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Shadow price based co-ordination methods of microgrids and battery swapping stations

Author

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  • Wang, Yang
  • Lai, Kexing
  • Chen, Fengyun
  • Li, Zhengming
  • Hu, Chunhua

Abstract

The growing market share of electric vehicles embodies the remarkable progress of transportation electrification. Battery swapping station serves as a critical infrastructure for efficient electric vehicles refueling. To coordinate the scheduling of a battery swapping station and a microgrid managed by non-cooperative entities, we develop two shadow price-based coordination methods, namely peer-to-peer method and leader-follower method. The context is of great importance for mitigating potential barriers of integration of battery swapping stations and microgrids. The peer-to-peer method only requires the exchange of individual shadow price and power trading requests between two entities. This mechanism is the first-of-its-kind solution that allows for co-ordination between two systems without releasing proprietary information. An iterative heuristic algorithm is developed to obtain outcomes of the co-ordination mechanism. For the leader-follower method, microgrid entity gets access to proprietary information of battery swapping station that is managed by an independent entity. A bi-level optimization model is developed to model the gameplay between two non-corporative entities, which is solved by a modified nested column-and-constraint generation algorithm. For both methods, we use an AC optimal power flow model to optimize operation of microgrid while battery swapping station operation is determined by a mixed-integer linear programming model. This work is also the first-of-its-kind study that incorporates AC power flow equations into relevant research. We demonstrate the effectiveness of both methods using an integrated system comprising a standard IEEE 33-bus system and a battery swapping station serving multiple private electric sedans or public electric buses. Nearly 10% of total operational cost saving can be attained if the proposed methods are applied for coordinating two systems, compared to implementing a baseline method.

Suggested Citation

  • Wang, Yang & Lai, Kexing & Chen, Fengyun & Li, Zhengming & Hu, Chunhua, 2019. "Shadow price based co-ordination methods of microgrids and battery swapping stations," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    • Handle: RePEc:eee:appene:v:253:y:2019:i:c:104
    DOI: 10.1016/j.apenergy.2019.113510
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    References listed on IDEAS

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    Cited by:

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    4. Tushar, Wayes & Yuen, Chau & Saha, Tapan K. & Morstyn, Thomas & Chapman, Archie C. & Alam, M. Jan E. & Hanif, Sarmad & Poor, H. Vincent, 2021. "Peer-to-peer energy systems for connected communities: A review of recent advances and emerging challenges," Applied Energy, Elsevier, vol. 282(PA).
    5. Cui, Dingsong & Wang, Zhenpo & Liu, Peng & Wang, Shuo & Dorrell, David G. & Li, Xiaohui & Zhan, Weipeng, 2023. "Operation optimization approaches of electric vehicle battery swapping and charging station: A literature review," Energy, Elsevier, vol. 263(PE).
    6. Vinyals, Meritxell, 2021. "Scalable multi-agent local energy trading — Meeting regulatory compliance and validation in the Cardiff grid," Applied Energy, Elsevier, vol. 298(C).
    7. Yang Wang & Yifan Wang & Zhenghui Zhao & Zhiquan Zhou & Zhihao Hou, 2023. "Multi-Timescale Optimal Operation Strategy for Renewable Energy Power Systems Based on Inertia Evaluation," Energies, MDPI, vol. 16(8), pages 1-15, April.
    8. Feng, Jiawei & Hou, Shengya & Yu, Lijun & Dimov, Nikolay & Zheng, Pei & Wang, Chunping, 2020. "Optimization of photovoltaic battery swapping station based on weather/traffic forecasts and speed variable charging," Applied Energy, Elsevier, vol. 264(C).
    9. Ahmadi Jirdehi, Mehdi & Sohrabi Tabar, Vahid, 2023. "Risk-aware energy management of a microgrid integrated with battery charging and swapping stations in the presence of renewable resources high penetration, crypto-currency miners and responsive loads," Energy, Elsevier, vol. 263(PA).

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