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Multi-energy sharing optimization for a building cluster towards net-zero energy system

Author

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  • Gao, Hongjun
  • Cai, Wenhui
  • He, Shuaijia
  • Jiang, Jun
  • Liu, Junyong

Abstract

With the promotion of net-zero energy buildings, building users gradually face the realistic demand of net-zero energy. Multi-energy sharing is a crucial measure to further improve the scheduling efficiency of building cluster to realize net-zero energy. In this context, a multi-energy sharing optimization model for a building cluster towards a net-zero energy system is proposed. A decentralized energy system framework considering multi-energy sharing is established, which includes a building cluster operator and multiple buildings. The building resources (e.g., energy production, conversion and storage equipment) are also modelled. In addition, a flexible net-zero energy comprehensive index is proposed based on three evaluation indexes (e.g., cost, energy, and emission), which depends on users' demand and application scenarios. Then, the scheduling optimization model of the building cluster is decomposed into the optimization models of building users and the building cluster operator considering the net-zero energy goal. Moreover, the analysis target cascading method is adopted to realize the distributed coordination solution of the optimization models, and an improved Shapley value method is adopted to realize the benefit adjustment of the whole building cluster. Finally, the numerical result shows that the building cluster is closer to a net-zero energy system by multi-energy sharing. The overall economic benefit and the realization degree of net-zero energy are both improved. The influence of multi-energy sharing and net-zero energy indexes on scheduling optimization and benefit distribution are both discussed carefully.

Suggested Citation

  • Gao, Hongjun & Cai, Wenhui & He, Shuaijia & Jiang, Jun & Liu, Junyong, 2023. "Multi-energy sharing optimization for a building cluster towards net-zero energy system," Applied Energy, Elsevier, vol. 350(C).
    • Handle: RePEc:eee:appene:v:350:y:2023:i:c:s030626192301142x
    DOI: 10.1016/j.apenergy.2023.121778
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    References listed on IDEAS

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    5. Hang Wang & Qunli Wu & Huiling Guo, 2025. "Low-Carbon Optimal Operation Strategy of Multi-Energy Multi-Microgrid Electricity–Hydrogen Sharing Based on Asymmetric Nash Bargaining," Sustainability, MDPI, vol. 17(10), pages 1-31, May.
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