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Novel flexibility evaluation of hybrid combined cooling, heating and power system with an improved operation strategy

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  • Zhou, Yuan
  • Wang, Jiangjiang
  • Dong, Fuxiang
  • Qin, Yanbo
  • Ma, Zherui
  • Ma, Yanpeng
  • Li, Jianqiang

Abstract

Flexible combined cooling, heating and power (CCHP) systems actively resist the variable factors from both sides of load and renewable energies. In order to fully utilize the flexibility potential of the CCHP system, this paper divides the system with the energy supply process in an analytical viewpoint of flexibility and proposes a novel operational strategy of following system flexibility to schedule energy dispatch. An indicator called flexibility index is proposed and employed to evaluate the flexibility of CCHP system, which comprehensively reflects system design and operational performance. The flexibility index assesses the contribution of energy storage devices in reducing the underutilized fuel consumption and decreasing grid dependence. A multi-objective optimization model is constructed to improve the economic performance and flexibility of the CCHP system. The results in a case study demonstrate the proposed strategy can use flexibility components to cover 93.75% and 99.31% of load scenarios in cooling and heating seasons, respectively. Compared with traditional strategies of following electric load and following thermal load, the proposed method reduces the dependence on the electric grid by 98.04% and 99.61%, respectively, and declines the underused fuel consumption by 79.79% and 84.05%, respectively. The carbon emissions because of the efficient energy management are reduced by 8.30% and 21.30%, respectively.

Suggested Citation

  • Zhou, Yuan & Wang, Jiangjiang & Dong, Fuxiang & Qin, Yanbo & Ma, Zherui & Ma, Yanpeng & Li, Jianqiang, 2021. "Novel flexibility evaluation of hybrid combined cooling, heating and power system with an improved operation strategy," Applied Energy, Elsevier, vol. 300(C).
    • Handle: RePEc:eee:appene:v:300:y:2021:i:c:s0306261921007650
    DOI: 10.1016/j.apenergy.2021.117358
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    19. Zhao, Xiangming & Guo, Jianxiang & He, Maogang, 2023. "Multi-objective optimization and improvement of multi-energy combined cooling, heating and power system based on system simplification," Renewable Energy, Elsevier, vol. 217(C).
    20. Liu, Jiejie & Li, Yao & Ma, Yanan & Qin, Ruomu & Meng, Xianyang & Wu, Jiangtao, 2023. "Two-layer multiple scenario optimization framework for integrated energy system based on optimal energy contribution ratio strategy," Energy, Elsevier, vol. 285(C).
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    22. Wang, Yuwei & Song, Minghao & Jia, Mengyao & Li, Bingkang & Fei, Haoran & Zhang, Yiyue & Wang, Xuejie, 2023. "Multi-objective distributionally robust optimization for hydrogen-involved total renewable energy CCHP planning under source-load uncertainties," Applied Energy, Elsevier, vol. 342(C).

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