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Multi-Objective Dynamic Economic Dispatch of Microgrid Systems Including Vehicle-to-Grid

Author

Listed:
  • Haitao Liu

    (China Electric Power Research Institute, Haidian District, Beijing 100192, China)

  • Yu Ji

    (China Electric Power Research Institute, Haidian District, Beijing 100192, China)

  • Huaidong Zhuang

    (School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China)

  • Hongbin Wu

    (School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China)

Abstract

Based on the characteristics of electric vehicles (EVs), this paper establishes the load models of EVs under the autonomous charging mode and the coordinated charging and discharging mode. Integrating the EVs into a microgrid system which includes wind turbines (WTs), photovoltaic arrays (PVs), diesel engines (DEs), fuel cells (FCs) and a storage battery (BS), this paper establishes multi-objective economic dispatch models of a microgrid, including the lowest operating cost, the least carbon dioxide emissions, and the lowest pollutant treatment cost. After converting the multi-objective functions to a single objective function by using the judgment matrix method, we analyze the dynamic economic dispatch of the microgrid system including vehicle-to-grid (V2G) with an improved particle swarm optimization algorithm under different operation control strategies. With the example system, the proposed models and strategies are verified and analyzed. Simulation results show that the microgrid system with EVs under the coordinated charging and discharging mode has better operation economics than the autonomous charging mode. Meanwhile, the greater the load fluctuation is, the higher the operating cost of the microgrid system is.

Suggested Citation

  • Haitao Liu & Yu Ji & Huaidong Zhuang & Hongbin Wu, 2015. "Multi-Objective Dynamic Economic Dispatch of Microgrid Systems Including Vehicle-to-Grid," Energies, MDPI, vol. 8(5), pages 1-20, May.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:5:p:4476-4495:d:49800
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    References listed on IDEAS

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    Cited by:

    1. Xin Li & Xiaodi Zhang & Yuling Fan, 2019. "A Two-Step Framework for Energy Local Area Network Scheduling Problem with Electric Vehicles Based on Global–Local Optimization Method," Energies, MDPI, vol. 12(1), pages 1-17, January.
    2. Lizhi Zhang & Fan Li & Bo Sun & Chenghui Zhang, 2019. "Integrated Optimization Design of Combined Cooling, Heating, and Power System Coupled with Solar and Biomass Energy," Energies, MDPI, vol. 12(4), pages 1-21, February.
    3. Riccardo Iacobucci & Benjamin McLellan & Tetsuo Tezuka, 2018. "The Synergies of Shared Autonomous Electric Vehicles with Renewable Energy in a Virtual Power Plant and Microgrid," Energies, MDPI, vol. 11(8), pages 1-20, August.
    4. Asad Abbas & Saeed Mian Qaisar & Asad Waqar & Nasim Ullah & Ahmad Aziz Al Ahmadi, 2022. "Min-Max Regret-Based Approach for Sizing and Placement of DGs in Distribution System under a 24 h Load Horizon," Energies, MDPI, vol. 15(10), pages 1-32, May.
    5. Anamarija Falkoni & Antun Pfeifer & Goran Krajačić, 2020. "Vehicle-to-Grid in Standard and Fast Electric Vehicle Charging: Comparison of Renewable Energy Source Utilization and Charging Costs," Energies, MDPI, vol. 13(6), pages 1-22, March.
    6. Yuttana Kongjeen & Krischonme Bhumkittipich, 2018. "Impact of Plug-in Electric Vehicles Integrated into Power Distribution System Based on Voltage-Dependent Power Flow Analysis," Energies, MDPI, vol. 11(6), pages 1-16, June.
    7. Bingke Yan & Bo Wang & Lin Zhu & Hesen Liu & Yilu Liu & Xingpei Ji & Dichen Liu, 2015. "A Novel, Stable, and Economic Power Sharing Scheme for an Autonomous Microgrid in the Energy Internet," Energies, MDPI, vol. 8(11), pages 1-24, November.
    8. Cucchiella, Federica & D’Adamo, Idiano & Gastaldi, Massimo & Koh, SC Lenny & Rosa, Paolo, 2017. "A comparison of environmental and energetic performance of European countries: A sustainability index," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 401-413.
    9. Hui Hou & Mengya Xue & Yan Xu & Jinrui Tang & Guorong Zhu & Peng Liu & Tao Xu, 2018. "Multiobjective Joint Economic Dispatching of a Microgrid with Multiple Distributed Generation," Energies, MDPI, vol. 11(12), pages 1-19, November.
    10. Jesús Rodríguez-Molina & José-Fernán Martínez & Pedro Castillejo & Gregorio Rubio, 2017. "Development of Middleware Applied to Microgrids by Means of an Open Source Enterprise Service Bus," Energies, MDPI, vol. 10(2), pages 1-50, February.
    11. Hou, Hui & Xue, Mengya & Xu, Yan & Xiao, Zhenfeng & Deng, Xiangtian & Xu, Tao & Liu, Peng & Cui, Rongjian, 2020. "Multi-objective economic dispatch of a microgrid considering electric vehicle and transferable load," Applied Energy, Elsevier, vol. 262(C).
    12. Bin Ye & Jingjing Jiang & Lixin Miao & Peng Yang & Ji Li & Bo Shen, 2015. "Feasibility Study of a Solar-Powered Electric Vehicle Charging Station Model," Energies, MDPI, vol. 8(11), pages 1-19, November.
    13. Semaria Ruiz & Julian Patiño & Alejandro Marquez-Ruiz & Jairo Espinosa & Eduardo Duque & Paola Ortiz, 2019. "Optimal Design of a Diesel-PV-Wind-Battery-Hydro Pumped POWER system with the Integration of ELECTRIC vehicles in a Colombian Community," Energies, MDPI, vol. 12(23), pages 1-19, November.
    14. Kai Wang & Lixia Kang & Songhao Yang, 2022. "A Coordination Optimization Method for Load Shedding Considering Distribution Network Reconfiguration," Energies, MDPI, vol. 15(21), pages 1-18, November.
    15. Bhatti, Abdul Rauf & Salam, Zainal & Aziz, Mohd Junaidi Bin Abdul & Yee, Kong Pui & Ashique, Ratil H., 2016. "Electric vehicles charging using photovoltaic: Status and technological review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 34-47.

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