4.8 Article

Balancing Power Demand Through EV Mobility in Vehicle-to-Grid Mobile Energy Networks

Journal

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
Volume 12, Issue 1, Pages 79-90

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2015.2494884

Keywords

Demand response management (DRM); electric vehicle (EV) mobility; smart grid; vehicle-to-grid (V2G); V2G mobile energy network

Funding

  1. Natural Science Foundation of China (NSFC) [61422201, 61370159, U1201253, U1301255]
  2. Guangdong Province Natural Science Foundation [S2011030002886]
  3. Special Support Project of Guangdong Province [2014TQ01X100]
  4. High Education Excellent Young Teacher Program of Guangdong Province [YQ2013057]
  5. Science and Technology Program of Guangzhou [2014J2200097]
  6. Research Council of Norway [240079/F20]
  7. European Commission [PIRSES-GA-2013-627490]
  8. Energy Innovation Research Programme (EIRP), Singapore [NRF2012EWT-EIRP002-045]

Ask authors/readers for more resources

Vehicle-to-grid (V2G) technology enables bidirectional energy flow between electric vehicles (EVs) and power grid, which provides flexible demand response management (DRM) for the reliability of smart grid. EV mobility is a unique and inherent feature of the V2G system. However, the inter-relationship between EV mobility and DRM is not obvious. In this paper, we focus on the exploration of EV mobility to impact DRM in V2G systems in smart grid. We first present a dynamic complex network model of V2G mobile energy networks, considering the fact that EVs travel across multiple districts, and hence EVs can be acting as energy transporters among different districts. We formulate the districts' DRM dynamics, which is coupled with each other through EV fleets. In addition, a complex network synchronization method is proposed to analyze the dynamic behavior in V2G mobile energy networks. Numerical results show that EVs mobility of symmetrical EV fleet is able to achieve synchronous stability of network and balance the power demand among different districts. This observation is also validated by simulation with real world data.

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