A Data-Driven Approach for Enhancing the Efficiency in Chiller Plants: A Hospital Case Study

Serafín Alonso, Antonio Morán, Miguel Ángel Prada, Perfecto Reguera, Juan José Fuertes and Manuel Domínguez
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Serafín Alonso: Grupo de Investigación en Supervisión, Control y Automatización de Procesos Industriales (SUPPRESS), Esc. de Ing. Industrial e Informática, Universidad de León, Campus de Vegazana s/n, 24007 León, Spain
Antonio Morán: Grupo de Investigación en Supervisión, Control y Automatización de Procesos Industriales (SUPPRESS), Esc. de Ing. Industrial e Informática, Universidad de León, Campus de Vegazana s/n, 24007 León, Spain
Miguel Ángel Prada: Grupo de Investigación en Supervisión, Control y Automatización de Procesos Industriales (SUPPRESS), Esc. de Ing. Industrial e Informática, Universidad de León, Campus de Vegazana s/n, 24007 León, Spain
Perfecto Reguera: Grupo de Investigación en Supervisión, Control y Automatización de Procesos Industriales (SUPPRESS), Esc. de Ing. Industrial e Informática, Universidad de León, Campus de Vegazana s/n, 24007 León, Spain
Juan José Fuertes: Grupo de Investigación en Supervisión, Control y Automatización de Procesos Industriales (SUPPRESS), Esc. de Ing. Industrial e Informática, Universidad de León, Campus de Vegazana s/n, 24007 León, Spain
Manuel Domínguez: Grupo de Investigación en Supervisión, Control y Automatización de Procesos Industriales (SUPPRESS), Esc. de Ing. Industrial e Informática, Universidad de León, Campus de Vegazana s/n, 24007 León, Spain

Energies, 2019, vol. 12, issue 5, 1-28

Abstract: Large buildings cause more than 20% of the global energy consumption in advanced countries. In buildings such as hospitals, cooling loads represent an important percentage of the overall energy demand (up to 44%) due to the intensive use of heating, ventilation and air conditioning (HVAC) systems among other key factors, so their study should be considered. In this paper, we propose a data-driven analysis for improving the efficiency in multiple-chiller plants. Coefficient of performance (COP) is used as energy efficiency indicator. Data analysis, based on aggregation operations, filtering and data projection, allows us to obtain knowledge from chillers and the whole plant, in order to define and tune management rules. The plant manager software (PMS) that implements those rules establishes when a chiller should be staged up/down and which chiller should be started/stopped according different efficiency criteria. This approach has been applied on the chiller plant at the Hospital of León.

Keywords: energy efficiency; HVAC systems; chiller plants; chiller performance; COP; data-driven analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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