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Controllability Evaluation of EV Charging Infrastructure Transformed from Gas Stations in Distribution Networks with Renewables

Author

Listed:
  • Shuang Gao

    (School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China)

  • Jianzhong Wu

    (School of Engineering, Cardiff University, Cardiff CF24 3AA, UK)

  • Bin Xu

    (State Grid Anhui Electric Power Science Research Institute, Hefei 230061, China)

Abstract

A considerable market share of electric vehicles (EVs) is expected in the near future, which leads to a transformation from gas stations to EV charging infrastructure for automobiles. EV charging stations will be integrated with the power grid to replace the fuel consumption at the gas stations for the same mobile needs. In order to evaluate the impact on distribution networks and the controllability of the charging load, the temporal and spatial distribution of the charging power is calculated by establishing mapping the relation between gas stations and charging facilities. Firstly, the arrival and parking period is quantified by applying queuing theory and defining membership function between EVs to parking lots. Secondly, the operational model of charging stations connected to the power distribution network is formulated, and the control variables and their boundaries are identified. Thirdly, an optimal control algorithm is proposed, which combines the configuration of charging stations and charging power regulation during the parking period of each individual EV. A two-stage hybrid optimization algorithm is developed to solve the reliability constrained optimal dispatch problem for EVs, with an EV aggregator installed at each charging station. Simulation results validate the proposed method in evaluating the controllability of EV charging infrastructure and the synergy effects between EV and renewable integration.

Suggested Citation

  • Shuang Gao & Jianzhong Wu & Bin Xu, 2019. "Controllability Evaluation of EV Charging Infrastructure Transformed from Gas Stations in Distribution Networks with Renewables," Energies, MDPI, vol. 12(8), pages 1-20, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:8:p:1577-:d:225937
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    References listed on IDEAS

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    1. Perez-Diaz, Alvaro & Gerding, Enrico & McGroarty, Frank, 2018. "Coordination and payment mechanisms for electric vehicle aggregators," Applied Energy, Elsevier, vol. 212(C), pages 185-195.
    2. DeForest, Nicholas & MacDonald, Jason S. & Black, Douglas R., 2018. "Day ahead optimization of an electric vehicle fleet providing ancillary services in the Los Angeles Air Force Base vehicle-to-grid demonstration," Applied Energy, Elsevier, vol. 210(C), pages 987-1001.
    3. Shafie-khah, M. & Heydarian-Forushani, E. & Golshan, M.E.H. & Siano, P. & Moghaddam, M.P. & Sheikh-El-Eslami, M.K. & Catalão, J.P.S., 2016. "Optimal trading of plug-in electric vehicle aggregation agents in a market environment for sustainability," Applied Energy, Elsevier, vol. 162(C), pages 601-612.
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