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Operation optimization of community integrated energy system: Rationality evaluation of operation scheme and a new solution approach

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  • Li, Peng
  • Wang, Jiahao
  • Jia, Hongjie
  • Li, Jianfeng
  • Pan, Youpeng

Abstract

The community integrated energy system (CIES) can fully utilize multiple heterogeneous energy sources by coordinating various energy equipment, thereby achieving benefits unattainable by a single energy system. However, existing research determines the use of various energy equipment solely based on operational simulation results, lacking a rationality evaluation grounded in the equipment's output mechanism. Furthermore, the optimal operation model of CIES is typically a nonconvex nonlinear model, presenting a conflict between model accuracy and solution efficiency. In this paper, we analyze the nonconvex nonlinear components, and establish a unified operation model of CIES. We examine the internal mechanism of energy equipment output from a target-driven perspective. By considering time decoupling, we design a two-phase fast calculation method for the optimal operation scheme. Finally, a specific CIES is used as a case study to demonstrate the rationality and effectiveness of the proposed theory and method. The simulation results show that our argument supports the rationality evaluation of the optimal operation scheme of CIES. The proposed method significantly improves the calculation speed of the optimal operation scheme at the expense of a small increase in total costs. Specifically, the calculation speed in this paper is improved by 87.2%, while the daily operating cost increases by only 0.012%.

Suggested Citation

  • Li, Peng & Wang, Jiahao & Jia, Hongjie & Li, Jianfeng & Pan, Youpeng, 2024. "Operation optimization of community integrated energy system: Rationality evaluation of operation scheme and a new solution approach," Applied Energy, Elsevier, vol. 375(C).
  • Handle: RePEc:eee:appene:v:375:y:2024:i:c:s0306261924015113
    DOI: 10.1016/j.apenergy.2024.124128
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    References listed on IDEAS

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    1. Wang, Chengshan & Lv, Chaoxian & Li, Peng & Song, Guanyu & Li, Shuquan & Xu, Xiandong & Wu, Jianzhong, 2018. "Modeling and optimal operation of community integrated energy systems: A case study from China," Applied Energy, Elsevier, vol. 230(C), pages 1242-1254.
    2. Wang, Yi & Cheng, Jiangnan & Zhang, Ning & Kang, Chongqing, 2018. "Automatic and linearized modeling of energy hub and its flexibility analysis," Applied Energy, Elsevier, vol. 211(C), pages 705-714.
    3. He, Shuaijia & Gao, Hongjun & Chen, Zhe & Liu, Junyong, 2023. "Data-driven worst conditional value at risk energy management model of energy station," Energy, Elsevier, vol. 266(C).
    4. Mendes, Gonçalo & Ioakimidis, Christos & Ferrão, Paulo, 2011. "On the planning and analysis of Integrated Community Energy Systems: A review and survey of available tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4836-4854.
    5. Li, Peng & Wang, Zixuan & Wang, Jiahao & Guo, Tianyu & Yin, Yunxing, 2021. "A multi-time-space scale optimal operation strategy for a distributed integrated energy system," Applied Energy, Elsevier, vol. 289(C).
    6. Tostado-Véliz, Marcos & Jordehi, Ahmad Rezaee & Mansouri, Seyed Amir & Jurado, Francisco, 2023. "A two-stage IGDT-stochastic model for optimal scheduling of energy communities with intelligent parking lots," Energy, Elsevier, vol. 263(PD).
    7. Mu, Yunfei & Xu, Yurui & Cao, Yan & Chen, Wanqing & Jia, Hongjie & Yu, Xiaodan & Jin, Xiaolong, 2022. "A two-stage scheduling method for integrated community energy system based on a hybrid mechanism and data-driven model," Applied Energy, Elsevier, vol. 323(C).
    8. Mu, Yunfei & Chen, Wanqing & Yu, Xiaodan & Jia, Hongjie & Hou, Kai & Wang, Congshan & Meng, Xianjun, 2020. "A double-layer planning method for integrated community energy systems with varying energy conversion efficiencies," Applied Energy, Elsevier, vol. 279(C).
    9. Zhu, Jizhong & Dong, Hanjiang & Zheng, Weiye & Li, Shenglin & Huang, Yanting & Xi, Lei, 2022. "Review and prospect of data-driven techniques for load forecasting in integrated energy systems," Applied Energy, Elsevier, vol. 321(C).
    10. Jia, Jiandong & Li, Haiqiao & Wu, Di & Guo, Jiacheng & Jiang, Leilei & Fan, Zeming, 2024. "Multi-objective optimization study of regional integrated energy systems coupled with renewable energy, energy storage, and inter-station energy sharing," Renewable Energy, Elsevier, vol. 225(C).
    11. Li, Peng & Guo, Tianyu & Abeysekera, Muditha & Wu, Jianzhong & Han, Zhonghe & Wang, Zixuan & Yin, Yunxing & Zhou, Fengquan, 2021. "Intraday multi-objective hierarchical coordinated operation of a multi-energy system," Energy, Elsevier, vol. 228(C).
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