Book/Dissertation / PhD Thesis FZJ-2024-06140

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Optimizing Automated Shading Systems in Office Buildings by Exploring Occupant Behaviour



2024
Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag Jülich
ISBN: 978-3-95806-787-5

Jülich : Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag, IAS Series 67, 9, x, 168, ccxxiii () [10.34734/FZJ-2024-06140] = Dissertation, Wuppertal University, 2022

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Abstract: Automated shading systems represent a promising solution for improving indoor thermal and visual conditions as well as saving energy. However, previous studies indicate that many existing automated shading systems fail to improve occupants’ visual comfort and reduce the energy use as intended in the design phase. Thus, occupants frequently override or disable these systems, indicating their discomfort or desire for a customized indoor environment. Therefore, neglecting occupants’ needs and expectations in the building design and operation process may cause discrepancies between the predicted and actual energy performance and sub-optimal design decision-making. To address this issue, this research aims to explore and evaluate the use and function of automated shading systems in office environments for optimizing automated shading system design and operation in existing and new buildings. To achieve the objectives of this research, three phases were completed. In Phase 01, the current practice of automated shading design and operation was investigated in 19 case studies through a questionnaire. The commonly-used shading setpoints were identified and tested. The performance of two commercial shading control devices was examined by an experimental and field studies. Results indicate that commercial devices’ limited quality and accuracy for automatic shading control could be due to economic constraints and sensors’ positions or inclinations. Therefore, designers may consider other design strategies such as an intermediate blind position or combined internal/external shading systems. In Phase 02, an experimental study was conducted in a full-scale test cell to evaluate the performance of an automated shading system in terms of user behaviour and acceptance, thermal and visual comfort under six scenarios. After each scenario, a self-reported questionnaire was completed by the participant. Indoor and outdoor environmental parameters, user and system-triggered adjustments were recorded. Different performance indicators were used. The key findings suggest that a robust shading system (i.e., few override actions) can be achieved by: a multi-objective control strategy with an intermediate position, an acceptable range of irradiance thresholds, and a decent level of adaptive control options over the workplace. Phase 03 introduces a field study, including design investigation, data monitoring, a questionnaire, and simulation-based analysis. The study focused on using automated shading systems in a real office building to derive occupant-centric rules for optimal shading design. The monitored data and questionnaire analysis showed similar results, a relatively few interactions between the occupants and the shadings systems. The statistical analysis of the monitored data showed the limited approach of the regression model used in this study, while data mining techniques showed advantages in exploring occupant behavioural patterns. The extracted lessons for designers and researchers include: the use of double shading systems (internal/external) can improve user satisfaction of automated shading systems (i.e., few override actions), the definition of control thresholds is essential, and the deployment of light sensors is beneficial.


Note: Dissertation, Wuppertal University, 2022

Contributing Institute(s):
  1. Zivile Sicherheitsforschung (IAS-7)
  2. Modellierung von Energiesystemen (ICE-1)
Research Program(s):
  1. 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) (POF4-511)

Appears in the scientific report 2024
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Creative Commons Attribution CC BY 4.0 ; OpenAccess
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Institute Collections > IAS > IAS-7
Institute Collections > ICE > ICE-1
Document types > Theses > Ph.D. Theses
Document types > Books > Books
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 Record created 2024-11-07, last modified 2025-01-06


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