Further validation of a method aimed to estimate building performance parameters
2005 (English)In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 37, no 8, 867-871 p.Article in journal (Refereed) PublishedText
A further validation of an earlier developed neural network method for estimating the total heat loss coefficient (K-tot), the total heat capacity (C-tot) and the gain factor (alpha) based on measured diumal data of internal-external temperature difference, supplied heat for heating and "free heat" is presented. The validation was performed in laboratory scale, using a test cell, for three different cases of ventilation, without (constant)-, natural-, and forced ventilation. Earlier measurements from a building was also used in order to simulate a realistic energy use pattern and a rather stochastic behavior of alpha, which also was transformed to represent existing and future buildings in terms of the composition of their energy use. For all three types of ventilation and different types of buildings, the method was capable of estimating the three different performance parameters and their different dependencies. For K-tot, the RMSE was between 3 and 20% and for alpha, the deviation was between 9 and 19%.
Place, publisher, year, edition, pages
Lausanne: Elsevier, 2005. Vol. 37, no 8, 867-871 p.
buildings, heat gain, heat capacity, heat balance, time constant, neural network, identification, heat loss
Building Technologies Energy Engineering Civil Engineering
IdentifiersURN: urn:nbn:se:umu:diva-120407DOI: 10.1016/j.enbuild.2004.11.005ISI: 000230014100009OAI: oai:DiVA.org:umu-120407DiVA: diva2:935294