IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i19p3710-d271636.html
   My bibliography  Save this article

Analysis Application of Controllable Load Appliances Management in a Smart Home

Author

Listed:
  • Gerardo J. Osório

    (C-MAST, University of Beira Interior, Calcada Fonte Lameiro, 6201-001 Covilha, Portugal)

  • Miadreza Shafie-khah

    (School of Technology and Innovations, University of Vaasa, 65200 Vaasa, Finland)

  • Gonçalo C. R. Carvalho

    (Faculty of Engineering of University of Porto, R. Dr. Roberto Frias, 4200-465 Porto, Portugal)

  • João P. S. Catalão

    (Faculty of Engineering of University of Porto, R. Dr. Roberto Frias, 4200-465 Porto, Portugal
    INESC-TEC, R. Dr. Roberto Frias, 4200-465 Porto, Portugal)

Abstract

The residential sector is one of the sectors with the highest rates of electricity consumption worldwide. For years, many studies have been presented in order to minimize energy consumption at the residential level. The idea of such studies is that the residential customer (RC) is the interested party of their own consumption. Moreover, the algorithms that have been developed to predict and manage the energy consumption, also analyze the behavior of the loads, with the objective of minimizing the energy costs, with good safety, robustness, and comfort levels. In the context of the smart house (SH), one of the objectives of smart grids (SGs) is to enable the RC, with home energy management systems (HEM), to actively participate, allowing for higher reliability at different levels. In this work, a new model that simulates the behavior of an SH, considering heating, ventilation and air conditioning (HVAC) and sanitarian water heater (SWH) devices, is presented. For this purpose, the proposed model considers realistic physical parameters of the SH, together with customer comfort, in order to mitigate the RC disinterest. The proposed model considers the electric vehicle (EV), a battery-based energy storage system (ESS), a micro production unit, and different types of tariffs that the RC might choose, aiming to maximize the benefits, and temporarily shifting the proposed loads.

Suggested Citation

  • Gerardo J. Osório & Miadreza Shafie-khah & Gonçalo C. R. Carvalho & João P. S. Catalão, 2019. "Analysis Application of Controllable Load Appliances Management in a Smart Home," Energies, MDPI, vol. 12(19), pages 1-24, September.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:19:p:3710-:d:271636
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/19/3710/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/12/19/3710/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bhati, Abhishek & Hansen, Michael & Chan, Ching Man, 2017. "Energy conservation through smart homes in a smart city: A lesson for Singapore households," Energy Policy, Elsevier, vol. 104(C), pages 230-239.
    2. Newsham, Guy R. & Bowker, Brent G., 2010. "The effect of utility time-varying pricing and load control strategies on residential summer peak electricity use: A review," Energy Policy, Elsevier, vol. 38(7), pages 3289-3296, July.
    3. Nan, Sibo & Zhou, Ming & Li, Gengyin, 2018. "Optimal residential community demand response scheduling in smart grid," Applied Energy, Elsevier, vol. 210(C), pages 1280-1289.
    4. Zhu, Jiawei & Lin, Yishuai & Lei, Weidong & Liu, Youquan & Tao, Mengling, 2019. "Optimal household appliances scheduling of multiple smart homes using an improved cooperative algorithm," Energy, Elsevier, vol. 171(C), pages 944-955.
    5. Wilson, Charlie & Hargreaves, Tom & Hauxwell-Baldwin, Richard, 2017. "Benefits and risks of smart home technologies," Energy Policy, Elsevier, vol. 103(C), pages 72-83.
    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. Michael J. Ritchie & Jacobus A. A. Engelbrecht & M. J. (Thinus) Booysen, 2021. "Which Strategy Saves the Most Energy for Stratified Water Heaters?," Energies, MDPI, vol. 14(16), pages 1-12, August.
    2. Stefano Leonori & Luca Baldini & Antonello Rizzi & Fabio Massimo Frattale Mascioli, 2021. "A Physically Inspired Equivalent Neural Network Circuit Model for SoC Estimation of Electrochemical Cells," Energies, MDPI, vol. 14(21), pages 1-29, November.
    3. Michael J. Ritchie & Jacobus A. A. Engelbrecht & Marthinus J. Booysen, 2022. "Centrally Adapted Optimal Control of Multiple Electric Water Heaters," Energies, MDPI, vol. 15(4), pages 1-24, February.
    4. Wadim Strielkowski & Dalia Streimikiene & Alena Fomina & Elena Semenova, 2019. "Internet of Energy (IoE) and High-Renewables Electricity System Market Design," Energies, MDPI, vol. 12(24), pages 1-17, December.

    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. Schieweck, Alexandra & Uhde, Erik & Salthammer, Tunga & Salthammer, Lea C. & Morawska, Lidia & Mazaheri, Mandana & Kumar, Prashant, 2018. "Smart homes and the control of indoor air quality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 705-718.
    2. Attour, Amel & Baudino, Marco & Krafft, Jackie & Lazaric, Nathalie, 2020. "Determinants of energy tracking application use at the city level: Evidence from France," Energy Policy, Elsevier, vol. 147(C).
    3. Große-Kreul, Felix, 2022. "What will drive household adoption of smart energy? Insights from a consumer acceptance study in Germany," Utilities Policy, Elsevier, vol. 75(C).
    4. Calver, Philippa & Simcock, Neil, 2021. "Demand response and energy justice: A critical overview of ethical risks and opportunities within digital, decentralised, and decarbonised futures," Energy Policy, Elsevier, vol. 151(C).
    5. Daniel J. Mallinson & Saahir Shafi, 2022. "Smart home technology: Challenges and opportunities for collaborative governance and policy research," Review of Policy Research, Policy Studies Organization, vol. 39(3), pages 330-352, May.
    6. Furszyfer Del Rio, D.D., 2022. "Smart but unfriendly: Connected home products as enablers of conflict," Technology in Society, Elsevier, vol. 68(C).
    7. Amel Attour & Marco Baudino & Jackie Krafft & Nathalie Lazaric, 2020. "Determinants of smart energy tracking application use at the city level: Evidence from France," Post-Print hal-02942483, HAL.
    8. Okur, Özge & Heijnen, Petra & Lukszo, Zofia, 2021. "Aggregator’s business models in residential and service sectors: A review of operational and financial aspects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    9. Marikyan, Davit & Papagiannidis, Savvas & Alamanos, Eleftherios, 2019. "A systematic review of the smart home literature: A user perspective," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 139-154.
    10. Shola Oyedeji & Ahmed Seffah & Birgit Penzenstadler, 2018. "A Catalogue Supporting Software Sustainability Design," Sustainability, MDPI, vol. 10(7), pages 1-30, July.
    11. Flavio Martins & Maria Fatima Almeida & Rodrigo Calili & Agatha Oliveira, 2020. "Design Thinking Applied to Smart Home Projects: A User-Centric and Sustainable Perspective," Sustainability, MDPI, vol. 12(23), pages 1-27, December.
    12. Jordehi, A. Rezaee, 2019. "Optimisation of demand response in electric power systems, a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 308-319.
    13. Olga Bogdanov & Veljko Jeremiæ & Sandra Jednak & Mladen Èudanov, 2019. "Scrutinizing the Smart City Index: a multivariate statistical approach," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 37(2), pages 777-799.
    14. Eid, Cherrelle & Codani, Paul & Perez, Yannick & Reneses, Javier & Hakvoort, Rudi, 2016. "Managing electric flexibility from Distributed Energy Resources: A review of incentives for market design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 237-247.
    15. Nicole D. Sintov & P. Wesley Schultz, 2017. "Adjustable Green Defaults Can Help Make Smart Homes More Sustainable," Sustainability, MDPI, vol. 9(4), pages 1-12, April.
    16. Chatzigeorgiou, I.M. & Andreou, G.T., 2021. "A systematic review on feedback research for residential energy behavior change through mobile and web interfaces," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    17. Sajjad Ali & Imran Khan & Sadaqat Jan & Ghulam Hafeez, 2021. "An Optimization Based Power Usage Scheduling Strategy Using Photovoltaic-Battery System for Demand-Side Management in Smart Grid," Energies, MDPI, vol. 14(8), pages 1-29, April.
    18. Yiming Sun & Tatsuo Nakajima, 2023. "Mitigating Technological Anxiety through the Application of Natural Interaction in Mixed Reality Systems," Future Internet, MDPI, vol. 15(6), pages 1-15, June.
    19. Michal Gluszak & Remigiusz Gawlik & Malgorzata Zieba, 2019. "Smart and Green Buildings Features in the Decision-Making Hierarchy of Office Space Tenants: An Analytic Hierarchy Process Study," Administrative Sciences, MDPI, vol. 9(3), pages 1-16, July.
    20. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.

    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:12:y:2019:i:19:p:3710-:d:271636. 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.