu, Jing] CSIRO, Mayfield West, NSW 2304, Australia.
[Dong, ZhaoYang] Univ Sydney, Sch Elect & Informat Engn, Sydney, NSW, Australia.
通讯机构:
[Qiu, Jing] C
CSIRO, Mayfield West, NSW 2304, Australia.
语种:
英文
关键词:
Bidding strategy;conditional value-at-risk (CVaR);day-ahead and real-time markets;electric vehicle aggregators
期刊:
IEEE Transactions on Industrial Informatics
ISSN:
1551-3203
年:
2017
卷:
13
期:
5
页码:
2555-2565
基金类别:
Manuscript received July 20, 2016; revised October 29, 2016 and December 20, 2016; accepted January 27, 2017. Date of publication February 1, 2017; date of current version October 3, 2017. This work was supported in part by the National Natural Science Foundation of China under Grant 71331001, Grant 71420107027, and Grant 91547113, in part by the Science and Technology Projects of Hunan Province and Changsha City (2016WK2015, kh1601186), and in part by the Science and Technology projects of China Southern Power Grid under Grant WYKJ00000027. Paper no. TII-16-0727. (Corresponding author: J. Qiu.) H. Yang, S. Zhang, D. Qiu, and M. Lai are with the Hunan Provincial Engineering Research Center of Electric Transportation and Smart Distribution Network, Hunan Provincial Key Laboratory of Smart Grids Operation and Control, School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China (e-mail: yhm5218@hotmail.com; zshwts10@163.com; qiuduoduo13@hnu.edu.cn; laimingyong0731@hotmail.com).
机构署名:
本校为第一机构
院系归属:
电气与信息工程学院
摘要:
An electric vehicle aggregator (EVA) that manages geographically dispersed electric vehicles offers an opportunity for the demand side to participate in electricity markets. This paper proposes an optimization model to determine the day-ahead inflexible bidding and real-time flexible bidding under market uncertainties. Based on the relationship between market price and bid price, the proposed optimal bidding model of EVA aims to minimize the conditional expectation of electricity purchase cost in two markets considering price volatility. Moreover, the penalty cost of the deviation between the ...

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