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Stochastic Characteristics of Manual Solar Shades and their Influence on Building Energy Performance

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  • Jian Yao

    (Faculty of Architectural, Civil Engineering and Environment, Ningbo University, Ningbo 315211, China)

  • Rongyue Zheng

    (Faculty of Architectural, Civil Engineering and Environment, Ningbo University, Ningbo 315211, China)

Abstract

Occupant behavior has a significant impact on building energy performance. The purpose of this paper is to quantify the stochastic characteristics of manual solar shades and their influence on building energy performance. A co-simulation for occupants’ stochastic control of manual solar shades was conducted and the statistic indicators (non-parameter tests and autocorrelation function) were calculated in order to identify potential occupant behavior patterns. The results show that occupants’ stochastic shade control behavior among different seasons is not statistically different and that shade control behavior is not completely stochastic. Meanwhile, the trend in the fluctuation of Sc changes with time. Furthermore, a new index was introduced to evaluate the effectiveness of manual solar shades in terms of energy performance. The result shows that the effectiveness of manual solar shades is only between 39.8% and 81.3%, compared with automatically controlled shades, and there is a large potential for improving the effectiveness of manual solar shades in different seasons.

Suggested Citation

  • Jian Yao & Rongyue Zheng, 2017. "Stochastic Characteristics of Manual Solar Shades and their Influence on Building Energy Performance," Sustainability, MDPI, vol. 9(6), pages 1-15, June.
  • Handle: RePEc:gam:jsusta:v:9:y:2017:i:6:p:1070-:d:102098
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    References listed on IDEAS

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    1. Méndez Echenagucia, Tomás & Capozzoli, Alfonso & Cascone, Ylenia & Sassone, Mario, 2015. "The early design stage of a building envelope: Multi-objective search through heating, cooling and lighting energy performance analysis," Applied Energy, Elsevier, vol. 154(C), pages 577-591.
    2. Beckman, William A. & Broman, Lars & Fiksel, Alex & Klein, Sanford A. & Lindberg, Eva & Schuler, Mattias & Thornton, Jeff, 1994. "TRNSYS The most complete solar energy system modeling and simulation software," Renewable Energy, Elsevier, vol. 5(1), pages 486-488.
    3. Marinakis, Vangelis & Doukas, Haris & Karakosta, Charikleia & Psarras, John, 2013. "An integrated system for buildings’ energy-efficient automation: Application in the tertiary sector," Applied Energy, Elsevier, vol. 101(C), pages 6-14.
    4. Sun, Liangliang & Lu, Lin & Yang, Hongxing, 2012. "Optimum design of shading-type building-integrated photovoltaic claddings with different surface azimuth angles," Applied Energy, Elsevier, vol. 90(1), pages 233-240.
    5. Datta, Gouri, 2001. "Effect of fixed horizontal louver shading devices on thermal perfomance of building by TRNSYS simulation," Renewable Energy, Elsevier, vol. 23(3), pages 497-507.
    6. Yao, Jian, 2014. "Determining the energy performance of manually controlled solar shades: A stochastic model based co-simulation analysis," Applied Energy, Elsevier, vol. 127(C), pages 64-80.
    7. Jian Yao & David Hou Chi Chow & Yu-Wei Chi, 2016. "Impact of Manually Controlled Solar Shades on Indoor Visual Comfort," Sustainability, MDPI, vol. 8(8), pages 1-19, July.
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