DocumentCode :
666068
Title :
Optimal electric vehicle charging stations placement in distribution systems
Author :
Chun-Lien Su ; Rong-Ceng Leou ; Jun-Chang Yang ; Chan-Nan Lu
Author_Institution :
Dept. of Marine Eng., Nat. Kaohsiung Marine Univ., Kaohsiung, Taiwan
fYear :
2013
fDate :
10-13 Nov. 2013
Firstpage :
2121
Lastpage :
2126
Abstract :
This paper presents an algorithm dedicated to the electric vehicles (EVs) charging stations placement optimization in a given distribution system using genetic algorithms (GA), where daily time varying loads are considered together with random EVs charging patterns including starting time, duration, and power of charging. The problem is formulated as a non-differential combinational optimization problem, where the system losses to be minimized subject to capacity and system operation constraints. The placement alternatives considered are the installation of Level 2 single-phase slow chargers. In the GA evolutionary process, all individuals´ fitness is analyzed and for each feasible solution, a non-linear three phase power flow problem is solved and the system losses are calculated. A practical distribution system composed of 20 buses was used to validate the algorithm and demonstrate its applicability to large systems.
Keywords :
combinatorial mathematics; distribution networks; electric vehicles; genetic algorithms; load flow; 20 buses; EV charging stations placement optimization; distribution systems; genetic algorithms; level 2 single-phase slow chargers; nondifferential combinational optimization problem; nonlinear three phase power flow problem; optimal electric vehicle charging stations placement; random EV charging patterns; system operation constraints; the GA evolutionary process; Biological cells; Electric vehicles; Genetic algorithms; Load flow; Mathematical model; Optimization; Time measurement; Charging stations; Electric vehicles; Impact study; Placement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
Conference_Location :
Vienna
ISSN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2013.6699459
Filename :
6699459
Link To Document :
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