Skip to main content
SpringerLink
Log in

Dynamic Shading in Buildings: a Review of Testing Methods and Recent Research Findings

  • End-Use Efficiency (Y Wang, Section Editor)
  • Published:
Current Sustainable/Renewable Energy Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

The use of dynamically operated shading has been shown to provide energy savings and occupant visual and thermal comfort needs. As the literature in this area continues to grow, including development and evaluation of a range of shading devices, control strategies, and simulation and experimental test methods, a review is merited to assess the current state of the art.

Recent Findings

While roller shades and venetian blinds are most common, there are a growing number of additional shading types considered, as well as more complex control logic, some of which directly integrates occupant feedback. In addition, the majority of dynamic shading evaluation continues to be through simulation-based methods; however, there is an increasing amount of research using experimental methods. Some research has also explored combination simulation and experimental methods to simplify the number of sensors needed and associated complexity.

Summary

Improvements to control logic and ranges of test scenarios continue; however, there is still significant need for further studies in this area.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. US EIA. 2017. Available from: https://www.eia.gov/.

  2. ASHRAE. 1791 Tullie Circle, N.E., Atlanta G 30329. ASHRAE Handbook of Fundamentals. 2013.

  3. US EPA. US Environmental Protection Agency. 2017. Available from: http://www.epa.gov/

  4. Arasteh D, Selkowitz S, Apte J, LaFrance M. Zero energy windows. 2006 ACEEE Summer Study on Energy Efficiency in Buildings, Pacific Grove; 2006.

  5. O’Brien W, Kapsis K, Athienitis AK. Manually-operated window shade patterns in office buildings: a critical review. Build Environ. 2013;60:319–38. https://doi.org/10.1016/j.buildenv.2012.10.003.

    Article  Google Scholar 

  6. Yao J. An investigation into the impact of movable solar shades on energy, indoor thermal and visual comfort improvements. Build Environ. 2014;71:24–32. https://doi.org/10.1016/j.buildenv.2013.09.011.

    Article  Google Scholar 

  7. Karlsen L, Heiselberg P, Bryn I, Johra H. Solar shading control strategy for office buildings in cold climate. Energy Build. 2016;118:316–28. https://doi.org/10.1016/j.enbuild.2016.03.014.

    Article  Google Scholar 

  8. Carletti C, Sciurpi F, Pierangioli L, Asdrubali F, Pisello AL, Bianchi F, et al. Thermal and lighting effects of an external venetian blind: experimental analysis in a full scale test room. Build Environ. 2016;106:45–56. https://doi.org/10.1016/j.buildenv.2016.06.017.

    Article  Google Scholar 

  9. Eltaweel A, Su Y. Controlling venetian blinds based on parametric design; via implementing Grasshopper’s plugins: a case study of an office building in Cairo. Energy Build. 2017;139:31–43. https://doi.org/10.1016/j.enbuild.2016.12.075.

    Article  Google Scholar 

  10. Goovaerts C, Descamps F, Jacobs VA. Shading control strategy to avoid visual discomfort by using a low-cost camera: a field study of two cases. Build Environ. 2017;125:26–38. https://doi.org/10.1016/j.buildenv.2017.08.030.

    Article  Google Scholar 

  11. Karlsen L, Heiselberg P, Bryn I. Occupant satisfaction with two blind control strategies: slats closed and slats in cut-off position. Sol Energy. 2015;115:166–79. https://doi.org/10.1016/j.solener.2015.02.031.

    Article  Google Scholar 

  12. Katsifaraki A, Bueno B, Kuhn TE. A daylight optimized simulation-based shading controller for venetian blinds. Build Environ. 2017;126:207–20. https://doi.org/10.1016/j.buildenv.2017.10.003

  13. Sherif A, Sabry H, Wagdy A, Mashaly I, Arafa R. Shaping the slats of hospital patient room window blinds for daylighting and external view under desert clear skies. Sol Energy. 2016;133:1–13. https://doi.org/10.1016/j.solener.2016.03.053.

    Article  Google Scholar 

  14. Antunes HS. Daylight and energy performance of automated control strategies for interior roller shades. Master of science, NOVA University of Lisbon 2016.

  15. Singh R, Lazarus IJ, Kishore VVN. Effect of internal woven roller shade and glazing on the energy and daylighting performances of an office building in the cold climate of Shillong. Appl Energy. 2015;159:317–33. https://doi.org/10.1016/j.apenergy.2015.09.009.

    Article  Google Scholar 

  16. Firląg S, Yazdanian M, Curcija C, Kohler C, Vidanovic S, Hart R, et al. Control algorithms for dynamic windows for residential buildings. Energy Build. 2015;109:157–73. https://doi.org/10.1016/j.enbuild.2015.09.069.

    Article  Google Scholar 

  17. Xiong J, Tzempelikos A. Model-based shading and lighting controls considering visual comfort and energy use. Sol Energy. 2016;134:416–28. https://doi.org/10.1016/j.solener.2016.04.026.

    Article  Google Scholar 

  18. Yao J, Chow DHC, Zheng RY, Yan CW. Occupants’ impact on indoor thermal comfort: a co-simulation study on stochastic control of solar shades. J Build Perform Simul. 2016;9(3):272–87. https://doi.org/10.1080/19401493.2015.1046492.

    Article  Google Scholar 

  19. Huchuk B, Gunay HB, O’Brien W, Cruickshank CA. Model-based predictive control of office window shades. Build Res Inf. 2015;44(4):445–455. https://doi.org/10.1080/09613218.2016.1101949.

  20. GCJ S, Hviid CA, Svendsen S. The effect of dynamic solar shading on energy, daylighting and thermal comfort in a nearly zero-energy loft room in Rome and Copenhagen. Energy Build. 2017;135:302–11. https://doi.org/10.1016/j.enbuild.2016.11.053.

    Article  Google Scholar 

  21. Hoffmann S, Mcneil A, Lee E, Kalyanam R, Berkeley L, Road C. Discomfort glare with complex fenestration systems and the impact on energy use when using daylighting control. Proceedings of the 10th International Conference on Advanced Building Skins, Congress Center of Bern Expo, Bern, Switzerland, November 3‐4 2015.

  22. Palmero-Marrero AI, Oliveira AC. Effect of louver shading devices on building energy requirements. Appl Energy. 2010;87(6):2040–9. https://doi.org/10.1016/j.apenergy.2009.11.020.

    Article  Google Scholar 

  23. Elzeyadi I. The impacts of dynamic façade shading typologies on building energy performance and occupant’s multi-comfort. Archit Sci Rev. 2017;60(4):316–24. https://doi.org/10.1080/00038628.2017.1337558.

    Article  Google Scholar 

  24. Lai K, Wang W, Giles H. Solar shading performance of window with constant and dynamic shading function in different climate zones. Sol Energy 2017;147:113–125. doi:https://doi.org/10.1016/j.solener.2016.10.015

  25. Sun L, Hu W, Yuan Y, Cao X, Lei B. Dynamic performance of the shading-type building-integrated photovoltaic claddings. Procedia Eng. 2015;121:930–7. https://doi.org/10.1016/j.proeng.2015.09.053.

    Article  Google Scholar 

  26. Jayathissa P, Jansen M, Heeren N, Nagy Z, Schlueter A. Life cycle assessment of dynamic building integrated photovoltaics. Sol Energy Mater Sol Cells. 2016;156:75–82. https://doi.org/10.1016/j.solmat.2016.04.017.

    Article  Google Scholar 

  27. •• Chan YC, Tzempelikos A. Efficient venetian blind control strategies considering daylight utilization and glare protection. Sol Energy. 2013;98:241–54. https://doi.org/10.1016/j.solener.2013.10.005. This study utilizes various control strategies to control shading devices based on real-time glare simulation and pre-simulation in real buildings. Such simulation-based techniques have recently been used in other studies to create simulation-based controllers.

    Article  Google Scholar 

  28. Yun G, Park DY, Kim KS. Appropriate activation threshold of the external blind for visual comfort and lighting energy saving in different climate conditions. Build Environ. 2017;113:247–66. https://doi.org/10.1016/j.buildenv.2016.11.021.

    Article  Google Scholar 

  29. Yun G, Yoon KC, Kim KS. The influence of shading control strategies on the visual comfort and energy demand of office buildings. Energy Build. 2014;84:70–85. https://doi.org/10.1016/j.enbuild.2014.07.040.

    Article  Google Scholar 

  30. Sadeghi SA, Karava P, Konstantzos I, Tzempelikos A. Occupant interactions with shading and lighting systems using different control interfaces: a pilot field study. Build Environ. 2016;97:177–95. https://doi.org/10.1016/j.buildenv.2015.12.008.

    Article  Google Scholar 

  31. Meerbeek BW, de Bakker C, de Kort YAW, van Loenen EJ, Bergman T. Automated blinds with light feedback to increase occupant satisfaction and energy saving. Build Environ. 2016;103:70–85. https://doi.org/10.1016/j.buildenv.2016.04.002.

    Article  Google Scholar 

  32. • Motamed A, Deschamps L, Scartezzini JL. On-site monitoring and subjective comfort assessment of a sun shadings and electric lighting controller based on novel high dynamic range vision sensors. Energy Build. 2017;149:58–72. https://doi.org/10.1016/j.enbuild.2017.05.017. This study uses high dynamic range (HDR) imaging techniques for vision sensing technology to perform on-the-fly measurements of daylight glare probability (DGP) to control shading devices based on fuzzy logic. Previously, studies have used simplified DGP or sensor-based controls; thus, this method that calculates glare in real-time could hence have promising potential for improved shading control.

    Article  Google Scholar 

  33. Konstantzos I, Tzempelikos A. Daylight glare evaluation with the sun in the field of view through window shades. Build Environ. 2017;113:65–77. https://doi.org/10.1016/j.buildenv.2016.09.009.

    Article  Google Scholar 

  34. Allen K, Connelly K, Rutherford P, Wu Y. Smart windows—dynamic control of building energy performance. Energy Build. 2017;139:535–46. https://doi.org/10.1016/j.enbuild.2016.12.093.

    Article  Google Scholar 

  35. Singh R, Lazarus IJ, Kishore VVN. Uncertainty and sensitivity analyses of energy and visual performances of office building with external venetian blind shading in hot-dry climate. Appl Energy. 2016;184:155–70. https://doi.org/10.1016/j.apenergy.2016.10.007.

    Article  Google Scholar 

  36. Ahmad MW, Mourshed M, Hippolyte J. Optimising the scheduled operation of window blinds to enhance occupant comfort. Proceedings of BS2015: 14th Conference of International Building Performance Simulation Association, Hyderabad, India, Dec. 7-9, 2015;2393–400.

  37. Fasi MA, Budaiwi IM. Energy performance of windows in office buildings considering daylight integration and visual comfort in hot climates. Energy Build. 2015;108:307–16. https://doi.org/10.1016/j.enbuild.2015.09.024.

    Article  Google Scholar 

  38. Hoffmann S, Lee ES, McNeil A, Fernandes L, Vidanovic D, Thanachareonkit A. Balancing daylight, glare, and energy-efficiency goals: an evaluation of exterior coplanar shading systems using complex fenestration modeling tools. Energy Build. 2016;112:279–98. https://doi.org/10.1016/j.enbuild.2015.12.009.

    Article  Google Scholar 

  39. Iwata T, Taniguchi T, Sakuma R. Automated blind control based on glare prevention with dimmable light in open-plan offices. Build Environ. 2017;113:232–46. https://doi.org/10.1016/j.buildenv.2016.08.034.

    Article  Google Scholar 

  40. Gunay HB, O’Brien W, Beausoleil-Morrison I, Gilani S. Development and implementation of an adaptive lighting and blinds control algorithm. Build Environ. 2017;113:185–99. https://doi.org/10.1016/j.buildenv.2016.08.027.

    Article  Google Scholar 

  41. McNeil A. The five-phase method for simulating complex fenestration with radiance Lawrence Berkeley National Laboratory (LBNL) ,2013. https://windows.lbl.gov/sites/default/files/tutorial-fivephasemethod.pdf.

  42. Fernandes LL, Lee ES, McNeil A, Jonsson JC, Nouidui T, Pang X, et al. Angular selective window systems: assessment of technical potential for energy savings. Energy Build. 2015;90:188–206. https://doi.org/10.1016/j.enbuild.2014.10.010.

    Article  Google Scholar 

  43. McNeil A, Lee ES. A validation of the Radiance three-phase simulation method for modelling annual daylight performance of optically complex fenestration systems. J Build Perform Simul. 2012;6:24–37. Available from: http://eetd.lbl.gov/sites/all/files/publications/5606e.pdf

    Article  Google Scholar 

  44. Lawrence Berkeley National Laboratory. LBNL, Complex Glazing Database. 2014. Available from: http://windows.lbl.gov/software/CGDB/.

  45. Konstantzos I, Tzempelikos A, Chan YC. Experimental and simulation analysis of daylight glare probability in offices with dynamic window shades. Build Environ. 2015;87:244–54. https://doi.org/10.1016/j.buildenv.2015.02.007.

    Article  Google Scholar 

  46. DAYSIM Available from: http://daysim.ning.com/.

  47. Shen H, Tzempelikos A. Daylight-linked synchronized shading operation using simplified model-based control. Energy Build. 2017;145:200–12. https://doi.org/10.1016/j.enbuild.2017.04.021.

    Article  Google Scholar 

  48. Tzempelikos A, Chan YC. Estimating detailed optical properties of window shades from basic available data and modeling implications on daylighting and visual comfort. Energy Build. 2016;126:396–407. https://doi.org/10.1016/j.enbuild.2016.05.038.

    Article  Google Scholar 

  49. Tzempelikos A, Athienitis AK. The impact of shading design and control on building cooling and lighting demand. Sol Energy. 2007;81(3):369–82. https://doi.org/10.1016/j.solener.2006.06.015.

    Article  Google Scholar 

  50. EnergyPlus. U.S. Department of Energy Building Technology Office. Available from: https://energyplus.net/.

  51. Rhinoceros Robert McNeel & Associates. Available from: https://www.rhino3d.com/.

  52. ISE VE Available from: https://www.iesve.com/software.

  53. Manzan M, Clarich A. Multi-criteria energy and daylight optimization of an office with fixed and movable shading devices. Advances in Building Energy Research,2015;9(2):238–52. https://doi.org/10.1080/17512549.2015.1014839.

  54. Sadeghi SA, Awalgaonkar NM, Karava P, Bilionis I. A Bayesian modeling approach of human interactions with shading and electric lighting systems in private offices. Energy Build. 2017;134:185–201. https://doi.org/10.1016/j.enbuild.2016.10.046.

    Article  Google Scholar 

  55. Bakker LG, Hoes-van Oeffelen ECM, Loonen RCGM, Hensen JLM. User satisfaction and interaction with automated dynamic facades: a pilot study. Build Environ. 2014;78:44–52. https://doi.org/10.1016/j.buildenv.2014.04.007.

    Article  Google Scholar 

  56. Huang KT, Liu KFR, Liang HH. Design and energy performance of a buoyancy driven exterior shading device for building application in Taiwan. Energies. 2015;8(4):2358–80. https://doi.org/10.3390/en8042358.

    Article  Google Scholar 

  57. O’Brien W, Gunay HB. Mitigating office performance uncertainty of occupant use of window blinds and lighting using robust design. Build Simul. 2015;8(6):621–36. https://doi.org/10.1007/s12273-015-0239-2.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Iowa State University, 813 Bissell Road, Ames, IA, 50011, USA

    Niraj Kunwar

  2. Iowa State University, 813 Bissell Road, 428 Town Engineering, Ames, IA, 50011, USA

    Kristen S. Cetin

  3. Iowa State University, 491 Design, Ames, IA, 50011, USA

    Ulrike Passe

Authors
  1. Niraj Kunwar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kristen S. Cetin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ulrike Passe
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Niraj Kunwar.

Ethics declarations

Conflict of Interest

Niraj Kunwar, Kristen S. Cetin, and Ulrike Passe have received funds from the grant ASHRAE RP-1710 - Effect of Dynamic Shading Devices on Daylighting and Energy Performance of Perimeter Zones.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

This article is part of the Topical Collection on End-Use Efficiency

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kunwar, N., Cetin, K.S. & Passe, U. Dynamic Shading in Buildings: a Review of Testing Methods and Recent Research Findings. Curr Sustainable Renewable Energy Rep 5, 93–100 (2018). https://doi.org/10.1007/s40518-018-0103-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40518-018-0103-y

Keywords

Search

Navigation