Optimal energy performance of dynamic sliding and insulated shades for residential buildings
Introduction
In the US, buildings consumed 39% of total primary energy use with heating and cooling equipment accounting for a significant portion of this energy needed to maintain indoor thermal comfort [1]. US Department of Energy (DOE) estimated that windows are responsible directly for 10% of energy use in buildings and affect indirectly other end-uses such heating, cooling lighting, fans, and pumps which account for 40% of total US buildings' energy consumption [2]. Specifically, windows affect thermal performance of buildings through several mechanisms heat transmission (i.e., conduction and convection through the glazing layers), air infiltration (i.e., uncontrolled airflow through cracks around the windows’ frames), and solar heat gains (i.e., solar radiation transmitted through the transparent glazing). In addition, windows affect natural light aperture and consequently the use of electrical lighting based on daylighting controls. In the last decades, significant efforts have been made to improve the energy performance of windows using thin triple or vacuum-insulated glazing [3], high-performing inert gas fills [4], insulating frames [5], switchable or dynamic glazing [6]. While high performance windows can be implemented in new constructions, the replacement of existing windows are generally expensive and not cost-effective. Therefore, low-cost technologies to improve the energy efficiency of windows suitable for existing buildings are still required especially for US housing units [7]. Indeed, recent DOE predictions indicate that only third of residential units will be replaced by 2050 compared to more than half for the commercial buildings [7].
As alternatives to high-performance windows, static and dynamic attachments can be effective to reduce energy use of buildings. Indeed, external and internal shading systems can reduce air conditioning needs for buildings by managing solar heat gains from windows including overhangs [8], external roller shades [9], and venetian blinds [10,11]. Automated controls for interior shades have been evaluated extensively in the literature. In particular, several studies have shown that interior shading systems with automatic controls have the potential to reduce significantly energy use of buildings compared to static or manually operated systems [[12], [13], [14], [15]]. Through a controlled laboratory experimental analysis, dynamic roller shades found to reduce heating and cooling energy use by 26% compared to no-shading option [12]. The effectiveness of simplified control schemes in balancing visual and thermal performance for automatic roller shades has been evaluated both through modeling analysis and experimental testing [13] for office spaces [14]. Moreover, Tan et al. [15] modeled the impacts of dynamic roller shades on energy demand of residential buildings using equivalent shading schedules. Their analysis indicated that the shading performance vary significantly and can result in a decrease of up to 14.2% and an increase of up to 22.2% in the annual energy heating and cooling demand [15].
However, some simulation and experimental based analyses have indicated that exterior shades provide more energy benefits than interior blinds [16] including better management of solar gains [17] and higher reduction in air conditioning needs [18]. Limited analyses have been reported for dynamic external shading systems for buildings [[19], [20], [21], [22]]. For instance, Vlachokostas and Madamopoulos [21] evaluated the energy efficiency potential of using dynamic shading devices by adjusting the direct and diffuse solar radiation data in the weather file. Using a simulation-based analysis for an office space in New York City, NY, they found that dynamic shading devices reduce annual energy use by 33%–36% if controlled on an hourly basis [21]. Rotating overhangs with the ability to be adjusted continuously are estimated to save 9.5% of annual heating and cooling needs for a home located in Chicago, IL, when compared to the baseline case with no-overhangs [22]. On the other hand, static overhangs applied to the same home would increase the heating and cooling energy use by 6.8% relative to the baseline [22].
However, automatically operated dynamic shading systems have limited market adoption due to several factors including high costs and complexity of operation [7]. Moreover, the lack of optimized and yet simple controls is not readily available and proven [7]. In this paper, low-cost dynamic and insulating shading systems suitable to be controlled automatically to manage solar heat gains as well as to enhance the thermal performance of windows are described and evaluated. The dynamic shading systems can be deployed for new and existing residential and commercial buildings to minimize cooling and heating thermal loads. First, the basic design features and operation strategies of the dynamic shading systems are introduced. Then, the modeling approach is outlined including the characteristics of the housing unit considered in the analysis. Finally, the results of a series of sensitivity analyses are discussed to assess the performance of the dynamic shading systems for various operation scenarios, design features, and climate conditions.
Section snippets
Analysis approach
The analysis methodology used in this study is presented in this section to assess the optimal energy performance of external dynamic shading systems that can be deployed for new and existing for buildings. First, the design configurations and operation strategies of the proposed dynamic shades are described in this section. In addition, the building energy model and simulation tool used throughout the analyses are defined.
Discussion of results
The results of the initial analysis to assess the energy performance of static and dynamic sliding shades are summarized in this section when the housing unit is located in Boulder, CO. The impacts of various design and operating conditions on the optimal performance of dynamic shades are evaluated in Section 4 using a series of sensitivity analyses to account for factors such window size, unit orientation, and US climate.
The analysis in this study aims at evaluating control strategies for the
Sensitivity analyses
In this section, results from a series of sensitivity analyses are presented to assess the impact of design and operating conditions on the energy performance of the dynamic sliding shades. Specifically, the annual energy performance of dynamic shades is evaluated for various window sizes, window orientations, glazing types, insulation levels, and US climates.
Summary and conclusions
The study outlined in this paper considers the energy performance evaluation of novel dynamic shades made-up of insulated sliding panels suitable to manage solar heat gains as needed on hourly, daily, or monthly basis. Several operation options for the dynamic shades are considered in the evaluation including continuous and stepped controls. The analysis presented in this paper investigated the energy performance of the dynamic shades when applied to apartment housing units located in various
Author contribution
Moncef Krarti: Conceptualization, Investigation, Data curation, Software, Methodology, Validation, writing, and Editing.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
References (41)
- et al.
Energy and visual comfort performance of electro-chromic windows with overhangs
Build Environ
(2007) - et al.
The impact of shading design and control on building cooling and lighting demand
Sol Energy
(2007) - et al.
Thermal and daylighting performance of an automated Venetian blind and lighting system in a full-scale private office
Energy Build
(1998) - et al.
Energy balance calculation of window glazing's in the northern latitudes using long-term measured climatic data
Energy Convers Manag
(2015) - et al.
Full-scale experimental testing of integrated dynamically-operated roller shades and lighting in perimeter office spaces
Sol Energy
(2019) - et al.
Daylight-linked synchronized shading operation using simplified model-based control
Energy Build
(2017) - et al.
Study on the impact of window shades' physical characteristics and opening modes on air conditioning energy consumption in China
Energy Built Environ..
(2020) - et al.
Comparative advantage of an exterior shading device in thermal performance for residential buildings
Energy Build
(2012) - et al.
Internal versus external shading devices performance in office buildings
Energy Proc
(2014) - et al.
Comparative advantage of an exterior shading device in thermal performance for residential buildings
Energy Build
(2012)
Quantifying the potential of automated dynamic solar shading in office buildings through integrated simulations of energy and daylight
Sol Energy
The energy savings potential of using dynamic external louvers in an office building
Energy Build
Quantification of energy savings from dynamic solar radiation regulation strategies in office buildings
Energy Build
Evaluation of energy performance of dynamic overhang systems for US residential buildings
Energy Build
Performance of PV integrated dynamic overhangs applied to US homes
Dynamic operation of daylighting and shading systems: a literature review
Renew Sustain Energy Rev
Parametric behavior maps: a method for evaluating the energy performance of climate-adaptive building envelopes
Energy Build
Evaluation of PV integrated sliding-rotating overhangs for US apartment buildings
Appl Energy
Comparison of DOE-2 with temperature measurements in the Pala test houses
Energy Build
An empirical validation of the daylighting algorithms and associated interactions in building energy simulation programs using various shading devices and windows
Energy
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