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A Multiobjective Fractional Programming for a CHP System Operation Optimization Based on Energy Intensity

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  • Ye Xu

    (State Key Laboratory of Power Grid Safety and Energy Conservation, China Electric Power Research Institute, Beijing 100192, China
    MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China)

  • Na Meng

    (State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems, China Electric Power Research Institute, Beijing 100192, China)

  • Xu Wang

    (State Key Laboratory of Power Grid Safety and Energy Conservation, China Electric Power Research Institute, Beijing 100192, China
    MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China)

  • Junyuan Tan

    (State Key Laboratory of Power Grid Safety and Energy Conservation, China Electric Power Research Institute, Beijing 100192, China
    MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China)

  • Wei Li

    (State Key Laboratory of Power Grid Safety and Energy Conservation, China Electric Power Research Institute, Beijing 100192, China
    MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China)

Abstract

The objective of this research is to establish a multiobjective fractional programming (MOFP) model for supporting the operational management of a combined heat and power (CHP) system. Compared with the traditional operational optimization model of the CHP system, the importance of the energy intensity (i.e., the ratio of energy consumption and energy production) was emphasized in the MOFP model, which is considered as the system objective for replacing the common objective of minimizing the economic cost. This innovative transformation effectively reduces excessive energy consumption, accompanied by improvement in the system revenue. The CHP system of an industrial park in the City of Jinan, China, was used as a study case for demonstration. The obtained results reflected that the combination of two gas turbines (GTs) ensured safe, efficient, and stable output for meeting daily power requirements in various seasons. As for the steam load, during the summer, two heat recovery steam generators (HRSGs) play a major role, where the insufficient part is supplemented by two gas-fired boilers (SBs); conversely, the steam load in winter is mainly satisfied by the aid of two SBs. The successful application of the MOFP model in the park could provide a good demonstration for CHP management in many other districts and cities.

Suggested Citation

  • Ye Xu & Na Meng & Xu Wang & Junyuan Tan & Wei Li, 2022. "A Multiobjective Fractional Programming for a CHP System Operation Optimization Based on Energy Intensity," Energies, MDPI, vol. 15(6), pages 1-17, March.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:6:p:1965-:d:766521
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    References listed on IDEAS

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    1. V. Charles & D. Dutta, 2006. "Identification Of Redundant Objective Functions In Multi-Objective Stochastic Fractional Programming Problems," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 23(02), pages 155-170.
    2. Yang, G. & Zhai, X.Q., 2019. "Optimal design and performance analysis of solar hybrid CCHP system considering influence of building type and climate condition," Energy, Elsevier, vol. 174(C), pages 647-663.
    3. Jing, You-Yin & Bai, He & Wang, Jiang-Jiang, 2012. "Multi-objective optimization design and operation strategy analysis of BCHP system based on life cycle assessment," Energy, Elsevier, vol. 37(1), pages 405-416.
    4. Zheng, C.Y. & Wu, J.Y. & Zhai, X.Q. & Wang, R.Z., 2016. "Impacts of feed-in tariff policies on design and performance of CCHP system in different climate zones," Applied Energy, Elsevier, vol. 175(C), pages 168-179.
    5. Wang, Jiangjiang & Lu, Zherui & Li, Meng & Lior, Noam & Li, Weihua, 2019. "Energy, exergy, exergoeconomic and environmental (4E) analysis of a distributed generation solar-assisted CCHP (combined cooling, heating and power) gas turbine system," Energy, Elsevier, vol. 175(C), pages 1246-1258.
    6. Klaus Mohn, 2020. "The gravity of status quo: A review of IEA's World Energy Outlook," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 1), pages 63-82.
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    Cited by:

    1. Marco Gambini & Stefano Mazzoni & Michela Vellini, 2023. "The Role of Cogeneration in the Electrification Pathways towards Decarbonization," Energies, MDPI, vol. 16(15), pages 1-23, July.

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