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An Efficient Energy Management Approach Using Fog-as-a-Service for Sharing Economy in a Smart Grid

Author

Listed:
  • Adia Khalid

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

  • Sheraz Aslam

    (Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan
    Department of Computer Science, Information Technology University, Lahore 54000, Pakistan)

  • Khursheed Aurangzeb

    (College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia)

  • Syed Irtaza Haider

    (College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia)

  • Mahmood Ashraf

    (Federal Urdu University of Arts, Science and Technology, Islamabad 44000, Pakistan)

  • Nadeem Javaid

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

Abstract

An unprecedented opportunity is presented by smart grid technologies to shift the energy industry into the new era of availability, reliability and efficiency that will contribute to our economic and environmental health. Renewable energy sources play a significant role in making environments greener and generating electricity at a cheaper cost. The cloud/fog computing also contributes to tackling the computationally intensive tasks in a smart grid. This work proposes an energy efficient approach to solve the energy management problem in the fog based environment. We consider a small community that consists of multiple smart homes. A microgrid is installed at each residence for electricity generation. Moreover, it is connected with the fog server to share and store information. Smart energy consumers are able to share the details of excess energy with each other through the fog server. The proposed approach is validated through simulations in terms of cost and imported electricity alleviation.

Suggested Citation

  • Adia Khalid & Sheraz Aslam & Khursheed Aurangzeb & Syed Irtaza Haider & Mahmood Ashraf & Nadeem Javaid, 2018. "An Efficient Energy Management Approach Using Fog-as-a-Service for Sharing Economy in a Smart Grid," Energies, MDPI, vol. 11(12), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:12:p:3500-:d:190724
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Haghnegahdar, Lida & Chen, Yu & Wang, Yong, 2022. "Enhancing dynamic energy network management using a multiagent cloud-fog structure," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    2. Jones Luís Schaefer & Julio Cezar Mairesse Siluk & Patrícia Stefan de Carvalho & José Renes Pinheiro & Paulo Smith Schneider, 2020. "Management Challenges and Opportunities for Energy Cloud Development and Diffusion," Energies, MDPI, vol. 13(16), pages 1-27, August.
    3. Muhammad Shuaib Qureshi & Muhammad Bilal Qureshi & Muhammad Fayaz & Muhammad Zakarya & Sheraz Aslam & Asadullah Shah, 2020. "Time and Cost Efficient Cloud Resource Allocation for Real-Time Data-Intensive Smart Systems," Energies, MDPI, vol. 13(21), pages 1-25, October.
    4. Wilson Pavon & Esteban Inga & Silvio Simani & Maddalena Nonato, 2021. "A Review on Optimal Control for the Smart Grid Electrical Substation Enhancing Transition Stability," Energies, MDPI, vol. 14(24), pages 1-15, December.
    5. Uikyun Na & Eun-Kyu Lee, 2020. "Fog BEMS: An Agent-Based Hierarchical Fog Layer Architecture for Improving Scalability in a Building Energy Management System," Sustainability, MDPI, vol. 12(7), pages 1-28, April.
    6. Musaed Alhussein & Syed Irtaza Haider & Khursheed Aurangzeb, 2019. "Microgrid-Level Energy Management Approach Based on Short-Term Forecasting of Wind Speed and Solar Irradiance," Energies, MDPI, vol. 12(8), pages 1-27, April.
    7. Bilal Naji Alhasnawi & Basil H. Jasim & Maria Dolores Esteban & Josep M. Guerrero, 2020. "A Novel Smart Energy Management as a Service over a Cloud Computing Platform for Nanogrid Appliances," Sustainability, MDPI, vol. 12(22), pages 1-47, November.
    8. Bakar, Nur Najihah Abu & Bazmohammadi, Najmeh & Çimen, Halil & Uyanik, Tayfun & Vasquez, Juan C. & Guerrero, Josep M., 2022. "Data-driven ship berthing forecasting for cold ironing in maritime transportation," Applied Energy, Elsevier, vol. 326(C).
    9. 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.

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