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ABSTRACT
ISSN: 0975-4024
Title |
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Multiobjective Optimal Placement of Public Fast Charging Station on Power Distribution Network Using Hybrid Ant Colony Optimization and Bees Algorithm |
Authors |
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Prakornchai Phonrattanasak, Nopbhorn Leeprechanon |
Keywords |
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Fast charging station, Battery electric vehicle, Ant colony optimization, Bees algorithm, Power distribution system |
Issue Date |
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Dec 2016-Jan 2017 |
Abstract |
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The multiobjective hybrid ant colony optimization (ACO) and bees algorithm (BA) is proposed to solve multiobjective optimal placement of public fast charging station (FCS) for battery electric vehicle (BEV) on power distribution system. This new algorithm is named as MOHACOBA. It is used to minimize simultaneously both total cost associated with FCS and feeder loss on distribution network under many constraints of the power distribution system and traffic condition. The IEEE-69-bus in Tianjin Development Zone is the test system for the proposed approach with three case studies on fast charging head size. In order to verify performance of algorithm, four performance metrics (Hypervolume ratio, error ratio, spread and epsilon indicator) is applied to measure quality of Pareto optimal front of proposed method and it is compared with other multiobjective optimization methods i.e. MOPSO, NSGA II and MOACO. From the results, quality of Pareto optimal front of proposed approach is better than other methods. It can be summarized that MOHACOBA algorithm has effectiveness and robustness to obtain multiobjective optimal placement of FCS on power distribution system. |
Page(s) |
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2431-2442 |
ISSN |
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0975-4024 (Online) 2319-8613 (Print) |
Source |
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Vol. 8, No.6 |
PDF |
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Download |
DOI |
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10.21817/ijet/2016/v8i6/160806405 |
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