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Optimal Control Strategies for Switchable Transparent Insulation Systems Applied to Smart Windows for US Residential Buildings

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  • Mohammad Dabbagh

    (Civil, Environmental, and Architectural Engineering Department, University of Colorado Boulder, Boulder, CO 80309, USA)

  • Moncef Krarti

    (Civil, Environmental, and Architectural Engineering Department, University of Colorado Boulder, Boulder, CO 80309, USA)

Abstract

This paper evaluates the potential energy use and peak demand savings associated with optimal controls of switchable transparent insulation systems (STIS) applied to smart windows for US residential buildings. The optimal controls are developed based on Genetic Algorithm (GA) to identify the automatic settings of the dynamic shades. First, switchable insulation systems and their operation mechanisms are briefly described when combined with smart windows. Then, the GA-based optimization approach is outlined to operate switchable insulation systems applied to windows for a prototypical US residential building. The optimized controls are implemented to reduce heating and cooling energy end-uses for a house located four US locations, during three representative days of swing, summer, and winter seasons. The performance of optimal controller is compared to that obtained using simplified rule-based control sets to operate the dynamic insulation systems. The analysis results indicate that optimized controls of STISs can save up to 81.8% in daily thermal loads compared to the simplified rule-set especially when dwellings are located in hot climates such as that of Phoenix, AZ. Moreover, optimally controlled STISs can reduce electrical peak demand by up to 49.8% compared to the simplified rule-set, indicating significant energy efficiency and demand response potentials of the SIS technology when applied to US residential buildings.

Suggested Citation

  • Mohammad Dabbagh & Moncef Krarti, 2021. "Optimal Control Strategies for Switchable Transparent Insulation Systems Applied to Smart Windows for US Residential Buildings," Energies, MDPI, vol. 14(10), pages 1-24, May.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:10:p:2917-:d:556922
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    References listed on IDEAS

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    1. Evins, Ralph, 2013. "A review of computational optimisation methods applied to sustainable building design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 230-245.
    2. Tian, Wei, 2013. "A review of sensitivity analysis methods in building energy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 411-419.
    3. Casini, Marco, 2018. "Active dynamic windows for buildings: A review," Renewable Energy, Elsevier, vol. 119(C), pages 923-934.
    4. Reynolds, Jonathan & Rezgui, Yacine & Kwan, Alan & Piriou, Solène, 2018. "A zone-level, building energy optimisation combining an artificial neural network, a genetic algorithm, and model predictive control," Energy, Elsevier, vol. 151(C), pages 729-739.
    5. DeForest, Nicholas & Shehabi, Arman & Selkowitz, Stephen & Milliron, Delia J., 2017. "A comparative energy analysis of three electrochromic glazing technologies in commercial and residential buildings," Applied Energy, Elsevier, vol. 192(C), pages 95-109.
    6. Nundy, Srijita & Ghosh, Aritra, 2020. "Thermal and visual comfort analysis of adaptive vacuum integrated switchable suspended particle device window for temperate climate," Renewable Energy, Elsevier, vol. 156(C), pages 1361-1372.
    7. Jae-Hyang Kim & Jongin Hong & Seung-Hoon Han, 2021. "Optimized Physical Properties of Electrochromic Smart Windows to Reduce Cooling and Heating Loads of Office Buildings," Sustainability, MDPI, vol. 13(4), pages 1-30, February.
    8. Nguyen, Anh-Tuan & Reiter, Sigrid & Rigo, Philippe, 2014. "A review on simulation-based optimization methods applied to building performance analysis," Applied Energy, Elsevier, vol. 113(C), pages 1043-1058.
    9. Cho, Sung-Hwan & Shin, Kee-Shik & Zaheer-Uddin, M., 1995. "The effect of slat angle of windows with venetian blinds on heating and cooling loads of buildings in South Korea," Energy, Elsevier, vol. 20(12), pages 1225-1236.
    10. Ghosh, Aritra & Norton, Brian, 2019. "Optimization of PV powered SPD switchable glazing to minimise probability of loss of power supply," Renewable Energy, Elsevier, vol. 131(C), pages 993-1001.
    Full references (including those not matched with items on IDEAS)

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