IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v177y2016icp60-70.html
   My bibliography  Save this article

A simple model for automatic analysis and diagnosis of environmental thermal comfort in energy efficient buildings

Author

Listed:
  • Balvís, Eduardo
  • Sampedro, Óscar
  • Zaragoza, Sonia
  • Paredes, Angel
  • Michinel, Humberto

Abstract

We present a mathematical model to diagnose HVAC systems in buildings based upon the analysis of a small number of ambient state variables. In particular, the equations of the model accurately fit recorded data of temperature, relative humidity and carbon dioxide concentration in different workplaces. For validation, data were obtained under different conditions and with different sensors. In particular, we designed and fabricated a wireless sensor that measures and transmits data to a remote device and we also applied our model to data collected using a commercial sensor. For each case, information was obtained that could be used to understand and predict the evolution of ambient variables that impact thermal comfort and energy consumption in buildings. The tools presented here can thus be of great interest to achieve affordable, smart energy-efficient buildings, while adhering to environmental laws and comfort for work spaces.

Suggested Citation

  • Balvís, Eduardo & Sampedro, Óscar & Zaragoza, Sonia & Paredes, Angel & Michinel, Humberto, 2016. "A simple model for automatic analysis and diagnosis of environmental thermal comfort in energy efficient buildings," Applied Energy, Elsevier, vol. 177(C), pages 60-70.
    • Handle: RePEc:eee:appene:v:177:y:2016:i:c:p:60-70
    DOI: 10.1016/j.apenergy.2016.04.117
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261916306134
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2016.04.117?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. Široký, Jan & Oldewurtel, Frauke & Cigler, Jiří & Prívara, Samuel, 2011. "Experimental analysis of model predictive control for an energy efficient building heating system," Applied Energy, Elsevier, vol. 88(9), pages 3079-3087.
    2. Anna Laura Pisello & Michael Bobker & Franco Cotana, 2012. "A Building Energy Efficiency Optimization Method by Evaluating the Effective Thermal Zones Occupancy," Energies, MDPI, vol. 5(12), pages 1-22, December.
    3. Hunt Allcott & Michael Greenstone, 2012. "Is There an Energy Efficiency Gap?," Journal of Economic Perspectives, American Economic Association, vol. 26(1), pages 3-28, Winter.
    4. Gruber, Mattias & Trüschel, Anders & Dalenbäck, Jan-Olof, 2015. "Energy efficient climate control in office buildings without giving up implementability," Applied Energy, Elsevier, vol. 154(C), pages 934-943.
    5. Oh, Myoung Su & Ahn, Jae Hwan & Kim, Dong Woo & Jang, Dong Soo & Kim, Yongchan, 2014. "Thermal comfort and energy saving in a vehicle compartment using a localized air-conditioning system," Applied Energy, Elsevier, vol. 133(C), pages 14-21.
    6. Lopes, M.A.R. & Antunes, C.H. & Martins, N., 2012. "Energy behaviours as promoters of energy efficiency: A 21st century review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 4095-4104.
    7. Pisello, Anna Laura & Goretti, Michele & Cotana, Franco, 2012. "A method for assessing buildings’ energy efficiency by dynamic simulation and experimental activity," Applied Energy, Elsevier, vol. 97(C), pages 419-429.
    8. Zhao, Chun-Jiang & Han, Jia-Wei & Yang, Xin-Ting & Qian, Jian-Ping & Fan, Bei-Lei, 2016. "A review of computational fluid dynamics for forced-air cooling process," Applied Energy, Elsevier, vol. 168(C), pages 314-331.
    9. 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.
    10. Chung, William, 2012. "Using the fuzzy linear regression method to benchmark the energy efficiency of commercial buildings," Applied Energy, Elsevier, vol. 95(C), pages 45-49.
    11. Kusiak, Andrew & Li, Mingyang & Tang, Fan, 2010. "Modeling and optimization of HVAC energy consumption," Applied Energy, Elsevier, vol. 87(10), pages 3092-3102, October.
    12. Noailly, Joëlle, 2012. "Improving the energy efficiency of buildings: The impact of environmental policy on technological innovation," Energy Economics, Elsevier, vol. 34(3), pages 795-806.
    13. Papafragkou, Anastasios & Ghosh, Siddhartha & James, Patrick A.B. & Rogers, Alex & Bahaj, AbuBakr S., 2014. "A simple, scalable and low-cost method to generate thermal diagnostics of a domestic building," Applied Energy, Elsevier, vol. 134(C), pages 519-530.
    14. 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.
    15. Nils Kok & Marquise McGraw & John M. Quigley, 2011. "The Diffusion of Energy Efficiency in Building," American Economic Review, American Economic Association, vol. 101(3), pages 77-82, May.
    16. Anand, Y. & Gupta, A. & Tyagi, S.K. & Anand, S., 2016. "Computational fluid dynamics, a building simulation tool for achieving sustainable buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1174-1185.
    17. Martínez-Lera, S. & Ballester, J. & Martínez-Lera, J., 2013. "Analysis and sizing of thermal energy storage in combined heating, cooling and power plants for buildings," Applied Energy, Elsevier, vol. 106(C), pages 127-142.
    18. Ning, Mao & Mengjie, Song & Mingyin, Chan & Dongmei, Pan & Shiming, Deng, 2016. "Computational fluid dynamics (CFD) modelling of air flow field, mean age of air and CO2 distributions inside a bedroom with different heights of conditioned air supply outlet," Applied Energy, Elsevier, vol. 164(C), pages 906-915.
    19. 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.
    20. Li, Sheng & Sui, Jun & Jin, Hongguang & Zheng, Jianjiao, 2013. "Full chain energy performance for a combined cooling, heating and power system running with methanol and solar energy," Applied Energy, Elsevier, vol. 112(C), pages 673-681.
    21. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.
    22. Karmellos, M. & Kiprakis, A. & Mavrotas, G., 2015. "A multi-objective approach for optimal prioritization of energy efficiency measures in buildings: Model, software and case studies," Applied Energy, Elsevier, vol. 139(C), pages 131-150.
    23. 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.
    24. Wang, Liping & Greenberg, Steve & Fiegel, John & Rubalcava, Alma & Earni, Shankar & Pang, Xiufeng & Yin, Rongxin & Woodworth, Spencer & Hernandez-Maldonado, Jorge, 2013. "Monitoring-based HVAC commissioning of an existing office building for energy efficiency," Applied Energy, Elsevier, vol. 102(C), pages 1382-1390.
    25. Florides, G. A. & Tassou, S. A. & Kalogirou, S. A. & Wrobel, L. C., 2002. "Measures used to lower building energy consumption and their cost effectiveness," Applied Energy, Elsevier, vol. 73(3-4), pages 299-328, November.
    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. Barbeito, Inés & Zaragoza, Sonia & Tarrío-Saavedra, Javier & Naya, Salvador, 2017. "Assessing thermal comfort and energy efficiency in buildings by statistical quality control for autocorrelated data," Applied Energy, Elsevier, vol. 190(C), pages 1-17.
    2. Ogunjuyigbe, A.S.O. & Ayodele, T.R. & Akinola, O.A., 2017. "User satisfaction-induced demand side load management in residential buildings with user budget constraint," Applied Energy, Elsevier, vol. 187(C), pages 352-366.
    3. Roberto Robledo-Fava & Mónica C. Hernández-Luna & Pedro Fernández-de-Córdoba & Humberto Michinel & Sonia Zaragoza & A Castillo-Guzman & Romeo Selvas-Aguilar, 2019. "Analysis of the Influence Subjective Human Parameters in the Calculation of Thermal Comfort and Energy Consumption of Buildings," Energies, MDPI, vol. 12(8), pages 1-23, April.
    4. Schmidt, Mischa & Åhlund, Christer, 2018. "Smart buildings as Cyber-Physical Systems: Data-driven predictive control strategies for energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 742-756.
    5. Li, Guannan & Hu, Yunpeng & Chen, Huanxin & Li, Haorong & Hu, Min & Guo, Yabin & Liu, Jiangyan & Sun, Shaobo & Sun, Miao, 2017. "Data partitioning and association mining for identifying VRF energy consumption patterns under various part loads and refrigerant charge conditions," Applied Energy, Elsevier, vol. 185(P1), pages 846-861.

    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. Karmellos, M. & Kiprakis, A. & Mavrotas, G., 2015. "A multi-objective approach for optimal prioritization of energy efficiency measures in buildings: Model, software and case studies," Applied Energy, Elsevier, vol. 139(C), pages 131-150.
    2. Ascione, Fabrizio & Bianco, Nicola & de’ Rossi, Filippo & Turni, Gianluca & Vanoli, Giuseppe Peter, 2013. "Green roofs in European climates. Are effective solutions for the energy savings in air-conditioning?," Applied Energy, Elsevier, vol. 104(C), pages 845-859.
    3. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.
    4. Aste, Niccolò & Manfren, Massimiliano & Marenzi, Giorgia, 2017. "Building Automation and Control Systems and performance optimization: A framework for analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 313-330.
    5. 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.
    6. Kangji Li & Lei Pan & Wenping Xue & Hui Jiang & Hanping Mao, 2017. "Multi-Objective Optimization for Energy Performance Improvement of Residential Buildings: A Comparative Study," Energies, MDPI, vol. 10(2), pages 1-23, February.
    7. Delgarm, N. & Sajadi, B. & Kowsary, F. & Delgarm, S., 2016. "Multi-objective optimization of the building energy performance: A simulation-based approach by means of particle swarm optimization (PSO)," Applied Energy, Elsevier, vol. 170(C), pages 293-303.
    8. 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.
    9. Afroz, Zakia & Shafiullah, GM & Urmee, Tania & Higgins, Gary, 2018. "Modeling techniques used in building HVAC control systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 83(C), pages 64-84.
    10. Michailidis, Iakovos T. & Schild, Thomas & Sangi, Roozbeh & Michailidis, Panagiotis & Korkas, Christos & Fütterer, Johannes & Müller, Dirk & Kosmatopoulos, Elias B., 2018. "Energy-efficient HVAC management using cooperative, self-trained, control agents: A real-life German building case study," Applied Energy, Elsevier, vol. 211(C), pages 113-125.
    11. Hu, Mengqi, 2015. "A data-driven feed-forward decision framework for building clusters operation under uncertainty," Applied Energy, Elsevier, vol. 141(C), pages 229-237.
    12. Ascione, Fabrizio & Bianco, Nicola & De Stasio, Claudio & Mauro, Gerardo Maria & Vanoli, Giuseppe Peter, 2016. "Multi-stage and multi-objective optimization for energy retrofitting a developed hospital reference building: A new approach to assess cost-optimality," Applied Energy, Elsevier, vol. 174(C), pages 37-68.
    13. Yang, Zheng & Becerik-Gerber, Burcin, 2015. "A model calibration framework for simultaneous multi-level building energy simulation," Applied Energy, Elsevier, vol. 149(C), pages 415-431.
    14. Ceballos-Fuentealba, Irlanda & Álvarez-Miranda, Eduardo & Torres-Fuchslocher, Carlos & del Campo-Hitschfeld, María Luisa & Díaz-Guerrero, John, 2019. "A simulation and optimisation methodology for choosing energy efficiency measures in non-residential buildings," Applied Energy, Elsevier, vol. 256(C).
    15. Jing, Gang & Cai, Wenjian & Zhang, Xin & Cui, Can & Liu, Hongwu & Wang, Cheng, 2020. "An energy-saving control strategy for multi-zone demand controlled ventilation system with data-driven model and air balancing control," Energy, Elsevier, vol. 199(C).
    16. Shahzad, Sally & Brennan, John & Theodossopoulos, Dimitris & Hughes, Ben & Calautit, John Kaiser, 2017. "Energy and comfort in contemporary open plan and traditional personal offices," Applied Energy, Elsevier, vol. 185(P2), pages 1542-1555.
    17. Yang, Shiyu & Wan, Man Pun & Chen, Wanyu & Ng, Bing Feng & Dubey, Swapnil, 2020. "Model predictive control with adaptive machine-learning-based model for building energy efficiency and comfort optimization," Applied Energy, Elsevier, vol. 271(C).
    18. Gencel, Osman & Danish, Aamar & Yilmaz, Mukremin & Erdogmus, Ertugrul & Sutcu, Mucahit & Sadak, Ferhat & Ozbakkaloglu, Togay, 2024. "Performance evaluation of phosphor-based luminescent bricks using different coating methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    19. Wang, Endong, 2015. "Benchmarking whole-building energy performance with multi-criteria technique for order preference by similarity to ideal solution using a selective objective-weighting approach," Applied Energy, Elsevier, vol. 146(C), pages 92-103.
    20. Cui, Can & Zhang, Xin & Cai, Wenjian, 2020. "An energy-saving oriented air balancing method for demand controlled ventilation systems with branch and black-box model," Applied Energy, Elsevier, vol. 264(C).

    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:177:y:2016:i:c:p:60-70. 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.