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|Title: ||Data-driven simple thermal models: the importance of the parameter estimates|
|Authors: ||Dimitriou, Vanda|
Firth, Steven K.
Hassan, Tarek M.
Ordinary least squares
|Issue Date: ||2015|
|Publisher: ||© 2015 The Authors. Published by Elsevier Ltd.|
|Citation: ||DIMITRIOU, V. ... et al., 2015. Data-driven simple thermal models: The importance of the parameter estimates. Energy Procedia, 78, pp.2614-2619.|
|Abstract: ||A simple 1st order data-driven lumped parameter model of a domestic building is developed to explore the effect of using
different model parameter values in the model outputs. The adequacy of the Ordinary Least Square estimation technique is
explored. Results show that an improved fit to the measured data can be achieved by varying the initial model parameter values
of capacitance (up to 78%), resistance (-46%) and effective window area (-59%). This highlights the importance of having a
reference set of parameters based on the known physical characteristics of the building. Finally, the model residuals are deemed appropriate to inform the decision making process for further model development.|
|Description: ||This paper was also presented at the 6th International Building Physics Conference (IBPC2015), Turin,14-17th June. This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 NonCommercial-NoDerivatives Licence (BY-NC-ND). Full details of this licence are available at: http://creativecommons.org/licenses/by-nc-nd/4.0/|
|Sponsor: ||This work has been carried out as part of the REFIT project (‘Personalised Retrofit Decision Support Tools for UK Homes using Smart Home Technology’, £1.5m, Grant Reference EP/K002457/1).|
|Publisher Link: ||http://dx.doi.org/10.1016/j.egypro.2015.11.322|
|Appears in Collections:||Published Articles (Architecture, Building and Civil Engineering)|
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