DocumentCode :
78626
Title :
Optimal Use of Existing Distribution Feeders to Accommodate Transportation Electrification
Author :
Chieh-Min Chan ; Chan-Nan Lu ; Yuan Liang Lo
Author_Institution :
Formosa Petrochem. Corp., Mailiao, Taiwan
Volume :
16
Issue :
4
fYear :
2015
fDate :
Aug. 2015
Firstpage :
1941
Lastpage :
1950
Abstract :
An analytical method that can be used to study the optimal topology and maximum capacity of the existing distribution network to accommodate electric vehicle (EV) charging demands is presented in this paper. In order to facilitate a large number of EV integrations, the feeder reconfiguration problem is formulated as a discrete nonlinear optimization problem that finds optimal feeders´ tie switch locations and their on/off schedule to minimize operation costs and comply with the system operation constraints. A novel stochastic dynamic programming technique is adopted to solve the problem that includes various uncertainties associated with feeder baseline and EV charging loads. Simulation results obtained from an 84-bus feeder test system have indicated that for a case with 20% EV penetration to a 70% capacity utilization feeder area, a 10.78% reduction of operation cost and a 14.4% decrease in maximum feeder utilization can be obtained by distribution feeder reconfiguration.
Keywords :
distribution networks; electric vehicles; EV integrations; discrete nonlinear optimization problem; distribution feeders; distribution network; electric vehicle charging demands; feeder reconfiguration problem; transportation electrification; Batteries; Load modeling; Monte Carlo methods; Stochastic processes; Switches; System-on-chip; Transportation; Distribution system operation and planning; electric vehicle (EV); feeder reconfiguration; smart grid; stochastic dynamic programming (SDP); transportation electrification;
fLanguage :
English
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1524-9050
Type :
jour
DOI :
10.1109/TITS.2014.2385799
Filename :
7047852
Link To Document :
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