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Energy signatures (also called change-point regression models) relate energy demand of buildings to climatic variables, typically ambient temperature.[1] Also other climatic variables such as heating or cooling degree days are used.[2] In most cases, heating or cooling building energy demand is analysed through energy signatures, but also hot water or electricity demand is considered.
Energy signatures make a simplified assumption of a linear relationship between a building's energy demand and temperature.[3] This assumption allows for balancing accuracy with computation time, as the estimation of energy demand through energy signatures is considerably faster than using building performance simulation software. A crucial advantage of applying energy signatures is that no detailed information on the geometrical, construction, and operational characteristics of buildings needs to be available.
References
[edit]- ^ Eggimann Sven, Fiorentini Massimo (2024), "Transferring energy signatures across space and time to assess their viability for rapid urban energy demand estimation", Energy and Buildings, vol. 316, doi:10.1016/j.enbuild.2024.114348
- ^ Gorazd Krese, Matjaž Prek, Vincenc Butala (2012), "Analysis of Building Electric Energy Consumption Data Using an Improved Cooling Degree Day Method", Journal of Mechanical Engineering, vol. 58, no. 2, pp. 107–114, doi:10.5545/sv-jme.2011.160
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: CS1 maint: multiple names: authors list (link) - ^ Martin Eriksson, Jan Akander, Bahram Moshfeg (2010), "Development and validation of energy signature method – Case study on a multi-family building in Sweden before and after deep renovation", Energy and Buildings, vol. 210, doi:10.1016/j.enbuild.2020.109756
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: CS1 maint: multiple names: authors list (link)