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Energies 2015, 8(2), 1256-1272; doi:10.3390/en8021256

Coordinated Charging Strategy for Electric Taxis in Temporal and Spatial Scale

1
National Active Distribution Network Technology Research Center (NANTEC), Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, China
2
Collaborative Innovation Center of Electric Vehicles in Beijing, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, China
*
Author to whom correspondence should be addressed.
Academic Editor: Paul Stewart
Received: 5 December 2014 / Revised: 20 January 2015 / Accepted: 29 January 2015 / Published: 5 February 2015
(This article belongs to the Special Issue Electrical Power and Energy Systems for Transportation Applications)
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Abstract

Currently, electric taxis have been deployed in many cities of China. However, the charging unbalance in both temporal and spatial scale has become a rising problem, which leads to low charging efficiency or charging congestion in different stations or time periods. This paper presents a multi-objective coordinated charging strategy for electric taxis in the temporal and spatial scale. That is, the objectives are maximizing the utilization efficiency of charging facilities, minimizing the load unbalance of the regional power system and minimizing the customers’ cost. Besides, the basic configuration of a charging station and operation rules of electric taxis would be the constraints. To tackle this multi-objective optimizing problems, a fuzzy mathematical method has been utilized to transfer the multi-objective optimization to a single optimization issue, and furthermore, the Improved Particle Swarm Optimization (IPSO) Algorithm has been used to solve the optimization problem. Moreover, simulation cases are carried out, Case 1 is the original charging procedure, and Cases 2 and 3 are the temporal and spatial scale optimized separately, followed with Case 4, the combined coordinated charging. The simulation shows the significant improvement in charging facilities efficiency and users’ benefits, as well as the better dispatching of electric taxis’ charging loads. View Full-Text
Keywords: electric taxis; temporal scale; spatial scale; particle swarm optimization electric taxis; temporal scale; spatial scale; particle swarm optimization
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Yang, Y.; Zhang, W.; Niu, L.; Jiang, J. Coordinated Charging Strategy for Electric Taxis in Temporal and Spatial Scale. Energies 2015, 8, 1256-1272.

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