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TitleTowards integration of virtual meters into building energy management systems: Development and assessment of thermal meters for cooling
AuthorSaloux, EORCID logo; Zhang, K
SourceJournal of Building Engineering 65, 105785, 2023 p. 1-28,
Alt SeriesNatural Resources Canada, Contribution Series 20230014
Mediapaper; digital; on-line
File formatpdf
Subjectsenergy; Energy management
Released2023 01 09
AbstractThe increasing availability of sub-hourly operational data represents an untapped opportunity to help better manage and operate buildings. However, specific variables may not be typically measured, and virtual sensors and meters can be used to infer these key variables. This paper presents the development and assessment of three virtual energy meters (VEMs), which aim to estimate cooling load at different levels by leveraging available data from: 1) the chilled water plants, 2) the Air Handling Units (AHUs), and 3) the Variable Air Volume (VAV) boxes. These VEMs were developed based on mass and energy balance equations and applied to an existing large commercial building equipped with primary/secondary AHUs and VAV systems. Case study results show 11% difference in average between similar VEMs in two years and that 23% of the building cooling load is for dehumidification. Among the over 500 office rooms, 9% consume more than 3 times the average cooling energy. This paper also discussed in detail the merits of each VEM, and their potential applications including performance tracking, energy use mapping, inefficiency detection and operation optimization. This work highlights the potential of VEMs and represents a first step towards their integration into building energy management systems.
Summary(Plain Language Summary, not published)
This paper focuses on virtual energy metering approaches applied to estimate the cooling load for a large office building. Virtual meters allow to complement the available data by inferring important variables, which are typically not measured. This paper aims to better assess cooling load from available measurements in order to assess operation faults, unlock control opportunities and improve buildings controls, eventually targeting energy use and GHG emission reductions.

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