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Autor(en) / Beteiligte
Titel
An inquiry into the effect of thermal energy meter density and configuration on load disaggregation accuracy
Ist Teil von
  • HVAC&R research, 2023-04, Vol.29 (4), p.424-441
Ort / Verlag
Philadelphia: Taylor & Francis
Erscheinungsjahr
2023
Quelle
Taylor & Francis
Beschreibungen/Notizen
  • Initial and maintenance costs often prevent dense submeter installations that enable room-level thermal energy monitoring. Previous studies suggested that building automation system (BAS) trend data represents an untapped potential to disaggregate existing meter data for heating and cooling into device- and system-level end-uses. These techniques disaggregate meter data by analyzing trend data that provide contextual information regarding the operating status of energy-consuming equipment. However, the level of submetering required to enable end-use disaggregation has yet to be studied. To this end, this paper investigates the effect of submeter density and configuration on the performance of a regression-based disaggregation strategy using BAS trend data as predictors. The method was evaluated in two steps; first, using synthetic meter and BAS trend data generated by a building performance simulation (BPS) model of a government office building, and second, with submeter data from a real office building. The results highlight the factors affecting the minimum number of heating energy submeters needed to be installed in both buildings for accurate device- and system-level disaggregation. The methodology presented in the paper can also inform changes in building design codes and standards regarding the minimum density and appropriate configuration for submetering.
Sprache
Englisch
Identifikatoren
ISSN: 2374-4731
eISSN: 2374-474X
DOI: 10.1080/23744731.2023.2197814
Titel-ID: cdi_proquest_journals_2819152922

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