期刊
ENERGY
卷 173, 期 -, 页码 548-553出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2019.02.015
关键词
Electric vehicle; Location; Genetic algorithm; Grey decision-making
资金
- National Natural Science Foundation of China [71503136, 71834003]
- Jiangsu Soft Science Foundation [BR2018062]
- Jiangsu Qinglan Project
- Six Talents Peaks Project in Jiangsu Province [2015-XNY-008]
- Outstanding Team Building Project for Jiangsu Philosophy and Social Science of Universities [2015ZSTD006]
- Key Projects for the Universities' Philosophy and Social Sciences in Jiangsu Province [2016ZDIXM019]
- Topnotch Academic Programs Project of Jiangsu Higher Education Institutions [PPZY2015A072]
- China Institute of Manufacturing Development [SK20180090-1#]
- Postgraduate Research & Practice Innovation of Jiangsu Province [KYCX18_1047]
the reasonable location of a charging station will promote the rapid development of the new energy automobile industry. This paper initially establishes the location model of minimizing the total social cost with the purpose of a genetic algorithm solution. Next, an evaluation index system is constructed based on five location influencing factors; land cost, construction costs, road traffic flow, power grid conditions and the surrounding environment. Numerical studies show that both grey incidence decision and grey target theory have the advantages of ease of operation, low requirement of data collection and processing when they are employed while selecting the optimal location. (C) 2019 Elsevier Ltd. All rights reserved.
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