IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v207y2017icp305-323.html
   My bibliography  Save this article

Energy efficient HVAC control for an IPS-enabled large space in commercial buildings through dynamic spatial occupancy distribution

Author

Listed:
  • Wang, Wei
  • Chen, Jiayu
  • Huang, Gongsheng
  • Lu, Yujie

Abstract

Since commercial and residential buildings have become the largest energy consumers across all sectors, building energy efficiency has attracted increasing attention in recent years. Many studies suggest occupancy detection is critical in promoting building energy efficiency because it is premised on the idea of avoiding unnecessary waste while providing sufficient service. In this paper, we propose the integration of an iBeacon-enabled indoor positioning system (IPS) and a Variable Air Volume (VAV) heating, ventilation, and air-conditioning (HVAC) system to optimize system control and save energy based on high-resolution occupancy detection. The proposed system aims to match thermal service with the spatial distribution of occupants and redefine occupancy as a dynamic spatial occupancy distribution (DSOD) occupancy matrix. For this reason, this paper proposes measuring spatial occupancy by meshing large indoor spaces into zones and patches, and uses a feature-scaled artificial neural network algorithm to map the spatial IPS signal patterns. After acquiring the detailed spatial distribution, we also developed a ventilation control mechanism based on occupancy distribution. To validate the proposed control mechanism, we compared it with other traditional controllers in an on-site experiment and through a computational fluid dynamics (CFD) simulation. The results suggest that a 20% energy saving potential can be realized when the proposed approach is properly implemented.

Suggested Citation

  • Wang, Wei & Chen, Jiayu & Huang, Gongsheng & Lu, Yujie, 2017. "Energy efficient HVAC control for an IPS-enabled large space in commercial buildings through dynamic spatial occupancy distribution," Applied Energy, Elsevier, vol. 207(C), pages 305-323.
    • Handle: RePEc:eee:appene:v:207:y:2017:i:c:p:305-323
    DOI: 10.1016/j.apenergy.2017.06.060
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917308139
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2017.06.060?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Siano, Pierluigi, 2014. "Demand response and smart grids—A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 461-478.
    2. Xu, Xiaoqi & Culligan, Patricia J. & Taylor, John E., 2014. "Energy Saving Alignment Strategy: Achieving energy efficiency in urban buildings by matching occupant temperature preferences with a building’s indoor thermal environment," Applied Energy, Elsevier, vol. 123(C), pages 209-219.
    3. Azar, Elie & Al Ansari, Hamad, 2017. "Framework to investigate energy conservation motivation and actions of building occupants: The case of a green campus in Abu Dhabi, UAE," Applied Energy, Elsevier, vol. 190(C), pages 563-573.
    4. Chen, Jiayu & Jain, Rishee K. & Taylor, John E., 2013. "Block Configuration Modeling: A novel simulation model to emulate building occupant peer networks and their impact on building energy consumption," Applied Energy, Elsevier, vol. 105(C), pages 358-368.
    5. Li, Nan & Yang, Zheng & Becerik-Gerber, Burcin & Tang, Chao & Chen, Nanlin, 2015. "Why is the reliability of building simulation limited as a tool for evaluating energy conservation measures?," Applied Energy, Elsevier, vol. 159(C), pages 196-205.
    6. Gruber, J.K. & Huerta, F. & Matatagui, P. & Prodanović, M., 2015. "Advanced building energy management based on a two-stage receding horizon optimization," Applied Energy, Elsevier, vol. 160(C), pages 194-205.
    7. Chung, William & Hui, Y.V. & Lam, Y. Miu, 2006. "Benchmarking the energy efficiency of commercial buildings," Applied Energy, Elsevier, vol. 83(1), pages 1-14, January.
    8. Menezes, Anna Carolina & Cripps, Andrew & Bouchlaghem, Dino & Buswell, Richard, 2012. "Predicted vs. actual energy performance of non-domestic buildings: Using post-occupancy evaluation data to reduce the performance gap," Applied Energy, Elsevier, vol. 97(C), pages 355-364.
    9. Oldewurtel, Frauke & Sturzenegger, David & Morari, Manfred, 2013. "Importance of occupancy information for building climate control," Applied Energy, Elsevier, vol. 101(C), pages 521-532.
    10. Goyal, Siddharth & Ingley, Herbert A. & Barooah, Prabir, 2013. "Occupancy-based zone-climate control for energy-efficient buildings: Complexity vs. performance," Applied Energy, Elsevier, vol. 106(C), pages 209-221.
    11. Korkas, Christos D. & Baldi, Simone & Michailidis, Iakovos & Kosmatopoulos, Elias B., 2015. "Intelligent energy and thermal comfort management in grid-connected microgrids with heterogeneous occupancy schedule," Applied Energy, Elsevier, vol. 149(C), pages 194-203.
    12. Zhao, Hai-xiang & Magoulès, Frédéric, 2012. "A review on the prediction of building energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3586-3592.
    13. Woradechjumroen, Denchai & Yu, Yuebin & Li, Haorong, 2016. "Virtual partition surface temperature sensor based on linear parametric model," Applied Energy, Elsevier, vol. 162(C), pages 1323-1335.
    14. Abu Bakar, Nur Najihah & Hassan, Mohammad Yusri & Abdullah, Hayati & Rahman, Hasimah Abdul & Abdullah, Md Pauzi & Hussin, Faridah & Bandi, Masilah, 2015. "Energy efficiency index as an indicator for measuring building energy performance: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 1-11.
    15. Zeng, Yaohui & Zhang, Zijun & Kusiak, Andrew, 2015. "Predictive modeling and optimization of a multi-zone HVAC system with data mining and firefly algorithms," Energy, Elsevier, vol. 86(C), pages 393-402.
    16. Pisello, Anna Laura & Asdrubali, Francesco, 2014. "Human-based energy retrofits in residential buildings: A cost-effective alternative to traditional physical strategies," Applied Energy, Elsevier, vol. 133(C), pages 224-235.
    17. Liang, Xin & Hong, Tianzhen & Shen, Geoffrey Qiping, 2016. "Improving the accuracy of energy baseline models for commercial buildings with occupancy data," Applied Energy, Elsevier, vol. 179(C), pages 247-260.
    18. Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
    19. Ueno, Tsuyoshi & Sano, Fuminori & Saeki, Osamu & Tsuji, Kiichiro, 2006. "Effectiveness of an energy-consumption information system on energy savings in residential houses based on monitored data," Applied Energy, Elsevier, vol. 83(2), pages 166-183, February.
    20. Wang, Qinpeng & Augenbroe, Godfried & Kim, Ji-Hyun & Gu, Li, 2016. "Meta-modeling of occupancy variables and analysis of their impact on energy outcomes of office buildings," Applied Energy, Elsevier, vol. 174(C), pages 166-180.
    21. Rana, Rajib & Kusy, Brano & Wall, Josh & Hu, Wen, 2015. "Novel activity classification and occupancy estimation methods for intelligent HVAC (heating, ventilation and air conditioning) systems," Energy, Elsevier, vol. 93(P1), pages 245-255.
    22. Korkas, Christos D. & Baldi, Simone & Michailidis, Iakovos & Kosmatopoulos, Elias B., 2016. "Occupancy-based demand response and thermal comfort optimization in microgrids with renewable energy sources and energy storage," Applied Energy, Elsevier, vol. 163(C), pages 93-104.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Panagiotis Michailidis & Iakovos Michailidis & Dimitrios Vamvakas & Elias Kosmatopoulos, 2023. "Model-Free HVAC Control in Buildings: A Review," Energies, MDPI, vol. 16(20), pages 1-45, October.
    2. Wei, Shuangyu & Tien, Paige Wenbin & Calautit, John Kaiser & Wu, Yupeng & Boukhanouf, Rabah, 2020. "Vision-based detection and prediction of equipment heat gains in commercial office buildings using a deep learning method," Applied Energy, Elsevier, vol. 277(C).
    3. Peng, Yuzhen & Rysanek, Adam & Nagy, Zoltán & Schlüter, Arno, 2018. "Using machine learning techniques for occupancy-prediction-based cooling control in office buildings," Applied Energy, Elsevier, vol. 211(C), pages 1343-1358.
    4. Jin Dong & Christopher Winstead & James Nutaro & Teja Kuruganti, 2018. "Occupancy-Based HVAC Control with Short-Term Occupancy Prediction Algorithms for Energy-Efficient Buildings," Energies, MDPI, vol. 11(9), pages 1-20, September.
    5. Jung, Wooyoung & Jazizadeh, Farrokh, 2019. "Human-in-the-loop HVAC operations: A quantitative review on occupancy, comfort, and energy-efficiency dimensions," Applied Energy, Elsevier, vol. 239(C), pages 1471-1508.
    6. Mpho J. Lencwe & SP Daniel Chowdhury & Sipho Mahlangu & Maxwell Sibanyoni & Louwrance Ngoma, 2021. "An Efficient HVAC Network Control for Safety Enhancement of a Typical Uninterrupted Power Supply Battery Storage Room," Energies, MDPI, vol. 14(16), pages 1-23, August.
    7. Zhang, Sheng & Cheng, Yong & Liu, Jian & Lin, Zhang, 2019. "Subzone control optimization of air distribution for thermal comfort and energy efficiency under cooling load uncertainty," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    8. Baldi, Simone & Korkas, Christos D. & Lv, Maolong & Kosmatopoulos, Elias B., 2018. "Automating occupant-building interaction via smart zoning of thermostatic loads: A switched self-tuning approach," Applied Energy, Elsevier, vol. 231(C), pages 1246-1258.
    9. Soltanaghaei, Elahe & Whitehouse, Kamin, 2018. "Practical occupancy detection for programmable and smart thermostats," Applied Energy, Elsevier, vol. 220(C), pages 842-855.
    10. Wang, Wei & Hong, Tianzhen & Li, Nan & Wang, Ryan Qi & Chen, Jiayu, 2019. "Linking energy-cyber-physical systems with occupancy prediction and interpretation through WiFi probe-based ensemble classification," Applied Energy, Elsevier, vol. 236(C), pages 55-69.
    11. Zhang, Sheng & Cheng, Yong & Oladokun, Majeed Olaide & Huan, Chao & Lin, Zhang, 2019. "Heat removal efficiency of stratum ventilation for air-side modulation," Applied Energy, Elsevier, vol. 238(C), pages 1237-1249.
    12. Rashid, Syed Aftab & Haider, Zeeshan & Chapal Hossain, S.M. & Memon, Kashan & Panhwar, Fazil & Mbogba, Momoh Karmah & Hu, Peng & Zhao, Gang, 2019. "Retrofitting low-cost heating ventilation and air-conditioning systems for energy management in buildings," Applied Energy, Elsevier, vol. 236(C), pages 648-661.
    13. Wang, Wei & Hong, Tianzhen & Xu, Xiaodong & Chen, Jiayu & Liu, Ziang & Xu, Ning, 2019. "Forecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm," Applied Energy, Elsevier, vol. 248(C), pages 217-230.
    14. Pal, Monalisa & Alyafi, Amr Alzouhri & Ploix, Stéphane & Reignier, Patrick & Bandyopadhyay, Sanghamitra, 2019. "Unmasking the causal relationships latent in the interplay between occupant’s actions and indoor ambience: A building energy management outlook," Applied Energy, Elsevier, vol. 238(C), pages 1452-1470.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Wei & Hong, Tianzhen & Li, Nan & Wang, Ryan Qi & Chen, Jiayu, 2019. "Linking energy-cyber-physical systems with occupancy prediction and interpretation through WiFi probe-based ensemble classification," Applied Energy, Elsevier, vol. 236(C), pages 55-69.
    2. Baldi, Simone & Yuan, Shuai & Endel, Petr & Holub, Ondrej, 2016. "Dual estimation: Constructing building energy models from data sampled at low rate," Applied Energy, Elsevier, vol. 169(C), pages 81-92.
    3. Soltanaghaei, Elahe & Whitehouse, Kamin, 2018. "Practical occupancy detection for programmable and smart thermostats," Applied Energy, Elsevier, vol. 220(C), pages 842-855.
    4. Song, Kwonsik & Kim, Sooyoung & Park, Moonseo & Lee, Hyun-Soo, 2017. "Energy efficiency-based course timetabling for university buildings," Energy, Elsevier, vol. 139(C), pages 394-405.
    5. Baldi, Simone & Korkas, Christos D. & Lv, Maolong & Kosmatopoulos, Elias B., 2018. "Automating occupant-building interaction via smart zoning of thermostatic loads: A switched self-tuning approach," Applied Energy, Elsevier, vol. 231(C), pages 1246-1258.
    6. Pisello, Anna Laura & Asdrubali, Francesco, 2014. "Human-based energy retrofits in residential buildings: A cost-effective alternative to traditional physical strategies," Applied Energy, Elsevier, vol. 133(C), pages 224-235.
    7. Song, Kwonsik & Jang, Youjin & Park, Moonseo & Lee, Hyun-Soo & Ahn, Joseph, 2020. "Energy efficiency of end-user groups for personalized HVAC control in multi-zone buildings," Energy, Elsevier, vol. 206(C).
    8. Fujimi, Toshio & Kajitani, Yoshio & Chang, Stephanie E., 2016. "Effective and persistent changes in household energy-saving behaviors: Evidence from post-tsunami Japan," Applied Energy, Elsevier, vol. 167(C), pages 93-106.
    9. Rashid, Syed Aftab & Haider, Zeeshan & Chapal Hossain, S.M. & Memon, Kashan & Panhwar, Fazil & Mbogba, Momoh Karmah & Hu, Peng & Zhao, Gang, 2019. "Retrofitting low-cost heating ventilation and air-conditioning systems for energy management in buildings," Applied Energy, Elsevier, vol. 236(C), pages 648-661.
    10. Yang, Zheng & Ghahramani, Ali & Becerik-Gerber, Burcin, 2016. "Building occupancy diversity and HVAC (heating, ventilation, and air conditioning) system energy efficiency," Energy, Elsevier, vol. 109(C), pages 641-649.
    11. Korkas, Christos D. & Baldi, Simone & Michailidis, Iakovos & Kosmatopoulos, Elias B., 2016. "Occupancy-based demand response and thermal comfort optimization in microgrids with renewable energy sources and energy storage," Applied Energy, Elsevier, vol. 163(C), pages 93-104.
    12. Nutkiewicz, Alex & Yang, Zheng & Jain, Rishee K., 2018. "Data-driven Urban Energy Simulation (DUE-S): A framework for integrating engineering simulation and machine learning methods in a multi-scale urban energy modeling workflow," Applied Energy, Elsevier, vol. 225(C), pages 1176-1189.
    13. Korkas, Christos D. & Baldi, Simone & Michailidis, Iakovos & Kosmatopoulos, Elias B., 2015. "Intelligent energy and thermal comfort management in grid-connected microgrids with heterogeneous occupancy schedule," Applied Energy, Elsevier, vol. 149(C), pages 194-203.
    14. Azar, Elie & Nikolopoulou, Christina & Papadopoulos, Sokratis, 2016. "Integrating and optimizing metrics of sustainable building performance using human-focused agent-based modeling," Applied Energy, Elsevier, vol. 183(C), pages 926-937.
    15. Naylor, Sophie & Gillott, Mark & Lau, Tom, 2018. "A review of occupant-centric building control strategies to reduce building energy use," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 1-10.
    16. Liang, Xin & Hong, Tianzhen & Shen, Geoffrey Qiping, 2016. "Improving the accuracy of energy baseline models for commercial buildings with occupancy data," Applied Energy, Elsevier, vol. 179(C), pages 247-260.
    17. Ghahramani, Ali & Zhang, Kenan & Dutta, Kanu & Yang, Zheng & Becerik-Gerber, Burcin, 2016. "Energy savings from temperature setpoints and deadband: Quantifying the influence of building and system properties on savings," Applied Energy, Elsevier, vol. 165(C), pages 930-942.
    18. Azar, Elie & Al Ansari, Hamad, 2017. "Framework to investigate energy conservation motivation and actions of building occupants: The case of a green campus in Abu Dhabi, UAE," Applied Energy, Elsevier, vol. 190(C), pages 563-573.
    19. Tronchin, Lamberto & Manfren, Massimiliano & Nastasi, Benedetto, 2018. "Energy efficiency, demand side management and energy storage technologies – A critical analysis of possible paths of integration in the built environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 341-353.
    20. D’Oca, Simona & Hong, Tianzhen & Langevin, Jared, 2018. "The human dimensions of energy use in buildings: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 731-742.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:207:y:2017:i:c:p:305-323. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.