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Development of Home Energy Management Scheme for a Smart Grid Community

Author

Listed:
  • Md Mamun Ur Rashid

    (Department of Information Engineering and Computer Science, University of Trento, 38122 Trento, Italy
    Department of Electrical & Electronic Engineering, National Institute of Textile Engineering and Research (NITER), Dhaka 1350, Bangladesh)

  • Fabrizio Granelli

    (Department of Information Engineering and Computer Science, University of Trento, 38122 Trento, Italy)

  • Md. Alamgir Hossain

    (Capability Systems Centre, School of Engineering & Information Technology, University of New South Wales, Canberra 2612, Australia
    Department of Electrical and Electronic Engineering, Dhaka University of Engineering & Technology (DUET), Gazipur 1700, Bangladesh)

  • Md. Shafiul Alam

    (K. A. CARE Energy Research & Innovation Center, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia)

  • Fahad Saleh Al-Ismail

    (K. A. CARE Energy Research & Innovation Center, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia)

  • Ashish Kumar Karmaker

    (Department of Electrical and Electronic Engineering, Dhaka University of Engineering & Technology (DUET), Gazipur 1700, Bangladesh)

  • Md. Mijanur Rahaman

    (Department of Electrical and Electronic Engineering, Dhaka University of Engineering & Technology (DUET), Gazipur 1700, Bangladesh)

Abstract

The steady increase in energy demand for residential consumers requires an efficient energy management scheme. Utility organizations encourage household applicants to engage in residential energy management (REM) system. The utility’s primary goal is to reduce system peak load demand while consumer intends to reduce electricity bills. The benefits of REM can be enhanced with renewable energy sources (RESs), backup battery storage system (BBSS), and optimal power-sharing strategies. This paper aims to reduce energy usages and monetary cost for smart grid communities with an efficient home energy management scheme (HEMS). Normally, the residential consumer deals with numerous smart home appliances that have various operating time priorities depending on consumer preferences. In this paper, a cost-efficient power-sharing technique is developed which works based on priorities of appliances’ operating time. The home appliances are sorted on priority basis and the BBSS are charged and discharged based on the energy availability within the smart grid communities and real time energy pricing. The benefits of optimal power-sharing techniques with the RESs and BBSS are analyzed by taking three different scenarios which are simulated by C++ software package. Extensive case studies are carried out to validate the effectiveness of the proposed energy management scheme. It is demonstrated that the proposed method can save energy and reduce electricity cost up to 35% and 45% compared to the existing methods.

Suggested Citation

  • Md Mamun Ur Rashid & Fabrizio Granelli & Md. Alamgir Hossain & Md. Shafiul Alam & Fahad Saleh Al-Ismail & Ashish Kumar Karmaker & Md. Mijanur Rahaman, 2020. "Development of Home Energy Management Scheme for a Smart Grid Community," Energies, MDPI, vol. 13(17), pages 1-24, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:17:p:4288-:d:400959
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    References listed on IDEAS

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    Cited by:

    1. Francesco Mancini & Jacopo Cimaglia & Gianluigi Lo Basso & Sabrina Romano, 2021. "Implementation and Simulation of Real Load Shifting Scenarios Based on a Flexibility Price Market Strategy—The Italian Residential Sector as a Case Study," Energies, MDPI, vol. 14(11), pages 1-21, May.
    2. Md Mamun Ur Rashid & Majed A. Alotaibi & Abdul Hasib Chowdhury & Muaz Rahman & Md. Shafiul Alam & Md. Alamgir Hossain & Mohammad A. Abido, 2021. "Home Energy Management for Community Microgrids Using Optimal Power Sharing Algorithm," Energies, MDPI, vol. 14(4), pages 1-21, February.
    3. Ri Piao & Deok-Joo Lee & Taegu Kim, 2020. "Real-Time Pricing Scheme in Smart Grid Considering Time Preference: Game Theoretic Approach," Energies, MDPI, vol. 13(22), pages 1-19, November.
    4. Fernando V. Cerna & Mahdi Pourakbari-Kasmaei & Luizalba S. S. Pinheiro & Ehsan Naderi & Matti Lehtonen & Javier Contreras, 2021. "Intelligent Energy Management in a Prosumer Community Considering the Load Factor Enhancement," Energies, MDPI, vol. 14(12), pages 1-24, June.

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