Refrigeration machine modeling for exergy-based performance and optimization potential evaluation of chillers in real field plants. (November 2021)

• Record Type: Journal Article
• Authors: Brenner, Lorenz; Tillenkamp, Frank; Ghiaus, Christian
• Is Part Of: International journal of refrigeration. Volume 131(2021)
• Page Start: 775
• Page End: 785
• Publication Date: 2021-11
• Subjects: Optimization potential assessment method -- Modeling -- Refrigeration plant -- Refrigeration machine -- Optimization potential index; Méthode d'évaluation du potentiel d'optimisation -- Modélisation -- Installation frigorifique -- Machine frigorifique -- Indice de potentiel d'optimisation; Refrigeration and refrigerating machinery -- Periodicals; 621.56
• DOI: 10.1016/j.ijrefrig.2021.07.026
• Languages: English
• ISSNs: 0140-7007

Abstract

Highlights: Four different refrigeration machine models are evaluated. Implementation of the models in the optimization potential index (OPI) is shown. Acceptable and adequate baseline values for the OPI scale are proposed. Performance and optimization potential of refrigeration machines is revealed. Application of the method is shown on a real field plant as a case study. Abstract: To investigate and optimize a refrigeration system, the behavior at various operating conditions must be known or determined. The performance and improvement possibilities may then be inferred from measurement data and compared with corresponding performance key figures. These values are typically referred to normal conditions and it is usually unknown which ones represent an adequate operation. However, it is relevant for refrigeration plant operators to have reference values for a large range of operation conditions as a baseline for determining the obtainable improvements. The present work proposes the application of steady-state models of refrigeration machines for increasing the range of applicability of the exergy-based optimization potential index method. Four different modeling approaches are evaluated and discussed: equation-fit, physical lumped parameter, refrigeration cycle and artificial neural network based models. The practical usage of the improved evaluation method is shown for the subsystem refrigeration machine on a real field installation as a case study. With the introduced additional limits for the optimization potential index, the interpretability of the results is increased. The distinction between adequate (technical requirements exceeded), acceptable (technical requirements fulfilled) and inadequate (potential for improvement) operation according to the state of the art in technology is straightforward, which is important in practice.