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      Review on Modeling of Vapor Compression Chillers: District Cooling Perspective

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      https://www.riss.kr/link?id=A106930841

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      다국어 초록 (Multilingual Abstract)

      Energy consumption and its associated consequences can be reduced by implementing district cooling strategies that supply low temperature water to a wide range of end users through chillers and distribution networks. Adequate understanding, performance prediction and further optimization of vapor compression chillers used widely in district cooling plants have been a subject of intense research through model-based approaches. In this context, we perform an extensive review of different modeling techniques used for predicting steady-state or dynamic performance of vapor compression liquid chillers. The explored modeling techniques include physical and empirical models. Different physical models used for vapor compression chillers, based on physics laws, are discussed in detail. Furthermore, empirical models (based on artificial neural networks, regression analysis) are elaborated along with their advantages and drawbacks. The physical models can depict both steady- and unsteady-state performance of the vapor compression chiller; however, their accuracy and physical realism can be enhanced by considering the geometrical arrangement of the condenser and evaporator and validating them for various ecofriendly refrigerants and large system size (i.e., cooling capacity). Apparently, empirical models are easy to develop but do not provide the necessary physical realism of the process of vapor compression chiller. It is further observed that DC plants/networks have been modeled from the point of view of optimization or integration but no efforts have been made to model the chillers with multiple VCR cycles. The development of such models will facilitate to optimize the DC plant and provide improved control strategies for effective and efficient operation.
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      Energy consumption and its associated consequences can be reduced by implementing district cooling strategies that supply low temperature water to a wide range of end users through chillers and distribution networks. Adequate understanding, performanc...

      Energy consumption and its associated consequences can be reduced by implementing district cooling strategies that supply low temperature water to a wide range of end users through chillers and distribution networks. Adequate understanding, performance prediction and further optimization of vapor compression chillers used widely in district cooling plants have been a subject of intense research through model-based approaches. In this context, we perform an extensive review of different modeling techniques used for predicting steady-state or dynamic performance of vapor compression liquid chillers. The explored modeling techniques include physical and empirical models. Different physical models used for vapor compression chillers, based on physics laws, are discussed in detail. Furthermore, empirical models (based on artificial neural networks, regression analysis) are elaborated along with their advantages and drawbacks. The physical models can depict both steady- and unsteady-state performance of the vapor compression chiller; however, their accuracy and physical realism can be enhanced by considering the geometrical arrangement of the condenser and evaporator and validating them for various ecofriendly refrigerants and large system size (i.e., cooling capacity). Apparently, empirical models are easy to develop but do not provide the necessary physical realism of the process of vapor compression chiller. It is further observed that DC plants/networks have been modeled from the point of view of optimization or integration but no efforts have been made to model the chillers with multiple VCR cycles. The development of such models will facilitate to optimize the DC plant and provide improved control strategies for effective and efficient operation.

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      참고문헌 (Reference)

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      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2023 평가예정 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
      2020-01-01 평가 등재학술지 유지 (해외등재 학술지 평가) KCI등재
      2013-01-01 평가 등재 1차 FAIL (등재유지) KCI등재
      2010-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      2009-01-01 평가 등재후보 1차 PASS (등재후보1차) KCI등재후보
      2008-01-01 평가 등재후보학술지 유지 (등재후보1차) KCI등재후보
      2006-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.56 0.56 0.48
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.4 0.34 0.535 0.11
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