Abstract
Uncoordinated charging of large-scale electric vehicles (EVs) will have a negative impact on the secure and economic operation of the power system, especially at the distribution level. Given that the charging load of EVs can be controlled to some extent, research on the optimal charging control of EVs has been extensively carried out. In this paper, two possible smart charging scenarios in China are studied: centralized optimal charging operated by an aggregator and decentralized optimal charging managed by individual users. Under the assumption that the aggregators and individual users only concern the economic benefits, new load peaks will arise under time of use (TOU) pricing which is extensively employed in China. To solve this problem, a simple incentive mechanism is proposed for centralized optimal charging while a rolling-update pricing scheme is devised for decentralized optimal charging. The original optimal charging models are modified to account for the developed schemes. Simulated tests corroborate the efficacy of optimal scheduling for charging EVs in various scenarios.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 810-819 |
| Number of pages | 10 |
| Journal | Journal of Electrical Engineering and Technology |
| Volume | 11 |
| Issue number | 4 |
| DOIs | |
| State | Published - Jul 1 2016 |
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Keywords
- Centralized optimal charging
- Decentralized optimal charging
- Electric vehicles
- Incentive
- Rolling-update price
Cite this
Optimal scheduling of electric vehicles charging in low-voltage distribution systems. / Xu, Shaolun; Zhang, Liang; Yan, Zheng; Feng, Donghan; Wang, Gang; Zhao, Xiaobo.
In: Journal of Electrical Engineering and Technology, Vol. 11, No. 4, 01.07.2016, p. 810-819.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Optimal scheduling of electric vehicles charging in low-voltage distribution systems
AU - Xu, Shaolun
AU - Zhang, Liang
AU - Yan, Zheng
AU - Feng, Donghan
AU - Wang, Gang
AU - Zhao, Xiaobo
PY - 2016/7/1
Y1 - 2016/7/1
N2 - Uncoordinated charging of large-scale electric vehicles (EVs) will have a negative impact on the secure and economic operation of the power system, especially at the distribution level. Given that the charging load of EVs can be controlled to some extent, research on the optimal charging control of EVs has been extensively carried out. In this paper, two possible smart charging scenarios in China are studied: centralized optimal charging operated by an aggregator and decentralized optimal charging managed by individual users. Under the assumption that the aggregators and individual users only concern the economic benefits, new load peaks will arise under time of use (TOU) pricing which is extensively employed in China. To solve this problem, a simple incentive mechanism is proposed for centralized optimal charging while a rolling-update pricing scheme is devised for decentralized optimal charging. The original optimal charging models are modified to account for the developed schemes. Simulated tests corroborate the efficacy of optimal scheduling for charging EVs in various scenarios.
AB - Uncoordinated charging of large-scale electric vehicles (EVs) will have a negative impact on the secure and economic operation of the power system, especially at the distribution level. Given that the charging load of EVs can be controlled to some extent, research on the optimal charging control of EVs has been extensively carried out. In this paper, two possible smart charging scenarios in China are studied: centralized optimal charging operated by an aggregator and decentralized optimal charging managed by individual users. Under the assumption that the aggregators and individual users only concern the economic benefits, new load peaks will arise under time of use (TOU) pricing which is extensively employed in China. To solve this problem, a simple incentive mechanism is proposed for centralized optimal charging while a rolling-update pricing scheme is devised for decentralized optimal charging. The original optimal charging models are modified to account for the developed schemes. Simulated tests corroborate the efficacy of optimal scheduling for charging EVs in various scenarios.
KW - Centralized optimal charging
KW - Decentralized optimal charging
KW - Electric vehicles
KW - Incentive
KW - Rolling-update price
UR - http://www.scopus.com/inward/record.url?scp=84974795043&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84974795043&partnerID=8YFLogxK
U2 - 10.5370/JEET.2016.11.4.810
DO - 10.5370/JEET.2016.11.4.810
M3 - Article
VL - 11
SP - 810
EP - 819
JO - Journal of Electrical Engineering and Technology
JF - Journal of Electrical Engineering and Technology
SN - 1975-0102
IS - 4
ER -