IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i4p881-d495656.html
   My bibliography  Save this article

Optimal Fuzzy Energy Trading System in a Fog-Enabled Smart Grid

Author

Listed:
  • Khuram Shahzad

    (School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan)

  • Sohail Iqbal

    (School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan)

  • Hamid Mukhtar

    (Department of Computer Science, College of CIT, Taif University, Taif 21944, Saudi Arabia)

Abstract

With the recent technological advancements, it has become possible to conceive numerous valuable applications for efficient utilization of energy resources in a smart grid. As distributed energy generation and distributed storage systems become cost-effective, trading energy becomes a lucrative alternative for both prosumers and manufacturers. In this paper, we make use of fuzzy logic to propose a system for optimal energy trading in a fog-enabled smart grid set-up. The existing systems in this realm have inherited issues of network latency, computational expensiveness, information availability, scalability, and performance. Some systems require a specialized transmission line for energy trading and plenty of them based on the dedicated producer-consumer model, putting limits to their practical effectiveness. Our framework makes use of fog-computing infrastructure to address scalability, information availability, and network latency issues. We exploit the fuzzy logic paradigm to handle the issues with crisp values and to improve the computational efficiency of the system. Our model of energy-trading system incorporates various input parameters to decide on the excess energy, including real-time price, time of day, outdoor temperature, buyers’ interest, and storage capacity. Simulation results show that our proposed system possesses promising potential to maximize the profit of energy trading and to minimize electricity usage from the main grid.

Suggested Citation

  • Khuram Shahzad & Sohail Iqbal & Hamid Mukhtar, 2021. "Optimal Fuzzy Energy Trading System in a Fog-Enabled Smart Grid," Energies, MDPI, vol. 14(4), pages 1-16, February.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:4:p:881-:d:495656
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/4/881/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/4/881/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ye-Byoul Son & Jong-Hyuk Im & Hee-Yong Kwon & Seong-Yun Jeon & Mun-Kyu Lee, 2020. "Privacy-Preserving Peer-to-Peer Energy Trading in Blockchain-Enabled Smart Grids Using Functional Encryption," Energies, MDPI, vol. 13(6), pages 1-22, March.
    2. Ghulam Hafeez & Nadeem Javaid & Sohail Iqbal & Farman Ali Khan, 2018. "Optimal Residential Load Scheduling Under Utility and Rooftop Photovoltaic Units," Energies, MDPI, vol. 11(3), pages 1-27, March.
    3. Zunaira Nadeem & Nadeem Javaid & Asad Waqar Malik & Sohail Iqbal, 2018. "Scheduling Appliances with GA, TLBO, FA, OSR and Their Hybrids Using Chance Constrained Optimization for Smart Homes," Energies, MDPI, vol. 11(4), pages 1-30, April.
    4. Hafiz Majid Hussain & Nadeem Javaid & Sohail Iqbal & Qadeer Ul Hasan & Khursheed Aurangzeb & Musaed Alhussein, 2018. "An Efficient Demand Side Management System with a New Optimized Home Energy Management Controller in Smart Grid," Energies, MDPI, vol. 11(1), pages 1-28, January.
    5. Juho Hamari & Mimmi Sjöklint & Antti Ukkonen, 2016. "The sharing economy: Why people participate in collaborative consumption," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(9), pages 2047-2059, September.
    6. Jung-Hoon Lee & Sang-Hwa Chung & Won-Suk Kim, 2019. "Fog server deployment technique: An approach based on computing resource usage," International Journal of Distributed Sensor Networks, , vol. 15(1), pages 15501477188, January.
    7. Nadeem Javaid & Adnan Ahmed & Sohail Iqbal & Mahmood Ashraf, 2018. "Day Ahead Real Time Pricing and Critical Peak Pricing Based Power Scheduling for Smart Homes with Different Duty Cycles," Energies, MDPI, vol. 11(6), pages 1-28, June.
    8. Zhang, Chenghua & Wu, Jianzhong & Zhou, Yue & Cheng, Meng & Long, Chao, 2018. "Peer-to-Peer energy trading in a Microgrid," Applied Energy, Elsevier, vol. 220(C), pages 1-12.
    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. Seongwoo Lee & Joonho Seon & Byungsun Hwang & Soohyun Kim & Youngghyu Sun & Jinyoung Kim, 2024. "Recent Trends and Issues of Energy Management Systems Using Machine Learning," Energies, MDPI, vol. 17(3), pages 1-24, January.

    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. Muhammad Saidu Aliero & Muhammad Asif & Imran Ghani & Muhammad Fermi Pasha & Seung Ryul Jeong, 2022. "Systematic Review Analysis on Smart Building: Challenges and Opportunities," Sustainability, MDPI, vol. 14(5), pages 1-28, March.
    2. Makhadmeh, Sharif Naser & Khader, Ahamad Tajudin & Al-Betar, Mohammed Azmi & Naim, Syibrah & Abasi, Ammar Kamal & Alyasseri, Zaid Abdi Alkareem, 2019. "Optimization methods for power scheduling problems in smart home: Survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    3. Younes Zahraoui & Ibrahim Alhamrouni & Saad Mekhilef & M. Reyasudin Basir Khan & Mehdi Seyedmahmoudian & Alex Stojcevski & Ben Horan, 2021. "Energy Management System in Microgrids: A Comprehensive Review," Sustainability, MDPI, vol. 13(19), pages 1-33, September.
    4. 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).
    5. Rodrigues, Daniel L. & Ye, Xianming & Xia, Xiaohua & Zhu, Bing, 2020. "Battery energy storage sizing optimisation for different ownership structures in a peer-to-peer energy sharing community," Applied Energy, Elsevier, vol. 262(C).
    6. Soto, Esteban A. & Bosman, Lisa B. & Wollega, Ebisa & Leon-Salas, Walter D., 2022. "Comparison of net-metering with peer-to-peer models using the grid and electric vehicles for the electricity exchange," Applied Energy, Elsevier, vol. 310(C).
    7. Adamu Sani Yahaya & Nadeem Javaid & Fahad A. Alzahrani & Amjad Rehman & Ibrar Ullah & Affaf Shahid & Muhammad Shafiq, 2020. "Blockchain Based Sustainable Local Energy Trading Considering Home Energy Management and Demurrage Mechanism," Sustainability, MDPI, vol. 12(8), pages 1-28, April.
    8. 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).
    9. Ableitner, Liliane & Tiefenbeck, Verena & Meeuw, Arne & Wörner, Anselma & Fleisch, Elgar & Wortmann, Felix, 2020. "User behavior in a real-world peer-to-peer electricity market," Applied Energy, Elsevier, vol. 270(C).
    10. Hui Huang & Shilin Nie & Jin Lin & Yuanyuan Wang & Jun Dong, 2020. "Optimization of Peer-to-Peer Power Trading in a Microgrid with Distributed PV and Battery Energy Storage Systems," Sustainability, MDPI, vol. 12(3), pages 1-20, January.
    11. Rocha, Helder R.O. & Honorato, Icaro H. & Fiorotti, Rodrigo & Celeste, Wanderley C. & Silvestre, Leonardo J. & Silva, Jair A.L., 2021. "An Artificial Intelligence based scheduling algorithm for demand-side energy management in Smart Homes," Applied Energy, Elsevier, vol. 282(PA).
    12. Kanakadhurga, Dharmaraj & Prabaharan, Natarajan, 2022. "Demand side management in microgrid: A critical review of key issues and recent trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    13. Umer, Khalid & Huang, Qi & Khorasany, Mohsen & Afzal, Muhammad & Amin, Waqas, 2021. "A novel communication efficient peer-to-peer energy trading scheme for enhanced privacy in microgrids," Applied Energy, Elsevier, vol. 296(C).
    14. Mohammad Esmaeil Honarmand & Vahid Hosseinnezhad & Barry Hayes & Pierluigi Siano, 2021. "Local Energy Trading in Future Distribution Systems," Energies, MDPI, vol. 14(11), pages 1-19, May.
    15. Albana Ilo & Helmut Bruckner & Markus Olofsgard & Marketa Adamcova & Andrea Werner, 2023. "Viable Fully Integrated Energy Community Based on the Holistic LINK Approach," Energies, MDPI, vol. 16(6), pages 1-38, March.
    16. Karim L. Anaya & Michael G. Pollitt, 2021. "How to Procure Flexibility Services within the Electricity Distribution System: Lessons from an International Review of Innovation Projects," Energies, MDPI, vol. 14(15), pages 1-26, July.
    17. Yiqi Dong & Zuoji Dong, 2023. "Bibliometric Analysis of Game Theory on Energy and Natural Resource," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    18. Wang, Dongxiao & Qiu, Jing & Reedman, Luke & Meng, Ke & Lai, Loi Lei, 2018. "Two-stage energy management for networked microgrids with high renewable penetration," Applied Energy, Elsevier, vol. 226(C), pages 39-48.
    19. Serhat Burmaoglu & Ozcan Saritas, 2019. "An evolutionary analysis of the innovation policy domain: Is there a paradigm shift?," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 823-847, March.
    20. Matija Kostelac & Lin Herenčić & Tomislav Capuder, 2022. "Planning and Operational Aspects of Individual and Clustered Multi-Energy Microgrid Options," Energies, MDPI, vol. 15(4), pages 1-17, 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:4:p:881-:d:495656. 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.