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Energy management of grid-interconnected multi-microgrids based on adjustable power and greenhouse gas credits

Author

Listed:
  • Mohan, Anjali
  • Thirumala, Karthik
  • Prakash, J. Jude
  • Ilango, G. Saravana

Abstract

This paper presents a novel hierarchical energy management system (EMS) to minimise the operational greenhouse gas (GHG) emission of grid interconnected multi-microgrid (IMMG) systems. The peer-to-peer energy trading strategy (ETS) integrated optimisation is implemented with three levels for the IMMG test system: MGs, the utility grid, and community power distribution agents (CPDAs). The ETS employs the “adjustable power” concept to harness the underutilised controllable DGs by considering the per-unit emission of the DGs involved. Further, “GHG credits”, inspired by the carbon markets prevalent in European nations, are introduced in the ETS. This serves as an offset for the GHG emissions produced or as an incentive. The three levels of the proposed EMS approach include local optimisation at the MG level, followed by ETS-integrated global optimisation at the IMMG level, and lastly, settlement of GHG credits using the Bid-based Hamilton Allocation approach. A comparative study using two alternative approaches validates the efficacy, robustness, and scalability of the proposed approach in promoting environmental sustainability and improving decarbonisation of the network. Furthermore, two other recent and widely adopted ETS approaches are implemented on the test IMMG system, and a comparative analysis further highlights the superior performance of the novel ETS-integrated EMS approach.

Suggested Citation

  • Mohan, Anjali & Thirumala, Karthik & Prakash, J. Jude & Ilango, G. Saravana, 2026. "Energy management of grid-interconnected multi-microgrids based on adjustable power and greenhouse gas credits," Renewable Energy, Elsevier, vol. 256(PE).
    • Handle: RePEc:eee:renene:v:256:y:2026:i:pe:s0960148125018440
    DOI: 10.1016/j.renene.2025.124180
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    References listed on IDEAS

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    1. Bian, Yifan & Xie, Lirong & Ma, Lan & Cui, Chuanshi, 2025. "A novel two-stage energy sharing model for data center cluster considering integrated demand response of multiple loads," Applied Energy, Elsevier, vol. 384(C).
    2. Philippe Delacote & Tara L’Horty & Andreas Kontoleon & Thales A. P. West & Anna Creti & Ben Filewod & Gwenole LeVelly & Alejandro Guizar-Coutiño & Ben Groom & Micah Elias, 2024. "Strong transparency required for carbon credit mechanisms," Nature Sustainability, Nature, vol. 7(6), pages 706-713, June.
    3. Moghaddam, Amjad Anvari & Seifi, Alireza & Niknam, Taher & Alizadeh Pahlavani, Mohammad Reza, 2011. "Multi-objective operation management of a renewable MG (micro-grid) with back-up micro-turbine/fuel cell/battery hybrid power source," Energy, Elsevier, vol. 36(11), pages 6490-6507.
    4. Joanna Sitarz & Michael Pahle & Sebastian Osorio & Gunnar Luderer & Robert Pietzcker, 2024. "Policy credibility is a key component for an effective and efficient EU Emissions Trading System," Nature Energy, Nature, vol. 9(6), pages 637-638, June.
    5. Zhong, Xiaoqing & Zhong, Weifeng & Liu, Yi & Yang, Chao & Xie, Shengli, 2022. "Optimal energy management for multi-energy multi-microgrid networks considering carbon emission limitations," Energy, Elsevier, vol. 246(C).
    6. Wu, Chun & Chen, Xingying & Hua, Haochen & Yu, Kun & Gan, Lei & Shen, Jun & Ding, Yi, 2024. "Peer-to-peer energy trading optimization for community prosumers considering carbon cap-and-trade," Applied Energy, Elsevier, vol. 358(C).
    7. Luc Lauwers & Tom Van Puyenbroeck, 2006. "The Hamilton Apportionment Method Is Between the Adams Method and the Jefferson Method," Mathematics of Operations Research, INFORMS, vol. 31(2), pages 390-397, May.
    8. Rezaei, Navid & Pezhmani, Yasin & Khazali, Amirhossein, 2022. "Economic-environmental risk-averse optimal heat and power energy management of a grid-connected multi microgrid system considering demand response and bidding strategy," Energy, Elsevier, vol. 240(C).
    9. Ou, Xunmin & Xiaoyu, Yan & Zhang, Xiliang, 2011. "Life-cycle energy consumption and greenhouse gas emissions for electricity generation and supply in China," Applied Energy, Elsevier, vol. 88(1), pages 289-297, January.
    10. Dechezleprêtre, Antoine & Nachtigall, Daniel & Venmans, Frank, 2023. "The joint impact of the European Union emissions trading system on carbon emissions and economic performance," Journal of Environmental Economics and Management, Elsevier, vol. 118(C).
    11. Aatola, Piia & Ollikainen, Markku & Toppinen, Anne, 2013. "Price determination in the EU ETS market: Theory and econometric analysis with market fundamentals," Energy Economics, Elsevier, vol. 36(C), pages 380-395.
    12. Zhang, Yue & Wu, Qiong & Ren, Hongbo & Li, Qifen & Zhou, Weisheng, 2025. "A multi-agent distributed electricity-carbon shared trading strategy considering regional carbon inclusion," Renewable Energy, Elsevier, vol. 239(C).
    13. Tomin, Nikita & Shakirov, Vladislav & Kozlov, Aleksander & Sidorov, Denis & Kurbatsky, Victor & Rehtanz, Christian & Lora, Electo E.S., 2022. "Design and optimal energy management of community microgrids with flexible renewable energy sources," Renewable Energy, Elsevier, vol. 183(C), pages 903-921.
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