A framework to evaluate the thermal and energy performance of smart building systems in existing buildings: A case study on automated interior insulating window shades

This paper presents a methodological framework for evaluating the thermal and energy performance of smart building systems in existing buildings, with a focus on automated interior insulating window shades as an energy efficiency retrofit measure. The methodology is demonstrated through a case study of a high-rise building in which different shade control strategies were assessed. This paper provides comprehensive descriptions of the (i) development and implementation of the study design, (ii) selection and deployment of measurement instruments, (iii) analysis of various shade control strategies to quantify thermal and energy performance for heating, cooling, and ventilation energy end-uses, and (iv) quantification of the uncertainty associated with the measurements and calculations. This manuscript provides detailed, step-by-step and in-depth guidance to conduct such an evaluation. Overall, this paper:•Highlights the benefits, challenges, and limitations in conducting long-term measurements that capture realistic temporal, seasonal, and operational patterns in an occupied existing building.•Provides practical considerations for such measurements and analysis approaches, upon which future studies can build.•Emphasizes the importance of ensuring that the study design and measurements do not interfere with the building's existing operations.

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Publication Details

Journal
MethodsX
Published
2025-05-19
DOI
https://doi.org/10.1016/j.mex.2025.103378
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

A framework to evaluate the thermal and energy performance of smart building systems in existing buildings: A case study on automated interior insulating window shades

Brent Stephens, Mohammad Heidarinejad, Akram Syed Ali, Jongki Lee et al.
MethodsX
Building Energy and Comfort Optimization
article

A framework to evaluate the thermal and energy performance of smart building systems in existing buildings: A case study on automated interior insulating window shades

Brent Stephens, Mohammad Heidarinejad, Akram Syed Ali, Jongki Lee, Saman Haratian
article en

Abstract

This paper presents a methodological framework for evaluating the thermal and energy performance of smart building systems in existing buildings, with a focus on automated interior insulating window shades as an energy efficiency retrofit measure. The methodology is demonstrated through a case study of a high-rise building in which different shade control strategies were assessed. This paper provides comprehensive descriptions of the (i) development and implementation of the study design, (ii) selection and deployment of measurement instruments, (iii) analysis of various shade control strategies to quantify thermal and energy performance for heating, cooling, and ventilation energy end-uses, and (iv) quantification of the uncertainty associated with the measurements and calculations. This manuscript provides detailed, step-by-step and in-depth guidance to conduct such an evaluation. Overall, this paper:•Highlights the benefits, challenges, and limitations in conducting long-term measurements that capture realistic temporal, seasonal, and operational patterns in an occupied existing building.•Provides practical considerations for such measurements and analysis approaches, upon which future studies can build.•Emphasizes the importance of ensuring that the study design and measurements do not interfere with the building's existing operations.

MethodsXVol. 14
Illinois Institute of Technology (US)
American Society of Heating, Refrigerating and Air-Conditioning Engineers
Affordable and clean energy
Openalex Percentile: Top 89%
Building Energy and Comfort Optimization
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A framework to evaluate the thermal and energy performance of smart building systems in existing buildings: A case study on automated interior insulating window shades — Brent Stephens, Mohammad Heidarinejad, et al. · MethodsX (2025) | TGRS Research Map | TGRS