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Design optimization of community energy systems based on dual uncertainties of meteorology and load for robustness improvement

Author

Listed:
  • Xue, Kai
  • Wang, Jinshi
  • Zhang, Shuo
  • Ou, Kejie
  • Chen, Weixiong
  • Zhao, Quanbin
  • Hu, Guangtao
  • Sun, Zhiyong

Abstract

The community energy system (CES) is widely recognized for the contribution to clean and sustainable development, which allows for the integration of locally available energy sources and synergistic supply of demand. The parameter fluctuations faced by CES in operation affect the overall performance, so it is urgent to implement robustness enhancement research against uncertainty. For the purpose of improving the resilience of CES, a new design framework is proposed to facilitate more rational capacity planning in this work, considering dual uncertainties of meteorology and load. Multi-objective optimization and decision-making methods are employed, with lifecycle cost, primary energy saving rate, and pollutant reduction rate as indicators. Latin hypercube sampling and Monte Carlo simulation are coupled for the uncertainty optimization. When meteorology and load fluctuate concurrently, the comprehensive performance index have a probability of 67 % and 81 % to remain within the deviation interval of certainty optimization under following electrical load and following thermal load strategies. The robustness and comprehensive performance index of the former can be improved by 24.6 % and 3.6 % over the certainty optimization, and the values are 20.9 % and 3.9 % in the latter. The results of the case study show that dual uncertainty optimization leads to greater reliability of CES.

Suggested Citation

  • Xue, Kai & Wang, Jinshi & Zhang, Shuo & Ou, Kejie & Chen, Weixiong & Zhao, Quanbin & Hu, Guangtao & Sun, Zhiyong, 2024. "Design optimization of community energy systems based on dual uncertainties of meteorology and load for robustness improvement," Renewable Energy, Elsevier, vol. 232(C).
    • Handle: RePEc:eee:renene:v:232:y:2024:i:c:s0960148124010243
    DOI: 10.1016/j.renene.2024.120956
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    as
    1. Zhao, Naixin & Gu, Wenbo & Zheng, Zipeng & Ma, Tao, 2023. "Multi-objective bi-level planning of the integrated energy system considering uncertain user loads and carbon emission during the equipment manufacturing process," Renewable Energy, Elsevier, vol. 216(C).
    2. Wang, Jiangjiang & Deng, Hongda & Qi, Xiaoling, 2022. "Cost-based site and capacity optimization of multi-energy storage system in the regional integrated energy networks," Energy, Elsevier, vol. 261(PA).
    3. Wang, Haiyang & Zhang, Chenghui & Li, Ke & Ma, Xin, 2021. "Game theory-based multi-agent capacity optimization for integrated energy systems with compressed air energy storage," Energy, Elsevier, vol. 221(C).
    4. Abdoos, Ali Akbar & Abdoos, Hatef & Kazemitabar, Javad & Mobashsher, Mohammad Mehdi & Khaloo, Hooman, 2023. "An intelligent hybrid method based on Monte Carlo simulation for short-term probabilistic wind power prediction," Energy, Elsevier, vol. 278(PA).
    5. Li, Peng & Wang, Zixuan & Wang, Jiahao & Yang, Weihong & Guo, Tianyu & Yin, Yunxing, 2021. "Two-stage optimal operation of integrated energy system considering multiple uncertainties and integrated demand response," Energy, Elsevier, vol. 225(C).
    6. Lasemi, Mohammad Ali & Arabkoohsar, Ahmad & Hajizadeh, Amin & Mohammadi-ivatloo, Behnam, 2022. "A comprehensive review on optimization challenges of smart energy hubs under uncertainty factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    7. Li, Yuxuan & Zhang, Junli & Wu, Xiao & Shen, Jiong & Maréchal, François, 2023. "Stochastic-robust planning optimization method based on tracking-economy extreme scenario tradeoff for CCHP multi-energy system," Energy, Elsevier, vol. 283(C).
    8. Peng, Chunhua & Fan, Guozhu & Xiong, Zhisheng & Zeng, Xinzhi & Sun, Huijuan & Xu, Xuesong, 2023. "Integrated energy system planning considering renewable energy uncertainties based on multi-scenario confidence gap decision," Renewable Energy, Elsevier, vol. 216(C).
    9. Fan, Wei & Tan, Qingbo & Zhang, Amin & Ju, Liwei & Wang, Yuwei & Yin, Zhe & Li, Xudong, 2023. "A Bi-level optimization model of integrated energy system considering wind power uncertainty," Renewable Energy, Elsevier, vol. 202(C), pages 973-991.
    10. Kostelac, Matija & Pavić, Ivan & Zhang, Ning & Capuder, Tomislav, 2022. "Uncertainty modelling of an industry facility as a multi-energy demand response provider," Applied Energy, Elsevier, vol. 307(C).
    11. Gimelli, A. & Mottola, F. & Muccillo, M. & Proto, D. & Amoresano, A. & Andreotti, A. & Langella, G., 2019. "Optimal configuration of modular cogeneration plants integrated by a battery energy storage system providing peak shaving service," Applied Energy, Elsevier, vol. 242(C), pages 974-993.
    12. Lu, Menglong & Sun, Yongjun & Ma, Zhenjun, 2024. "Multi-objective design optimization of multiple energy systems in net/nearly zero energy buildings under uncertainty correlations," Applied Energy, Elsevier, vol. 370(C).
    13. Ma, Yixiang & Yu, Lean & Zhang, Guoxing & Lu, Zhiming & Wu, Jiaqian, 2023. "Source-load uncertainty-based multi-objective multi-energy complementary optimal scheduling," Renewable Energy, Elsevier, vol. 219(P1).
    14. Ren, Xiaoxiao & Han, Zijun & Ma, Jinpeng & Xue, Kai & Chong, Daotong & Wang, Jinshi & Yan, Junjie, 2024. "Life-cycle-based multi-objective optimal design and analysis of distributed multi-energy systems for data centers," Energy, Elsevier, vol. 288(C).
    15. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    16. Dong, Fuxiang & Wang, Jiangjiang & Xu, Hangwei & Zhang, Xutao, 2024. "A robust real-time energy scheduling strategy of integrated energy system based on multi-step interval prediction of uncertainties," Energy, Elsevier, vol. 300(C).
    17. Liu, Zhijian & Li, Ying & Fan, Guangyao & Wu, Di & Guo, Jiacheng & Jin, Guangya & Zhang, Shicong & Yang, Xinyan, 2022. "Co-optimization of a novel distributed energy system integrated with hybrid energy storage in different nearly zero energy community scenarios," Energy, Elsevier, vol. 247(C).
    18. Huang, Shangjiu & Lu, Hao & Chen, Maozhi & Zhao, Wenjun, 2023. "Integrated energy system scheduling considering the correlation of uncertainties," Energy, Elsevier, vol. 283(C).
    19. Sanaye, Sepehr & Khakpaay, Navid, 2014. "Simultaneous use of MRM (maximum rectangle method) and optimization methods in determining nominal capacity of gas engines in CCHP (combined cooling, heating and power) systems," Energy, Elsevier, vol. 72(C), pages 145-158.
    20. Mukhopadhyay, Bineeta & Das, Debapriya, 2020. "Multi-objective dynamic and static reconfiguration with optimized allocation of PV-DG and battery energy storage system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
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