Development and Analysis of a Dynamic Energy Model of an Office Using a Building Management System (BMS) and Actual Measurement Data

Rasa Džiugaitė-Tumėnienė, Rūta Mikučionienė, Giedrė Streckienė and Juozas Bielskus
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Rasa Džiugaitė-Tumėnienė: Department of Building Energetics, Vilnius Gediminas Technical University, Sauletekio Ave. 11, 10223 Vilnius, Lithuania
Rūta Mikučionienė: Department of Building Energetics, Vilnius Gediminas Technical University, Sauletekio Ave. 11, 10223 Vilnius, Lithuania
Giedrė Streckienė: Department of Building Energetics, Vilnius Gediminas Technical University, Sauletekio Ave. 11, 10223 Vilnius, Lithuania
Juozas Bielskus: Department of Building Energetics, Vilnius Gediminas Technical University, Sauletekio Ave. 11, 10223 Vilnius, Lithuania

Energies, 2021, vol. 14, issue 19, 1-24

Abstract: Calibration of the energy model of a building is one of the essential tasks required to determine the efficiency of building management systems, and both their own and other systems’ improvement potential. In order to make the building energy model as accurate as possible, it is necessary to collect comprehensive data on its operation and sometimes to assess the missing information. This paper represents the process of developing an energy model for an administrative building and its calibration procedure, using detailed long-term measurement and building management system (BMS) data. Indoor air temperature, CO? concentration, and relative humidity were experimentally measured and evaluated separately. Such dual application of data reduces the inaccuracy of the assumptions made and assesses the model’s accuracy. The DesignBuilder software developed the building model. During the development of the model, it was observed that the actual energy consumption needs to be assessed, as the assumptions made during the design about the operation and management of HVAC systems often do not coincide with the actual situation. After integrating BMS information on HVAC management into the building model, the resulting discrepancy between the model results and the actual heat consumption was 6.5%. Such a model can be further used to optimize management decisions and assess energy savings potential.

Keywords: building dynamic energy model; BMS; HVAC; DesignBuilder; measurements; indoor climate parameters (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: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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