LAPSE:2018.1064
Published Article
LAPSE:2018.1064
A Multi-Period Framework for Coordinated Dispatch of Plug-in Electric Vehicles
Yinuo Huang, Chuangxin Guo, Yi Ding, Licheng Wang, Bingquan Zhu, Lizhong Xu
November 27, 2018
Coordinated dispatch of plug-in electric vehicles (PEVs) with renewable energies has been proposed in recent years. However, it is difficult to achieve effective PEV dispatch with a win-win result, which not only optimizes power system operation, but also satisfies the requirements of PEV owners. In this paper, a multi-period PEV dispatch framework, combining day-ahead dispatch with real-time dispatch, is proposed. On the one hand, the day-ahead dispatch is used to make full use of wind power and minimize the fluctuation of total power in the distribution system, and schedule the charging/discharging power of PEV stations for each period. On the other hand, the real-time dispatch arranges individual PEVs to meet the charging/discharging power demands of PEV stations given by the day-ahead dispatch. To reduce the dimensions of the resulting large-scale, non-convex problem, PEVs are clustered according to their travel information. An interval optimization model is introduced to obtain the problem solution of the day-ahead dispatch. For the real-time dispatch, a priority-ordering method is developed to satisfy the requirements of PEV owners with fast response. Numerical studies demonstrate the effectiveness of the presented framework.
Keywords
day-ahead dispatch, interval optimization, PEV-clustered model, plug-in electric vehicles (PEVs), priority-ordering method, real-time dispatch
Suggested Citation
Huang Y, Guo C, Ding Y, Wang L, Zhu B, Xu L. A Multi-Period Framework for Coordinated Dispatch of Plug-in Electric Vehicles. (2018). LAPSE:2018.1064
Author Affiliations
Huang Y: College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Guo C: College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Ding Y: College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Wang L: School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane 4067, Australia
Zhu B: State Grid Zhejiang Electric Power Company, Hangzhou 310007, China
Xu L: State Grid Zhejiang Electric Power Company, Hangzhou 310007, China
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Journal Name
Energies
Volume
9
Issue
5
Article Number
E370
Year
2016
Publication Date
2016-05-16
Published Version
ISSN
1996-1073
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PII: en9050370, Publication Type: Journal Article
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LAPSE:2018.1064
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doi:10.3390/en9050370
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Nov 27, 2018
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Nov 27, 2018
 
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Calvin Tsay
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