IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i17p3336-d262163.html
   My bibliography  Save this article

A Novel Direct Load Control Testbed for Smart Appliances

Author

Listed:
  • Joaquín Garrido-Zafra

    (Electronics and Computer Engineering Department, University of Córdoba, Córdoba 14071, Spain)

  • Antonio Moreno-Munoz

    (Electronics and Computer Engineering Department, University of Córdoba, Córdoba 14071, Spain)

  • Aurora Gil-de-Castro

    (Electronics and Computer Engineering Department, University of Córdoba, Córdoba 14071, Spain)

  • Emilio J. Palacios-Garcia

    (Department of Energy Technology, Aalborg University, Aalborg 9220, Denmark)

  • Carlos D. Moreno-Moreno

    (Electronics and Computer Engineering Department, University of Córdoba, Córdoba 14071, Spain)

  • Tomás Morales-Leal

    (Electrical Engineering Department, University of Córdoba, Córdoba 14071, Spain)

Abstract

The effort to continuously improve and innovate smart appliances (SA) energy management requires an experimental research and development environment which integrates widely differing tools and resources seamlessly. To this end, this paper proposes a novel Direct Load Control (DLC) testbed, aiming to conveniently support the research community, as well as analyzing and comparing their designs in a laboratory environment. Based on the LabVIEW computing platform, this original testbed enables access to knowledge of major components such as online weather forecasting information, distributed energy resources (e.g., energy storage, solar photovoltaic), dynamic electricity tariff from utilities and demand response (DR) providers together with different mathematical optimization features given by General Algebraic Modelling System (GAMS). This intercommunication is possible thanks to the different applications programming interfaces (API) incorporated into the system and to intermediate agents specially developed for this case. Different basic case studies have been presented to envision the possibilities of this system in the future and more complex scenarios, to actively support the DLC strategies. These measures will offer enough flexibility to minimize the impact on user comfort combined with support for multiple DR programs. Thus, given the successful results, this platform can lead to a solution towards more efficient use of energy in the residential environment.

Suggested Citation

  • Joaquín Garrido-Zafra & Antonio Moreno-Munoz & Aurora Gil-de-Castro & Emilio J. Palacios-Garcia & Carlos D. Moreno-Moreno & Tomás Morales-Leal, 2019. "A Novel Direct Load Control Testbed for Smart Appliances," Energies, MDPI, vol. 12(17), pages 1-16, August.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:17:p:3336-:d:262163
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/17/3336/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/12/17/3336/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhou, Bin & Li, Wentao & Chan, Ka Wing & Cao, Yijia & Kuang, Yonghong & Liu, Xi & Wang, Xiong, 2016. "Smart home energy management systems: Concept, configurations, and scheduling strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 30-40.
    2. Fotouhi Ghazvini, Mohammad Ali & Soares, João & Horta, Nuno & Neves, Rui & Castro, Rui & Vale, Zita, 2015. "A multi-objective model for scheduling of short-term incentive-based demand response programs offered by electricity retailers," Applied Energy, Elsevier, vol. 151(C), pages 102-118.
    3. Palacios-Garcia, E.J. & Moreno-Munoz, A. & Santiago, I. & Flores-Arias, J.M. & Bellido-Outeirino, F.J. & Moreno-Garcia, I.M., 2018. "A stochastic modelling and simulation approach to heating and cooling electricity consumption in the residential sector," Energy, Elsevier, vol. 144(C), pages 1080-1091.
    4. Beaudin, Marc & Zareipour, Hamidreza, 2015. "Home energy management systems: A review of modelling and complexity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 318-335.
    5. Kleidaras, Alexandros & Kiprakis, Aristides E. & Thompson, John S., 2018. "Human in the loop heterogeneous modelling of thermostatically controlled loads for demand side management studies," Energy, Elsevier, vol. 145(C), pages 754-769.
    6. Babonneau, Frédéric & Caramanis, Michael & Haurie, Alain, 2016. "A linear programming model for power distribution with demand response and variable renewable energy," Applied Energy, Elsevier, vol. 181(C), pages 83-95.
    7. Amasyali, Kadir & El-Gohary, Nora M., 2018. "A review of data-driven building energy consumption prediction studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1192-1205.
    8. Killian, M. & Zauner, M. & Kozek, M., 2018. "Comprehensive smart home energy management system using mixed-integer quadratic-programming," Applied Energy, Elsevier, vol. 222(C), pages 662-672.
    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. Lucas V. Bellinaso & Edivan L. Carvalho & Rafael Cardoso & Leandro Michels, 2021. "Price-Response Matrices Design Methodology for Electrical Energy Management Systems Based on DC Bus Signalling," Energies, MDPI, vol. 14(6), pages 1-19, March.
    2. Antonio Moreno-Munoz, 2019. "Special Issue “Nanogrids, Microgrids, and the Internet of Things (IoT): Towards the Digital Energy Network”," Energies, MDPI, vol. 12(20), pages 1-3, October.

    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. Laura Canale & Anna Rita Di Fazio & Mario Russo & Andrea Frattolillo & Marco Dell’Isola, 2021. "An Overview on Functional Integration of Hybrid Renewable Energy Systems in Multi-Energy Buildings," Energies, MDPI, vol. 14(4), pages 1-33, February.
    2. Chen, Chien-fei & Nelson, Hannah & Xu, Xiaojing & Bonilla, Gregory & Jones, Nicholas, 2021. "Beyond technology adoption: Examining home energy management systems, energy burdens and climate change perceptions during COVID-19 pandemic," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    3. Mehrjerdi, Hasan & Bornapour, Mosayeb & Hemmati, Reza & Ghiasi, Seyyed Mohammad Sadegh, 2019. "Unified energy management and load control in building equipped with wind-solar-battery incorporating electric and hydrogen vehicles under both connected to the grid and islanding modes," Energy, Elsevier, vol. 168(C), pages 919-930.
    4. Adnan Ahmad & Asif Khan & Nadeem Javaid & Hafiz Majid Hussain & Wadood Abdul & Ahmad Almogren & Atif Alamri & Iftikhar Azim Niaz, 2017. "An Optimized Home Energy Management System with Integrated Renewable Energy and Storage Resources," Energies, MDPI, vol. 10(4), pages 1-35, April.
    5. Krzysztof Gajowniczek & Tomasz Ząbkowski, 2017. "Electricity forecasting on the individual household level enhanced based on activity patterns," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-26, April.
    6. Al Essa, Mohammed Jasim M., 2019. "Home energy management of thermostatically controlled loads and photovoltaic-battery systems," Energy, Elsevier, vol. 176(C), pages 742-752.
    7. Alvaro Llaria & Jessye Dos Santos & Guillaume Terrasson & Zina Boussaada & Christophe Merlo & Octavian Curea, 2021. "Intelligent Buildings in Smart Grids: A Survey on Security and Privacy Issues Related to Energy Management," Energies, MDPI, vol. 14(9), pages 1-37, May.
    8. Ebrahimi, Seyyed Reza & Rahimiyan, Morteza & Assili, Mohsen & Hajizadeh, Amin, 2022. "Home energy management under correlated uncertainties: A statistical analysis through Copula," Applied Energy, Elsevier, vol. 305(C).
    9. Nojavan, Sayyad & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2017. "Optimal stochastic energy management of retailer based on selling price determination under smart grid environment in the presence of demand response program," Applied Energy, Elsevier, vol. 187(C), pages 449-464.
    10. Muhammad Majid Hussain & Rizwan Akram & Zulfiqar Ali Memon & Mian Hammad Nazir & Waqas Javed & Muhammad Siddique, 2021. "Demand Side Management Techniques for Home Energy Management Systems for Smart Cities," Sustainability, MDPI, vol. 13(21), pages 1-20, October.
    11. Tri-Hai Nguyen & Luong Vuong Nguyen & Jason J. Jung & Israel Edem Agbehadji & Samuel Ofori Frimpong & Richard C. Millham, 2020. "Bio-Inspired Approaches for Smart Energy Management: State of the Art and Challenges," Sustainability, MDPI, vol. 12(20), pages 1-24, October.
    12. Rohács, Dániel, 2023. "Analysis and optimization of potential energy sources for residential building application," Energy, Elsevier, vol. 275(C).
    13. Gao, Zhikun & Yu, Junqi & Zhao, Anjun & Hu, Qun & Yang, Siyuan, 2022. "A hybrid method of cooling load forecasting for large commercial building based on extreme learning machine," Energy, Elsevier, vol. 238(PC).
    14. da Fonseca, André L.A. & Chvatal, Karin M.S. & Fernandes, Ricardo A.S., 2021. "Thermal comfort maintenance in demand response programs: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    15. 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.
    16. WeiYu Ji & Edwin H. W. Chan, 2019. "Critical Factors Influencing the Adoption of Smart Home Energy Technology in China: A Guangdong Province Case Study," Energies, MDPI, vol. 12(21), pages 1-24, November.
    17. Antonio Ruano & Alvaro Hernandez & Jesus Ureña & Maria Ruano & Juan Garcia, 2019. "NILM Techniques for Intelligent Home Energy Management and Ambient Assisted Living: A Review," Energies, MDPI, vol. 12(11), pages 1-29, June.
    18. Isaías Gomes & Karol Bot & Maria Graça Ruano & António Ruano, 2022. "Recent Techniques Used in Home Energy Management Systems: A Review," Energies, MDPI, vol. 15(8), pages 1-41, April.
    19. Wang, Jidong & Liu, Jianxin & Li, Chenghao & Zhou, Yue & Wu, Jianzhong, 2020. "Optimal scheduling of gas and electricity consumption in a smart home with a hybrid gas boiler and electric heating system," Energy, Elsevier, vol. 204(C).
    20. Kim, Hakpyeong & Choi, Heeju & Kang, Hyuna & An, Jongbaek & Yeom, Seungkeun & Hong, Taehoon, 2021. "A systematic review of the smart energy conservation system: From smart homes to sustainable smart cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(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:gam:jeners:v:12:y:2019:i:17:p:3336-:d:262163. 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.