IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i6p1524-d514260.html
   My bibliography  Save this article

FEEdBACk: An ICT-Based Platform to Increase Energy Efficiency through Buildings’ Consumer Engagement

Author

Listed:
  • Filipe Soares

    (Institute for Systems and Computing Engineering, Tecnology and Science (INESC TEC), Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal)

  • André Madureira

    (Institute for Systems and Computing Engineering, Tecnology and Science (INESC TEC), Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal)

  • Andreu Pagès

    (DEXMA, C/ Nàpols 189, Bajos D, 08013 Barcelona, Spain)

  • António Barbosa

    (Institute for Systems and Computing Engineering, Tecnology and Science (INESC TEC), Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal)

  • António Coelho

    (Institute for Systems and Computing Engineering, Tecnology and Science (INESC TEC), Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal)

  • Fernando Cassola

    (Institute for Systems and Computing Engineering, Tecnology and Science (INESC TEC), Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal)

  • Fernando Ribeiro

    (Institute for Systems and Computing Engineering, Tecnology and Science (INESC TEC), Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal)

  • João Viana

    (Institute for Systems and Computing Engineering, Tecnology and Science (INESC TEC), Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal)

  • José Andrade

    (Institute for Systems and Computing Engineering, Tecnology and Science (INESC TEC), Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal)

  • Marina Dorokhova

    (École Polytechnique fédérale de Lausanne (EPFL), STI IMT PV-LAB, MC A2 304 (Microcity), Rue de la Maladière 71b, CH-2002 Neuchâtel, Switzerland)

  • Nélson Morais

    (Institute for Systems and Computing Engineering, Tecnology and Science (INESC TEC), Campus da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal)

  • Nicolas Wyrsch

    (École Polytechnique fédérale de Lausanne (EPFL), STI IMT PV-LAB, MC A2 304 (Microcity), Rue de la Maladière 71b, CH-2002 Neuchâtel, Switzerland)

  • Trine Sørensen

    (In-JeT ApS, Jeppe Aakjærs Vej, 15 3460 Birkerød, Denmark)

Abstract

Energy efficiency in buildings can be enhanced by several actions: encouraging users to comprehend and then adopt more energy-efficient behaviors; aiding building managers in maximizing energy savings; and using automation to optimize energy consumption, generation, and storage of controllable and flexible devices without compromising comfort levels and indoor air-quality parameters. This paper proposes an integrated Information and communications technology (ICT) based platform addressing all these factors. The gamification platform is embedded in the ICT platform along with an interactive energy management system, which aids interested stakeholders in optimizing “when and at which rate” energy should be buffered and consumed, with several advantages, such as reducing peak load, maximizing local renewable energy consumption, and delivering more efficient use of the resources available in individual buildings or blocks of buildings. This system also interacts with an automation manager and a users’ behavior predictor application. The work was developed in the Horizon 2020 FEEdBACk (Fostering Energy Efficiency and BehAvioral Change through ICT) project.

Suggested Citation

  • Filipe Soares & André Madureira & Andreu Pagès & António Barbosa & António Coelho & Fernando Cassola & Fernando Ribeiro & João Viana & José Andrade & Marina Dorokhova & Nélson Morais & Nicolas Wyrsch , 2021. "FEEdBACk: An ICT-Based Platform to Increase Energy Efficiency through Buildings’ Consumer Engagement," Energies, MDPI, vol. 14(6), pages 1-43, March.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:6:p:1524-:d:514260
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/6/1524/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/6/1524/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Antonio Paone & Jean-Philippe Bacher, 2018. "The Impact of Building Occupant Behavior on Energy Efficiency and Methods to Influence It: A Review of the State of the Art," Energies, MDPI, vol. 11(4), pages 1-19, April.
    2. Wang, Huilong & Wang, Shengwei & Tang, Rui, 2019. "Development of grid-responsive buildings: Opportunities, challenges, capabilities and applications of HVAC systems in non-residential buildings in providing ancillary services by fast demand responses," Applied Energy, Elsevier, vol. 250(C), pages 697-712.
    3. Frederiks, Elisha R. & Stenner, Karen & Hobman, Elizabeth V., 2015. "Household energy use: Applying behavioural economics to understand consumer decision-making and behaviour," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1385-1394.
    4. Esa, Nur Farahin & Abdullah, Md Pauzi & Hassan, Mohammad Yusri, 2016. "A review disaggregation method in Non-intrusive Appliance Load Monitoring," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 163-173.
    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. Jonas Rothfuss & Fabio Ferreira & Simon Walther & Maxim Ulrich, 2019. "Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks," Papers 1903.00954, arXiv.org, revised Apr 2019.
    7. Hong, Tao & Pinson, Pierre & Fan, Shu & Zareipour, Hamidreza & Troccoli, Alberto & Hyndman, Rob J., 2016. "Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond," International Journal of Forecasting, Elsevier, vol. 32(3), pages 896-913.
    8. Stamatios Ntanos & Grigorios Kyriakopoulos & Michalis Skordoulis & Miltiadis Chalikias & Garyfallos Arabatzis, 2019. "An Application of the New Environmental Paradigm (NEP) Scale in a Greek Context," Energies, MDPI, vol. 12(2), pages 1-18, January.
    9. Mustafa Alparslan Zehir & Kadir Baris Ortac & Hakan Gul & Alp Batman & Zafer Aydin & João Carlos Portela & Filipe Joel Soares & Mustafa Bagriyanik & Unal Kucuk & Aydogan Ozdemir, 2019. "Development and Field Demonstration of a Gamified Residential Demand Management Platform Compatible with Smart Meters and Building Automation Systems," Energies, MDPI, vol. 12(5), pages 1-18, March.
    10. Nagy, Gábor I. & Barta, Gergő & Kazi, Sándor & Borbély, Gyula & Simon, Gábor, 2016. "GEFCom2014: Probabilistic solar and wind power forecasting using a generalized additive tree ensemble approach," International Journal of Forecasting, Elsevier, vol. 32(3), pages 1087-1093.
    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. Alla Polyanska & Maksym Andriiovych & Natalia Generowicz & Joanna Kulczycka & Vladyslav Psyuk, 2022. "Gamification as an Improvement Tool for HR Management in the Energy Industry—A Case Study of the Ukrainian Market," Energies, MDPI, vol. 15(4), pages 1-18, February.
    2. Martin Rovňák & Alexander Tokarčík & Lenka Štofejová & Roman Novotný & Peter Adamišin & Matúš Bakoň, 2021. "Design of the Model of Optimization of Energy Efficiency Management Processes at the Regional Level of Slovakia," Energies, MDPI, vol. 14(20), pages 1-9, October.
    3. Marina Dorokhova & Fernando Ribeiro & António Barbosa & João Viana & Filipe Soares & Nicolas Wyrsch, 2021. "Real-World Implementation of an ICT-Based Platform to Promote Energy Efficiency," Energies, MDPI, vol. 14(9), pages 1-23, April.
    4. Zhu, Minglei & Huang, Haiyan & Ma, Weiwen, 2023. "Transformation of natural resource use: Moving towards sustainability through ICT-based improvements in green total factor energy efficiency," Resources Policy, Elsevier, vol. 80(C).

    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. Marina Dorokhova & Fernando Ribeiro & António Barbosa & João Viana & Filipe Soares & Nicolas Wyrsch, 2021. "Real-World Implementation of an ICT-Based Platform to Promote Energy Efficiency," Energies, MDPI, vol. 14(9), pages 1-23, April.
    2. González Ordiano, Jorge Ángel & Gröll, Lutz & Mikut, Ralf & Hagenmeyer, Veit, 2020. "Probabilistic energy forecasting using the nearest neighbors quantile filter and quantile regression," International Journal of Forecasting, Elsevier, vol. 36(2), pages 310-323.
    3. He, Yaoyao & Cao, Chaojin & Wang, Shuo & Fu, Hong, 2022. "Nonparametric probabilistic load forecasting based on quantile combination in electrical power systems," Applied Energy, Elsevier, vol. 322(C).
    4. Müller, Alfred & Reuber, Matthias, 2023. "A copula-based time series model for global horizontal irradiation," International Journal of Forecasting, Elsevier, vol. 39(2), pages 869-883.
    5. Zhang, Wenjie & Quan, Hao & Srinivasan, Dipti, 2018. "Parallel and reliable probabilistic load forecasting via quantile regression forest and quantile determination," Energy, Elsevier, vol. 160(C), pages 810-819.
    6. Luis Gonzaga Baca Ruiz & Manuel Pegalajar Cuéllar & Miguel Delgado Calvo-Flores & María Del Carmen Pegalajar Jiménez, 2016. "An Application of Non-Linear Autoregressive Neural Networks to Predict Energy Consumption in Public Buildings," Energies, MDPI, vol. 9(9), pages 1-21, August.
    7. Elnour, Mariam & Fadli, Fodil & Himeur, Yassine & Petri, Ioan & Rezgui, Yacine & Meskin, Nader & Ahmad, Ahmad M., 2022. "Performance and energy optimization of building automation and management systems: Towards smart sustainable carbon-neutral sports facilities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    8. Luis Mazorra-Aguiar & Philippe Lauret & Mathieu David & Albert Oliver & Gustavo Montero, 2021. "Comparison of Two Solar Probabilistic Forecasting Methodologies for Microgrids Energy Efficiency," Energies, MDPI, vol. 14(6), pages 1-26, March.
    9. Kiguchi, Y. & Weeks, M. & Arakawa, R., 2021. "Predicting winners and losers under time-of-use tariffs using smart meter data," Energy, Elsevier, vol. 236(C).
    10. Yang, Dazhi & van der Meer, Dennis, 2021. "Post-processing in solar forecasting: Ten overarching thinking tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    11. David, Mathieu & Luis, Mazorra Aguiar & Lauret, Philippe, 2018. "Comparison of intraday probabilistic forecasting of solar irradiance using only endogenous data," International Journal of Forecasting, Elsevier, vol. 34(3), pages 529-547.
    12. Long Cai & Jie Gu & Jinghuan Ma & Zhijian Jin, 2019. "Probabilistic Wind Power Forecasting Approach via Instance-Based Transfer Learning Embedded Gradient Boosting Decision Trees," Energies, MDPI, vol. 12(1), pages 1-19, January.
    13. Sherif Goubran & Carmela Cucuzzella & Mohamed M. Ouf, 2021. "Eyes on the Goal! Exploring Interactive Artistic Real-Time Energy Interfaces for Target-Specific Actions in the Built Environment," Sustainability, MDPI, vol. 13(4), pages 1-17, February.
    14. Baldi, Simone & Zhang, Fan & Le Quang, Thuan & Endel, Petr & Holub, Ondrej, 2019. "Passive versus active learning in operation and adaptive maintenance of Heating, Ventilation, and Air Conditioning," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    15. 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.
    16. Shan, Kui & Wang, Shengwei & Zhuang, Chaoqun, 2021. "Controlling a large constant speed centrifugal chiller to provide grid frequency regulation: A validation based on onsite tests," Applied Energy, Elsevier, vol. 300(C).
    17. Juana Isabel Méndez & Adán Medina & Pedro Ponce & Therese Peffer & Alan Meier & Arturo Molina, 2022. "Evolving Gamified Smart Communities in Mexico to Save Energy in Communities through Intelligent Interfaces," Energies, MDPI, vol. 15(15), pages 1-29, July.
    18. Cameron Roach & Rob Hyndman & Souhaib Ben Taieb, 2021. "Non‐linear mixed‐effects models for time series forecasting of smart meter demand," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1118-1130, September.
    19. Grzegorz Marcjasz & Tomasz Serafin & Rafał Weron, 2018. "Selection of Calibration Windows for Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 11(9), pages 1-20, September.
    20. Anna Borawska & Mariusz Borawski & Małgorzata Łatuszyńska, 2022. "Effectiveness of Electricity-Saving Communication Campaigns: Neurophysiological Approach," Energies, MDPI, vol. 15(4), pages 1-19, February.

    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:gam:jeners:v:14:y:2021:i:6:p:1524-:d:514260. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.