IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i22p6287-d285040.html
   My bibliography  Save this article

An Innovative Home Energy Management Model with Coordination among Appliances using Game Theory

Author

Listed:
  • Aqib Jamil

    (Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan)

  • Turki Ali Alghamdi

    (Department of Computer Science, College of Computer and Information Systems, Umm Al-Qura University, Makkah 11692, Saudi Arabia)

  • Zahoor Ali Khan

    (Computer Information Science, Higher Colleges of Technology, Fujairah 4114, UAE)

  • Sakeena Javaid

    (Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan)

  • Abdul Haseeb

    (Department of Electrical Engineering, Institute of Space Technology (IST), Islamabad 44000, Pakistan)

  • Zahid Wadud

    (Department of Computer System Engineering, University of Engineering and Technology, Peshawar 25000, Pakistan)

  • Nadeem Javaid

    (Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan)

Abstract

The feature of bidirectional communication in a smart grid involves the interaction between consumer and utility for optimizing the energy consumption of the users. For optimal management of the energy at the end user, several demand side management techniques are implemented. This work proposes a home energy management system, where consumption of household appliances is optimized using a hybrid technique. This technique is developed from cuckoo search algorithm and earthworm algorithm. However, there is a problem in such home energy management systems, that is, an uncertain behavior of the user that can lead to force start or stop of an appliance, deteriorating the purpose of scheduling of appliances. In order to solve this issue, coordination among appliances for rescheduling is incorporated in home energy management system using game theory. The appliances of the home are categorized in three different groups and their electricity cost is computed through the real-time pricing signals. Optimization schemes are implemented and their performance is scrutinized with and without coordination among the appliances. Simulation outcomes display that our proposed technique has minimized the total electricity cost by 50.6% as compared to unscheduled cost. Moreover, coordination among appliances has helped in increasing the user comfort by reducing the waiting time of appliances. The Shapley value has outperformed the Nash equilibrium and zero sum by achieving the maximum reduction in waiting time of appliances.

Suggested Citation

  • Aqib Jamil & Turki Ali Alghamdi & Zahoor Ali Khan & Sakeena Javaid & Abdul Haseeb & Zahid Wadud & Nadeem Javaid, 2019. "An Innovative Home Energy Management Model with Coordination among Appliances using Game Theory," Sustainability, MDPI, vol. 11(22), pages 1-23, November.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:22:p:6287-:d:285040
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/22/6287/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/22/6287/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sheraz Aslam & Zafar Iqbal & Nadeem Javaid & Zahoor Ali Khan & Khursheed Aurangzeb & Syed Irtaza Haider, 2017. "Towards Efficient Energy Management of Smart Buildings Exploiting Heuristic Optimization with Real Time and Critical Peak Pricing Schemes," Energies, MDPI, vol. 10(12), pages 1-25, December.
    2. Alam, Muhammad Raisul & St-Hilaire, Marc & Kunz, Thomas, 2019. "Peer-to-peer energy trading among smart homes," Applied Energy, Elsevier, vol. 238(C), pages 1434-1443.
    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. 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.
    2. Mahmoud H. Elkholy & Tomonobu Senjyu & Mohammed Elsayed Lotfy & Abdelrahman Elgarhy & Nehad S. Ali & Tamer S. Gaafar, 2022. "Design and Implementation of a Real-Time Smart Home Management System Considering Energy Saving," Sustainability, MDPI, vol. 14(21), pages 1-22, October.
    3. Simona-Vasilica Oprea & Adela Bâra & George Adrian Ifrim, 2021. "Optimizing the Electricity Consumption with a High Degree of Flexibility Using a Dynamic Tariff and Stackelberg Game," Journal of Optimization Theory and Applications, Springer, vol. 190(1), pages 151-182, July.
    4. Zahoor Ali Khan & Muhammad Adil & Nadeem Javaid & Malik Najmus Saqib & Muhammad Shafiq & Jin-Ghoo Choi, 2020. "Electricity Theft Detection Using Supervised Learning Techniques on Smart Meter Data," Sustainability, MDPI, vol. 12(19), pages 1-25, September.
    5. Tostado-Véliz, Marcos & Kamel, Salah & Aymen, Flah & Jurado, Francisco, 2022. "A novel hybrid lexicographic-IGDT methodology for robust multi-objective solution of home energy management systems," Energy, Elsevier, vol. 253(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. Gržanić, M. & Capuder, T. & Zhang, N. & Huang, W., 2022. "Prosumers as active market participants: A systematic review of evolution of opportunities, models and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    2. Park, Sung-Won & Zhang, Zhong & Li, Furong & Son, Sung-Yong, 2021. "Peer-to-peer trading-based efficient flexibility securing mechanism to support distribution system stability," Applied Energy, Elsevier, vol. 285(C).
    3. Lyu, Cheng & Jia, Youwei & Xu, Zhao, 2021. "Fully decentralized peer-to-peer energy sharing framework for smart buildings with local battery system and aggregated electric vehicles," Applied Energy, Elsevier, vol. 299(C).
    4. Lee, Juyong & Cho, Youngsang, 2020. "Estimation of the usage fee for peer-to-peer electricity trading platform: The case of South Korea," Energy Policy, Elsevier, vol. 136(C).
    5. Ma, Li & Wang, Lingfeng & Liu, Zhaoxi, 2021. "Multi-level trading community formation and hybrid trading network construction in local energy market," Applied Energy, Elsevier, vol. 285(C).
    6. Huang, Yujing & Wang, Yudong & Liu, Nian, 2022. "Low-carbon economic dispatch and energy sharing method of multiple Integrated Energy Systems from the perspective of System of Systems," Energy, Elsevier, vol. 244(PA).
    7. Wang, Zibo & Yu, Xiaodan & Mu, Yunfei & Jia, Hongjie, 2020. "A distributed Peer-to-Peer energy transaction method for diversified prosumers in Urban Community Microgrid System," Applied Energy, Elsevier, vol. 260(C).
    8. Tsao, Yu-Chung & Thanh, Vo-Van, 2021. "Toward sustainable microgrids with blockchain technology-based peer-to-peer energy trading mechanism: A fuzzy meta-heuristic approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 136(C).
    9. Davarzani, Sima & Pisica, Ioana & Taylor, Gareth A. & Munisami, Kevin J., 2021. "Residential Demand Response Strategies and Applications in Active Distribution Network Management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    10. Lin, Wen-Ting & Chen, Guo & Zhou, Xiaojun, 2022. "Distributed carbon-aware energy trading of virtual power plant under denial of service attacks: A passivity-based neurodynamic approach," Energy, Elsevier, vol. 257(C).
    11. Soto, Esteban A. & Bosman, Lisa B. & Wollega, Ebisa & Leon-Salas, Walter D., 2021. "Peer-to-peer energy trading: A review of the literature," Applied Energy, Elsevier, vol. 283(C).
    12. Bischi, Aldo & Basile, Mariano & Poli, Davide & Vallati, Carlo & Miliani, Francesco & Caposciutti, Gianluca & Marracci, Mirko & Dini, Gianluca & Desideri, Umberto, 2021. "Enabling low-voltage, peer-to-peer, quasi-real-time electricity markets through consortium blockchains," Applied Energy, Elsevier, vol. 288(C).
    13. Herodotos Herodotou & Sheraz Aslam, 2022. "Data-Intensive Computing in Smart Microgrids: Volume II," Energies, MDPI, vol. 15(16), pages 1-2, August.
    14. Esmat, Ayman & de Vos, Martijn & Ghiassi-Farrokhfal, Yashar & Palensky, Peter & Epema, Dick, 2021. "A novel decentralized platform for peer-to-peer energy trading market with blockchain technology," Applied Energy, Elsevier, vol. 282(PA).
    15. Capper, Timothy & Gorbatcheva, Anna & Mustafa, Mustafa A. & Bahloul, Mohamed & Schwidtal, Jan Marc & Chitchyan, Ruzanna & Andoni, Merlinda & Robu, Valentin & Montakhabi, Mehdi & Scott, Ian J. & Franci, 2022. "Peer-to-peer, community self-consumption, and transactive energy: A systematic literature review of local energy market models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    16. Milad Afzalan & Farrokh Jazizadeh, 2021. "Quantification of Demand-Supply Balancing Capacity among Prosumers and Consumers: Community Self-Sufficiency Assessment for Energy Trading," Energies, MDPI, vol. 14(14), pages 1-21, July.
    17. Amit Shewale & Anil Mokhade & Nitesh Funde & Neeraj Dhanraj Bokde, 2022. "A Survey of Efficient Demand-Side Management Techniques for the Residential Appliance Scheduling Problem in Smart Homes," Energies, MDPI, vol. 15(8), pages 1-34, April.
    18. Yang, Qing & Wang, Hao & Wang, Taotao & Zhang, Shengli & Wu, Xiaoxiao & Wang, Hui, 2021. "Blockchain-based decentralized energy management platform for residential distributed energy resources in a virtual power plant," Applied Energy, Elsevier, vol. 294(C).
    19. Muhammad Awais & Nadeem Javaid & Khursheed Aurangzeb & Syed Irtaza Haider & Zahoor Ali Khan & Danish Mahmood, 2018. "Towards Effective and Efficient Energy Management of Single Home and a Smart Community Exploiting Heuristic Optimization Algorithms with Critical Peak and Real-Time Pricing Tariffs in Smart Grids," Energies, MDPI, vol. 11(11), pages 1-30, November.
    20. Alaa A. F. Husain & Maryam Huda Ahmad Phesal & Mohd Zainal Abidin Ab Kadir & Ungku Anisa Ungku Amirulddin & Abdulhadi H. J. Junaidi, 2021. "A Decade of Transitioning Malaysia toward a High-Solar PV Energy Penetration Nation," Sustainability, MDPI, vol. 13(17), pages 1-16, September.

    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:jsusta:v:11:y:2019:i:22:p:6287-:d:285040. 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.