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An Incentive-based robust flexibility market for congestion management of an active distribution system to use the free capacity of Microgrids

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  • Babagheibi, Mahsa
  • Jadid, Shahram
  • Kazemi, Ahad

Abstract

Microgrids (MG) formation has changed the passive structure of the distribution system. MGs participate in local energy markets as separate decision-making units to optimize their economic profit by energy trading with the distribution system operator. However, in the transition-duration from passive to active configuration, the lack of sufficient infrastructure may define new challenges for distribution system security. This paper proposes a robust model of a local flexibility market to incentivize the MGs to provide flexibility services to relieve line congestion. The proposed market model is, based on a request and response structure by adopting a modified ADMM method for flexibility services negotiations. The proposed flexibility market is considered a complementary market for bilateral energy trading of MGs and a distribution system for a fairer environment. The distributed market frameworks keep data privacy and a low computational burden for the market clearing process. The IEEE 33 bus test system with four connected MGs is considered to simulate the proposed model. For results validation, the social welfare function result is compared with the centralized problem structure, and the effects of flexibility market separation are analyzed with a comparison with a security constraints-based market design.

Suggested Citation

  • Babagheibi, Mahsa & Jadid, Shahram & Kazemi, Ahad, 2023. "An Incentive-based robust flexibility market for congestion management of an active distribution system to use the free capacity of Microgrids," Applied Energy, Elsevier, vol. 336(C).
    • Handle: RePEc:eee:appene:v:336:y:2023:i:c:s0306261923001964
    DOI: 10.1016/j.apenergy.2023.120832
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    2. Mishra, Mrityunjay Kumar & Al-Sumaiti, Ameena Saad & Murari, Krishna & Parida, S.K. & Jaafari, Khaled Al, 2024. "Strategic interaction among distribution network operator and residential end-users via distribution use of system charges in demand-side management environment," Applied Energy, Elsevier, vol. 364(C).
    3. Seyed Amin Sedgh & Hossein Aghamohammadloo & Hassan Khazaei & Mehdi Mehdinejad & Somayeh Asadi, 2023. "A New Design for the Peer-to-Peer Electricity and Gas Markets Based on Robust Probabilistic Programming," Energies, MDPI, vol. 16(8), pages 1-19, April.
    4. Menghwar, Mohan & Yan, Jie & Chi, Yongning & Asim Amin, M. & Liu, Yongqian, 2024. "A market-based real-time algorithm for congestion alleviation incorporating EV demand response in active distribution networks," Applied Energy, Elsevier, vol. 356(C).
    5. Bochun Zhan & Changsen Feng & Zhemin Lin & Xiaoyu Shao & Fushuan Wen, 2023. "Peer-to-Peer Energy Trading among Prosumers with Voltage Regulation Services Provision," Energies, MDPI, vol. 16(14), pages 1-22, July.
    6. Tong, Ziqiang & Mansouri, Seyed Amir & Huang, Shoujun & Rezaee Jordehi, Ahmad & Tostado-Véliz, Marcos, 2023. "The role of smart communities integrated with renewable energy resources, smart homes and electric vehicles in providing ancillary services: A tri-stage optimization mechanism," Applied Energy, Elsevier, vol. 351(C).

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