uu.seUppsala University Publications
Change search
ReferencesLink to record
Permanent link

Direct link
Day-ahead predictions of electricity consumption in a Swedish office building from weather, occupancy, and temporal data
Royal Inst Technol, Dept Ind Informat & Control Syst, SE-10044 Stockholm, Sweden.
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Solid State Physics. (Built Environment Energy Systems Group (BEESG))
Royal Inst Technol, Dept Ind Informat & Control Syst, SE-10044 Stockholm, Sweden.
SP Tech Res Inst Sweden, Dept Energy Technol, SE-50115 Boras, Sweden.
2015 (English)In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 108, 279-290 p.Article in journal (Refereed) PublishedText
Abstract [en]

An important aspect of demand response (DR) is to make accurate predictions for the consumption in the short term, in order to have a benchmark load profile which can be compared with the load profile influenced by DR signals. In this paper, a data analysis approach to predict electricity consumption on load level in office buildings on a day-ahead basis is presented. The methodology is: (i) exploratory data analysis, (ii) produce linear models between the predictors (weather and occupancies) and the outcomes (appliance, ventilation, and cooling loads) in a step wise function, and (iii) use the models from (ii) to predict the consumption levels with day-ahead prognosis data on the predictors. The data has been collected from a Swedish office building floor. The results from (ii) show that occupancy is correlated with appliance load, and outdoor temperature and a temporal variable defining work hours are connected with ventilation and cooling load. It is concluded from the results in (iii) that the error rate decreases if fewer predictors are included in the predictions. This is because of the inherent forecast errors in the day-ahead prognosis data. The achieved error rates are comparable with similar prediction studies in related work.

Place, publisher, year, edition, pages
2015. Vol. 108, 279-290 p.
Keyword [en]
Office building electricity consumption, Load level, Building energy management system, HVAC, Exploratory data analysis, Prediction, Regression, Demand response
National Category
Energy Systems
URN: urn:nbn:se:uu:diva-269036DOI: 10.1016/j.enbuild.2015.08.052ISI: 000365364500028OAI: oai:DiVA.org:uu-269036DiVA: diva2:882001
SweGRIDS - Swedish Centre for Smart Grids and Energy Storage
Available from: 2015-12-12 Created: 2015-12-12 Last updated: 2016-01-12Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Widén, Joakim
By organisation
Solid State Physics
In the same journal
Energy and Buildings
Energy Systems

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 332 hits
ReferencesLink to record
Permanent link

Direct link