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A Cost-Efficient-Based Cooperative Allocation of Mining Devices and Renewable Resources Enhancing Blockchain Architecture

Author

Listed:
  • Mohamed A. Mohamed

    (Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61519, Egypt)

  • Seyedali Mirjalili

    (Center for Artificial Intelligence Research and Optimisation, Torrens University Australia, Brisbane, QLD 4006, Australia
    Yonsei Frontier Lab, Yonsei University, Seoul 03722, Korea)

  • Udaya Dampage

    (Faculty of Engineering, Kotelawala Defence University, Kandawala Estate, Ratmalana 10390, Sri Lanka)

  • Saleh H. Salmen

    (Department of Botany and Microbiology, College of Science, King Saud University, Riyadh 11451, Saudi Arabia)

  • Sami Al Obaid

    (Department of Botany and Microbiology, College of Science, King Saud University, Riyadh 11451, Saudi Arabia)

  • Andres Annuk

    (Chair of Energy Application Engineering, Institute of Technology, Estonian University of Life Sciences, 51006 Tartu, Estonia)

Abstract

The impressive furtherance of communication technologies has exhorted industrial companies to link-up these developments with their own abilities with the target of efficiency enhancement through smart supervision and control. With this in mind, the blockchain platform is a prospective solution for merging communication technologies and industrial infrastructures, but there are several challenges. Such obstacles should be addressed to effectively adopt this technology. One of the most recent challenges relative to adopting blockchain technology is the energy consumption of miners. Thus, providing an accurate approach that addresses the underlying cause of the problem will carry weight in the future. This work addresses managing the energy consumption of miners by using the advantage of distributed generation resources (DGRs). Along the same vein, it appears that achieving the optimal solution requires executing the modified reconfirmation of DGRs and miners (indeed, mining pool systems) in the smart grid. In order to perform this task, this article utilizes the Intelligent Priority Selection (IPS) method since this method is up to snuff for corporative allocation. In order to find practical solutions for this problem, the uncertainty is also modeled as a credible index highly correlated with the load and generation. All in all, it can be said that the outcome of this research study can help researchers in the field of enhancement of social welfare by using the proposed technology.

Suggested Citation

  • Mohamed A. Mohamed & Seyedali Mirjalili & Udaya Dampage & Saleh H. Salmen & Sami Al Obaid & Andres Annuk, 2021. "A Cost-Efficient-Based Cooperative Allocation of Mining Devices and Renewable Resources Enhancing Blockchain Architecture," Sustainability, MDPI, vol. 13(18), pages 1-24, September.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:18:p:10382-:d:637576
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. Xepapadeas, Petros, 2023. "Multi-agent, multi-site resource allocation under quotas with a Stackelberg leader and network externalities," Economic Modelling, Elsevier, vol. 121(C).
    2. Jian Chen & Tao Jin & Mohamed A. Mohamed & Andres Annuk & Udaya Dampage, 2022. "Investigating the Impact of Wind Power Integration on Damping Characteristics of Low Frequency Oscillations in Power Systems," Sustainability, MDPI, vol. 14(7), pages 1-23, March.
    3. Wei Hou & Rita Yi Man Li & Thanawan Sittihai, 2022. "Management Optimization of Electricity System with Sustainability Enhancement," Sustainability, MDPI, vol. 14(11), pages 1-17, May.
    4. Vinoth Kumar Ponnusamy & Padmanathan Kasinathan & Rajvikram Madurai Elavarasan & Vinoth Ramanathan & Ranjith Kumar Anandan & Umashankar Subramaniam & Aritra Ghosh & Eklas Hossain, 2021. "A Comprehensive Review on Sustainable Aspects of Big Data Analytics for the Smart Grid," Sustainability, MDPI, vol. 13(23), pages 1-35, December.
    5. Qunpeng Fan, 2022. "Management and Policy Modeling of the Market Using Artificial Intelligence," Sustainability, MDPI, vol. 14(14), pages 1-14, July.

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