Title
A real-time diagnostic tool for evaluating the thermal performance of nearly zero energy buildings
Author
Abokersh, M.H.
Spiekman, M.E.
Vijlbrief, O.
van Goch, T.A.J.
Vallies, M.
Boer, D.
Publication year
2021
Abstract
The nearly zero-energy buildings (nZEB) presents a promising contribution to fulfill the EU sustainable future targets. However, the construction industry that leads the development of nZEB is facing challenges to guarantee its performance. In this context, this paper proposes a methodology framework based on Multizone Resistance–Capacitance Model to trace the nZEB performance challenges with quantifications for the time-dependent variables comprising occupant behaviors as well as the dynamic behavior of weather conditions and building operations. This approach incorporates Bayesian optimization for calibration purposes to minimize the required monitoring data. Moreover, the proposed framework integrates the uncertainty analysis (UA) with two-step global sensitivity analysis (GSA) in order to quantify and assess the uncertainty associate with the performance of the developed digital dwelling. The methodology application is demonstrated through a case study for a newly renovated two-story dwelling located in a district of Emmen at the Netherlands. The results confirm a high accuracy for the digital dwelling performance where the model offers a prediction accuracy of 2.2% and 7.03% for the thermal energy consumption and indoor zone temperature, respectively. On the other hand, the UA confirms a high uncertainty associate with the nZEB performance where the total thermal energy consumption can increase up to 100 kWh/m2 /yr. This variation is driven by the infiltration rates followed by the building envelope characteristics. The proposed framework can serve a diagnostic tool to assist the construction and installation companies to maintain the performance of their products proactively.
Subject
Nearly zero energy building
Building performance simulation
Occupant behaviors
Bayesian calibration
Monte Carlo uncertainty analysis
Global sensitivity analysis
Buildings and Infrastructures
2015 Urbanisation
To reference this document use:
http://resolver.tudelft.nl/uuid:f95a9e30-e347-4d05-97dd-c6b6d38f99a4
TNO identifier
882983
Source
Applied Energy, 281 (281), 1-22
Document type
article