DocumentCode :
108370
Title :
Adaptive Electric Vehicle Charging Coordination on Distribution Network
Author :
Lunci Hua ; Jia Wang ; Chi Zhou
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA
Volume :
5
Issue :
6
fYear :
2014
fDate :
Nov. 2014
Firstpage :
2666
Lastpage :
2675
Abstract :
Electric vehicles (EVs) with large battery charging demands may cause detrimental impact on distribution grid stability without EV charging coordination. This paper proposes an on-line adaptive EV charing scheduling (OACS) framework to optimize EV charging schedules and reduce flow limit, voltage magnitude limit, 3-phase voltage imbalance limit, and transformer capacity violations. EV user convenience is considered and EV charging cost is optimized. DC power flow based optimizations is proposed for EV charging scheduling approximation and parallel ac power flow verification is used to verify the scheduling results. Incremental feasibility improvement procedure is further proposed to correct the scheduling discrepancy between dc linear model and the ac model. Experiments are performed on a modified IEEE 34 14.7 kV distribution system with different EV penetration levels to demonstrate performance comparisons between different scheduling schemes. The result shows that our proposed OACS framework optimizes the EV charging coordination problem efficiently.
Keywords :
approximation theory; cost reduction; electric vehicles; load flow; optimisation; power distribution economics; power system stability; secondary cells; smart power grids; 3-phase voltage imbalance limit reduction; AC model; DC linear model; DC power flow based optimizations; EV charging cost optimization; EV charging schedule optimization; EV charging scheduling approximation; IEEE 34 distribution system; OACS framework; adaptive electric vehicle charging coordination; battery charging demands; detrimental impact; distribution grid stability; distribution network; flow limit reduction; online adaptive EV charing scheduling framework; parallel AC power flow verification; transformer capacity violation reduction; voltage 14.7 kV; voltage magnitude limit reduction; Approximation methods; Electric vehicles; Load modeling; Optimization; Real-time systems; Scheduling; Demand coordination; distribution grid; electric vehicle (EV); optimization model; smart grid;
fLanguage :
English
Journal_Title :
Smart Grid, IEEE Transactions on
Publisher :
ieee
ISSN :
1949-3053
Type :
jour
DOI :
10.1109/TSG.2014.2336623
Filename :
6863680
Link To Document :
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