Multi-Area Self-Adaptive Pricing Control in Smart City With EV User Participation
Promoting the market of electric vehicles (EV) can be one of the most effective ways to deal with the increasing severity of air pollution. However, the behavior of EV users can be rather stochastic and the aggregated charging power may add pressure to urban power grid during peak hours. In this paper, a novel smart city modeling with combined EV traveling and charging network is formulated. To alleviate the potential contingency brought by stochastic EV charging, mandatory control from grid operator and different kinds of electricity pricing schemes are introduced. Finally, the comparison between existing EV charging control schemes and multi-area self-adaptive (MASA) pricing control is performed to point out the limitation of passive control imposed on users as well as the flexibility of MASA pricing scheme. The results demonstrate that MASA pricing with active EV participation serves as an effective and economical solution to the future smart city under complex transportation network and massive EV integration.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
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Supplemental Notes:
- Copyright © 2018, IEEE.
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Authors:
- Nie, Yongquan
- Wang, Xiaolin
- Cheng, Ka-Wai Eric
- Publication Date: 2018-7
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: pp 2156-2164
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Serial:
- IEEE Transactions on Intelligent Transportation Systems
- Volume: 19
- Issue Number: 7
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- ISSN: 1524-9050
- Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979
Subject/Index Terms
- TRT Terms: Consumer behavior; Control; Electric vehicle charging; Electric vehicles; Grids (Transmission lines); Optimization; Pricing; Traffic congestion; Urban transportation
- Uncontrolled Terms: Smart cities
- Subject Areas: Energy; Highways; Planning and Forecasting; Vehicles and Equipment;
Filing Info
- Accession Number: 01676882
- Record Type: Publication
- Files: TLIB, TRIS
- Created Date: Jul 27 2018 1:24PM