- Title
- A multi-objective collaborative planning strategy for integrated power distribution and electric vehicle charging systems
- Creator
- Yao, Weifeng; Zhao, Junhua; Wen, Fushuan; Dong, Zhaoyang; Xue, Yusheng; Xu, Yan; Meng, Ke
- Relation
- IEEE Transactions on Power Systems Vol. 29, Issue 4, p. 1811-1821
- Publisher Link
- http://dx.doi.org/10.1109/TPWRS.2013.2296615
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- journal article
- Date
- 2014
- Description
- An elaborately designed integrated power distribution and electric vehicle (EV) charging system will not only reduce the investment and operation cost of the system concerned, but also promote the popularization of environmentally friendly EVs. In this context, a multi-objective collaborative planning strategy is presented to deal with the optimal planning issue in integrated power distribution and EV charging systems. In the developed model, the overall annual cost of investment and energy losses is minimized simultaneously with the maximization of the annual traffic flow captured by fast charging stations (FCSs). Additionally, the user equilibrium based traffic assignment model (UETAM) is integrated to address the maximal traffic flow capturing problem. Subsequently, a decomposition based multi-objective evolutionary algorithm (MOEA/D) is employed to seek the non-dominated solutions, i.e., the Pareto frontier. Finally, collaborative planning results of two coupled distribution and transportation systems are presented to illustrate the performance of the proposed model and solution method.
- Subject
- Collaborative planning; Pareto frontier; decomposition based multi-objective evolutionary algorithm; distribution system; electric vehicles
- Identifier
- http://hdl.handle.net/1959.13/1067678
- Identifier
- uon:18457
- Identifier
- ISSN:0885-8950
- Language
- eng
- Reviewed
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