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Prediction of plug loads in office buildings: Simplified and probabilistic methods

Mahdavi, A; Tahmasebi, F; Kayalar, M; (2016) Prediction of plug loads in office buildings: Simplified and probabilistic methods. Energy and Buildings , 129 pp. 322-329. 10.1016/j.enbuild.2016.08.022. Green open access

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Abstract

To predict buildings’ energy use, multiple systems and processes must be considered. Next to factors such as building fabric and construction, indoor environmental control systems, and weather conditions, the energy demand attributable to buildings’ internal heat gains resulting from inhabitants, lighting, and equipment usage also needs to be addressed. Given this background, the present contribution focuses on plug loads in office buildings associated mainly with computers and peripherals. Using long-term observational data obtained from a continuously monitored office building in Vienna, we specifically explore the relationship between inhabitants’ presence, installed power for equipment, and the resulting electrical energy use. The findings facilitate the formulation of both simplified and probabilistic office plug loads predictions methods. Thereby, the model evaluation results suggest that the non-stochastic model provides fairly reasonable predictions of annual energy use associated with plug loads. However, the stochastic plug load model – together with a stochastic occupancy model – outperforms the simplified model in predicting the plug loads peak and distribution.

Type: Article
Title: Prediction of plug loads in office buildings: Simplified and probabilistic methods
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.enbuild.2016.08.022
Publisher version: https://doi.org/10.1016/j.enbuild.2016.08.022
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Science & Technology, Technology, Construction & Building Technology, Energy & Fuels, Engineering, Civil, Engineering, Occupancy, Plug loads, Equipment, Electrical energy use, Stochastic model, Non-stochastic method, OCCUPANT BEHAVIOR, PERFORMANCE SIMULATION, ENERGY-CONSUMPTION, EQUIPMENT, MODELS, TOOL
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources
URI: https://discovery.ucl.ac.uk/id/eprint/10058650
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