LAPSE:2023.14503
Published Article

LAPSE:2023.14503
A Multiobjective Fractional Programming for a CHP System Operation Optimization Based on Energy Intensity
March 1, 2023
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.
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.
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Keywords
energy intensity, fractional planning, multiobjective optimization, natural gas-fired distributed energy system
Subject
Suggested Citation
Xu Y, Meng N, Wang X, Tan J, Li W. A Multiobjective Fractional Programming for a CHP System Operation Optimization Based on Energy Intensity. (2023). LAPSE:2023.14503
Author Affiliations
Xu Y: 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 Engineeri
Meng N: State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems, China Electric Power Research Institute, Beijing 100192, China
Wang X: 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 Engineeri
Tan J: 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 Engineeri
Li W: 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 Engineeri
Meng N: State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems, China Electric Power Research Institute, Beijing 100192, China
Wang X: 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 Engineeri
Tan J: 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 Engineeri
Li W: 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 Engineeri
Journal Name
Energies
Volume
15
Issue
6
First Page
1965
Year
2022
Publication Date
2022-03-08
ISSN
1996-1073
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PII: en15061965, Publication Type: Journal Article
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LAPSE:2023.14503
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https://doi.org/10.3390/en15061965
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