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Optimal Energy Configuration of Integrated Energy Community Considering Carbon Emission

Author

Listed:
  • Jiangping Liu

    (Hubei Power Exchange Center, Wuhan 430077, China)

  • Jianghong Nie

    (Hubei Power Exchange Center, Wuhan 430077, China)

  • Xue Cui

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

  • Peng Liu

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

  • Pingzheng Tong

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

  • Xue Liu

    (School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)

Abstract

An integrated energy community with a distributed utilization of renewable energy and complementary electricity–gas–cold–heat integrated energy will play an important role in energy conservation and emission reduction. In addition, compared with traditional thermoelectric power equipment, solid oxide fuel cells have many advantages, such as a high energy utilization rate, good waste heat quality, and low carbon emissions. Therefore, the SOFC-based multi-energy and energy storage sharing operation model of an integrated energy community with an electricity–gas–cooling–heat integrated energy system is constructed, and a bi-objective optimal configuration model considering the carbon emission index is established. Considering the economic objective of the smallest annual total operating cost as the most important objective in optimizing the planning model, the ε-constraint method is used to transform the environmental objective function with the smallest annual total carbon emission into a constraint condition under the decision making of an economic single objective function, and then the planning model is linearized and solved by using the Big-M method and the McCormick relaxation method. By calculating and analyzing the energy allocation results in five scenarios, the effectiveness and rationality of the model built in this article are verified. At the same time, the calculation example analysis results show that as the ε value decreases, the energy configuration of the integrated energy community will shift from natural gas to clean energy. From this perspective, the energy equipment configuration and operating costs will increase. However, the heat storage system and power storage system sharing can effectively reduce the energy allocation capacity and costs.

Suggested Citation

  • Jiangping Liu & Jianghong Nie & Xue Cui & Peng Liu & Pingzheng Tong & Xue Liu, 2024. "Optimal Energy Configuration of Integrated Energy Community Considering Carbon Emission," Sustainability, MDPI, vol. 16(2), pages 1-26, January.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:2:p:728-:d:1319076
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    References listed on IDEAS

    as
    1. Jing, Rui & Wang, Meng & Liang, Hao & Wang, Xiaonan & Li, Ning & Shah, Nilay & Zhao, Yingru, 2018. "Multi-objective optimization of a neighborhood-level urban energy network: Considering Game-theory inspired multi-benefit allocation constraints," Applied Energy, Elsevier, vol. 231(C), pages 534-548.
    2. van der Stelt, Sander & AlSkaif, Tarek & van Sark, Wilfried, 2018. "Techno-economic analysis of household and community energy storage for residential prosumers with smart appliances," Applied Energy, Elsevier, vol. 209(C), pages 266-276.
    3. Yunjie Rao & Xue Cui & Xuyue Zou & Liming Ying & Pingzheng Tong & Junlin Li, 2023. "Research on Distributed Energy Storage Planning-Scheduling Strategy of Regional Power Grid Considering Demand Response," Sustainability, MDPI, vol. 15(19), pages 1-14, October.
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