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Strategic charging method for plugged in hybrid electric vehicles in smart grids; A game theoretic approach

Sheikhi, A ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1016/j.ijepes.2013.04.025
  3. Publisher: 2013
  4. Abstract:
  5. Implementation of various incentive-based and time-based load management strategies has great potential to decrease peak load growth and customer electricity bill cost. In recent years, developments in Plug in Hybrid Electric Vehicles (PHEVs) have provided various environmental and economic advantages. However, high penetration of electric vehicles in to the grid may cause high peak loads at different times of the days. Using advanced metering and automatic chargers makes it possible to optimize the charging cost, and release generation capacities to provide sustainable electricity supply. Using an appropriate encouraging program is a simple way for vehicle owners to manage their energy consumption and shift the time of charging to proper time of the day; and therefore, to reduce their electricity bill. With these objectives, this paper proposes a new practical PHEVs' charging scheduling programs aiming at optimizing customers charging cost by considering the generation capacity limitation and dynamic electricity price in different time slots of a day. Using a stochastic model for start time of charging and the duration of it in the proposed optimization algorithm, make this method a practical tool for modeling the vehicle owners' charging behavior with the purpose of peak load shaving
  6. Keywords:
  7. Charging scheduling ; Load management ; Peak load shaving ; Smart meter ; Automatic chargers ; Economic advantages ; Generation capacity ; Load management strategies ; Optimization algorithms ; Peak load ; Plug in hybrid electric vehicles ; Scheduling programs ; Algorithms ; Electric load management ; Electric vehicles ; Electricity ; Energy utilization ; Game theory ; Hybrid vehicles ; Optimization ; Scheduling ; Secondary batteries ; Smart meters ; Smart power grids ; Costs
  8. Source: International Journal of Electrical Power and Energy Systems ; Volume 53, Issue 1 , December , 2013 , Pages 499-506 ; 01420615 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S0142061513002147