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Exploration of dispatch model integrating wind generators and electric vehicles

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  • Haque, A.N.M.M.
  • Ibn Saif, A.U.N.
  • Nguyen, P.H.
  • Torbaghan, S.S.

Abstract

In recent years, the share of renewable energy sources (RES) in the electricity generation mix has been expanding rapidly. However, limited predictability of the RES poses challenges for traditional scheduling and dispatching mechanisms based on unit commitment (UC) and economic dispatch (ED). This paper presents an advanced UC-ED model to incorporate wind generators as RES-based units alongside conventional centralized generators. In the proposed UC-ED model, an imbalance cost is introduced reflecting the wind generation uncertainty along with the marginal generation cost. The proposed UC-ED model aims to utilize the flexibility of fleets of plug-in electric vehicles (PEVs) to optimally compensate for the wind generation uncertainty. A case study with 15 conventional units and 3 wind farms along with a fixed-sized PEV fleet demonstrates that shifting of PEV fleets charging at times of high wind availability realizes generation cost savings. Nevertheless, the operational cost saving incurred by controlled charging appears to diminish when dispatched wind energy becomes considerably larger than the charging energy of PEV fleets. Further analysis of the results reveals that the effectiveness of PEV control strategy in terms of CO2 emission reduction is strongly coupled with generation mix and the proposed control strategy is favored in cases where less pollutant-based plants like nuclear and hydro power are profoundly dominant.

Suggested Citation

  • Haque, A.N.M.M. & Ibn Saif, A.U.N. & Nguyen, P.H. & Torbaghan, S.S., 2016. "Exploration of dispatch model integrating wind generators and electric vehicles," Applied Energy, Elsevier, vol. 183(C), pages 1441-1451.
    • Handle: RePEc:eee:appene:v:183:y:2016:i:c:p:1441-1451
    DOI: 10.1016/j.apenergy.2016.09.078
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    References listed on IDEAS

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    2. Boyang Qu & Baihao Qiao & Yongsheng Zhu & Jingjing Liang & Ling Wang, 2017. "Dynamic Power Dispatch Considering Electric Vehicles and Wind Power Using Decomposition Based Multi-Objective Evolutionary Algorithm," Energies, MDPI, vol. 10(12), pages 1-28, December.
    3. Abbasi, Mohammad Hossein & Taki, Mehrdad & Rajabi, Amin & Li, Li & Zhang, Jiangfeng, 2019. "Coordinated operation of electric vehicle charging and wind power generation as a virtual power plant: A multi-stage risk constrained approach," Applied Energy, Elsevier, vol. 239(C), pages 1294-1307.
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    5. Panagiotis Adraktas & Athanasios Dagoumas, 2019. "Integration of Electric Vehicles in the Unit Commitment Problem with Uncertain Renewable Electricity Generation," International Journal of Energy Economics and Policy, Econjournals, vol. 9(2), pages 315-333.
    6. Wang, Haibing & Zheng, Tianhang & Sun, Weiqing & Khan, Muhammad Qasim, 2023. "Research on the pricing strategy of park electric vehicle agent considering carbon trading," Applied Energy, Elsevier, vol. 340(C).
    7. Yang, Linfeng & Zhang, Chen & Jian, Jinbao & Meng, Ke & Xu, Yan & Dong, Zhaoyang, 2017. "A novel projected two-binary-variable formulation for unit commitment in power systems," Applied Energy, Elsevier, vol. 187(C), pages 732-745.
    8. Mehrdad Tarafdar-Hagh & Kamran Taghizad-Tavana & Mohsen Ghanbari-Ghalehjoughi & Sayyad Nojavan & Parisa Jafari & Amin Mohammadpour Shotorbani, 2023. "Optimizing Electric Vehicle Operations for a Smart Environment: A Comprehensive Review," Energies, MDPI, vol. 16(11), pages 1-21, May.
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