Energy load predictions for buildings based on a total demand perspective
1998 (English)In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 28, no 1, 109-116 p.Article in journal (Refereed) Published
The outline of this work was to develop models for single family buildings, based on a total energy demand perspective, i.e., building-climate-inhabitants. The building-climate part was included by using a commercial dynamic energy simulation software. Whereas the influence from the inhabitants was implemented in terms of a predicted load for domestic equipment and hot water preparation, based on a reference building. The estimations were processed with neural network techniques. All models were based on access to measured diurnal data from a limited time period, ranging from 10 to 35 days. The annual energy predictions were found to be improved, compared to models based on only a building-climate perspective, when the domestic load was included. For periods with a small heating demand, i.e., May-September, the average accuracy was 7% and 4% for the heating and total energy load, respectively, whereas for the rest of the year the accuracy was on average 3% for both heating and total energy load.
Place, publisher, year, edition, pages
Elsevier, 1998. Vol. 28, no 1, 109-116 p.
neutral network, building energy prediction, inhabitant behaviour
Electrical Engineering, Electronic Engineering, Information Engineering Physical Sciences Building Technologies Energy Engineering
IdentifiersURN: urn:nbn:se:umu:diva-38898DOI: 10.1016/S0378-7788(98)00009-7OAI: oai:DiVA.org:umu-38898DiVA: diva2:384328