期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 14, 期 3, 页码 866-876出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2017.2748342
关键词
Data envelopment analysis (DEA); electric vehicle (EV); multistage charging facility (CF) planning; uncertainty
类别
资金
- National Natural Science Foundation of China [51507103, 51707123, 51477104]
- Natural Science Foundation of Guangdong Province [2015A030310316]
- Foundation of Shenzhen Science and Technology Committee [JCYJ20160422165525693, JCYJ20160520175515548]
- Hong Kong Polytechnic University Research Studentship
The planning of charging facilities (CFs) for electric vehicles (EVs) plays an important role for the extensive applications of EVs. Uncertainties existing in the development of future EV technology should be properly modeled to ensure the robustness of the planning scheme. The uncertainties concerned include EV development types, growth rate of load and traffic flow, and distributions of load and traffic flow in the smart grid. The existing single-stage planning model cannot fully evaluate the risks brought by all kinds of uncertainties. Given this background, the multistage CF planning problem considering uncertainties is studied in this work. First, several typical uncertainties in future smart grid with a high penetration of EVs are considered to generate development scenarios for multistage planning. Then, the well-established data envelopment analysis is utilized to evaluate the planning schemes while the novel EV expected energy not supplied cost is defined to measure the service ability of CFs. The final planning result obtained by the proposed framework will not only have good performance in the current stage but also exhibit robustness for all the considered scenarios in the future stage with respect to uncertainties. The application potential of the designed multistage planning framework is proved by an example with both the distribution network and traffic network included.
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