IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v101y2013icp6-14.html
   My bibliography  Save this article

An integrated system for buildings’ energy-efficient automation: Application in the tertiary sector

Author

Listed:
  • Marinakis, Vangelis
  • Doukas, Haris
  • Karakosta, Charikleia
  • Psarras, John

Abstract

Although integrated building automation systems have become increasingly popular, an integrated system which includes remote control technology to enable real-time monitoring of the energy consumption by energy end-users, as well as optimization functions is required. To respond to this common interest, the main aim of the paper is to present an integrated system for buildings’ energy-efficient automation. The proposed system is based on a prototype software tool for the simulation and optimization of energy consumption in the building sector, enhancing the interactivity of building automation systems. The system can incorporate energy-efficient automation functions for heating, cooling and/or lighting based on recent guidance and decisions of the National Law, energy efficiency requirements of EN 15232 and ISO 50001 Energy Management Standard among others. The presented system was applied to a supermarket building in Greece and focused on the remote control of active systems.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:101:y:2013:i:c:p:6-14
    DOI: 10.1016/j.apenergy.2012.05.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261912004059
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2012.05.032?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. van Beeck, Nicole & Doukas, Haris & Gioria, Michel & Karakosta, Charikleia & Psarras, John, 2009. "Energy RTD expenditures in the European union: Data gathering procedures and results towards a scientific reference system," Applied Energy, Elsevier, vol. 86(4), pages 452-459, April.
    2. Buonomano, Annamaria & Calise, Francesco & Palombo, Adolfo, 2012. "Buildings dynamic simulation: Water loop heat pump systems analysis for European climates," Applied Energy, Elsevier, vol. 91(1), pages 222-234.
    3. 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.
    4. Mechri, Houcem Eddine & Capozzoli, Alfonso & Corrado, Vincenzo, 2010. "USE of the ANOVA approach for sensitive building energy design," Applied Energy, Elsevier, vol. 87(10), pages 3073-3083, October.
    5. Kennedy, Scott & Sgouridis, Sgouris, 2011. "Rigorous classification and carbon accounting principles for low and Zero Carbon Cities," Energy Policy, Elsevier, vol. 39(9), pages 5259-5268, September.
    6. Li, Danny H.W. & Cheung, K.L. & Wong, S.L. & Lam, Tony N.T., 2010. "An analysis of energy-efficient light fittings and lighting controls," Applied Energy, Elsevier, vol. 87(2), pages 558-567, February.
    7. Rahman, M.M. & Rasul, M.G. & Khan, M.M.K., 2010. "Energy conservation measures in an institutional building in sub-tropical climate in Australia," Applied Energy, Elsevier, vol. 87(10), pages 2994-3004, October.
    8. Olofsson, Thomas & Mahlia, T.M.I., 2012. "Modeling and simulation of the energy use in an occupied residential building in cold climate," Applied Energy, Elsevier, vol. 91(1), pages 432-438.
    9. Sgouridis, Sgouris & Kennedy, Scott, 2010. "Tangible and fungible energy: Hybrid energy market and currency system for total energy management. A Masdar City case study," Energy Policy, Elsevier, vol. 38(4), pages 1749-1758, April.
    10. Ma, Zhenjun & Wang, Shengwei & Xiao, Fu, 2009. "Online performance evaluation of alternative control strategies for building cooling water systems prior to in situ implementation," Applied Energy, Elsevier, vol. 86(5), pages 712-721, May.
    11. Nair, Gireesh & Gustavsson, Leif & Mahapatra, Krushna, 2010. "Owners perception on the adoption of building envelope energy efficiency measures in Swedish detached houses," Applied Energy, Elsevier, vol. 87(7), pages 2411-2419, July.
    12. Chwieduk, Dorota, 2003. "Towards sustainable-energy buildings," Applied Energy, Elsevier, vol. 76(1-3), pages 211-217, September.
    13. Karunakaran, R. & Iniyan, S. & Goic, Ranko, 2010. "Energy efficient fuzzy based combined variable refrigerant volume and variable air volume air conditioning system for buildings," Applied Energy, Elsevier, vol. 87(4), pages 1158-1175, April.
    14. Dounis, A.I. & Caraiscos, C., 2009. "Advanced control systems engineering for energy and comfort management in a building environment--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1246-1261, August.
    15. Kusiak, Andrew & Li, Mingyang & Tang, Fan, 2010. "Modeling and optimization of HVAC energy consumption," Applied Energy, Elsevier, vol. 87(10), pages 3092-3102, October.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Lü, Xiaoshu & Lu, Tao & Kibert, Charles J. & Viljanen, Martti, 2014. "A novel dynamic modeling approach for predicting building energy performance," Applied Energy, Elsevier, vol. 114(C), pages 91-103.
    6. 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.
    7. Baldi, Simone & Michailidis, Iakovos & Ravanis, Christos & Kosmatopoulos, Elias B., 2015. "Model-based and model-free “plug-and-play” building energy efficient control," Applied Energy, Elsevier, vol. 154(C), pages 829-841.
    8. Buonomano, Annamaria & Montanaro, Umberto & Palombo, Adolfo & Santini, Stefania, 2016. "Dynamic building energy performance analysis: A new adaptive control strategy for stringent thermohygrometric indoor air requirements," Applied Energy, Elsevier, vol. 163(C), pages 361-386.
    9. 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.
    10. 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.
    11. Muhammad Fayaz & DoHyeun Kim, 2018. "Energy Consumption Optimization and User Comfort Management in Residential Buildings Using a Bat Algorithm and Fuzzy Logic," Energies, MDPI, vol. 11(1), pages 1-22, January.
    12. Gianluca Serale & Massimo Fiorentini & Alfonso Capozzoli & Daniele Bernardini & Alberto Bemporad, 2018. "Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities," Energies, MDPI, vol. 11(3), pages 1-35, March.
    13. Jiang, Lai & Yao, Runming & Liu, Kecheng & McCrindle, Rachel, 2017. "An Epistemic-Deontic-Axiologic (EDA) agent-based energy management system in office buildings," Applied Energy, Elsevier, vol. 205(C), pages 440-452.
    14. Wang, Zhu & Wang, Lingfeng & Dounis, Anastasios I. & Yang, Rui, 2012. "Multi-agent control system with information fusion based comfort model for smart buildings," Applied Energy, Elsevier, vol. 99(C), pages 247-254.
    15. Byung-Ki Jeon & Eui-Jong Kim, 2021. "LSTM-Based Model Predictive Control for Optimal Temperature Set-Point Planning," Sustainability, MDPI, vol. 13(2), pages 1-14, January.
    16. Abhinandana Boodi & Karim Beddiar & Malek Benamour & Yassine Amirat & Mohamed Benbouzid, 2018. "Intelligent Systems for Building Energy and Occupant Comfort Optimization: A State of the Art Review and Recommendations," Energies, MDPI, vol. 11(10), pages 1-26, September.
    17. 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.
    18. Olofsson, Thomas & Mahlia, T.M.I., 2012. "Modeling and simulation of the energy use in an occupied residential building in cold climate," Applied Energy, Elsevier, vol. 91(1), pages 432-438.
    19. Ahn, Jonghoon & Cho, Soolyeon & Chung, Dae Hun, 2017. "Analysis of energy and control efficiencies of fuzzy logic and artificial neural network technologies in the heating energy supply system responding to the changes of user demands," Applied Energy, Elsevier, vol. 190(C), pages 222-231.
    20. Ramkishore Singh & Dharam Buddhi & Samar Thapa & Chander Prakash & Rajesh Singh & Atul Sharma & Shane Sheoran & Kuldeep Kumar Saxena, 2022. "Sensitivity Analysis for Decisive Design Parameters for Energy and Indoor Visual Performances of a Glazed Façade Office Building," Sustainability, MDPI, vol. 14(21), pages 1-27, October.

    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:101:y:2013:i:c:p:6-14. 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.