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Implementation of a novel home energy management system (HEMS) architecture with solar photovoltaic system as supplementary source

Author

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  • Shakeri, Mohammad
  • Shayestegan, Mohsen
  • Reza, S.M. Salim
  • Yahya, Iskandar
  • Bais, Badariah
  • Akhtaruzzaman, Md
  • Sopian, Kamaruzzaman
  • Amin, Nowshad

Abstract

This study investigates a novel control algorithm for the home energy management system (HEMS) to monitor and schedule the electrical appliances to apply in any conventional houses. This is to reduce the electricity consumption and consequently electricity cost in places with time-of-use (TOU) pricing model. A hardware implementation is executed in a testbed house premise using in-house built control system, smart plugs as well as PV system as the supplementary source. In this system architecture, the overall consumption of the electrical appliances that run on the grid is limited by the algorithm and kept under the certain value that is fixed depending on the total consumption of the building and the capacity of the battery. If the predefined limit is crossed, the new appliances are shifted to run on battery instead of shifting to other time, and thereby human comfort is less violated. In the worst case scenario, where the electrical appliances are assumed to consume the maximum amount of electricity, a prototype implementation of the proposed algorithm achieves up to 15% of electricity cost reduction and ensures the minimum sacrifice in dweller's comfort.

Suggested Citation

  • Shakeri, Mohammad & Shayestegan, Mohsen & Reza, S.M. Salim & Yahya, Iskandar & Bais, Badariah & Akhtaruzzaman, Md & Sopian, Kamaruzzaman & Amin, Nowshad, 2018. "Implementation of a novel home energy management system (HEMS) architecture with solar photovoltaic system as supplementary source," Renewable Energy, Elsevier, vol. 125(C), pages 108-120.
    • Handle: RePEc:eee:renene:v:125:y:2018:i:c:p:108-120
    DOI: 10.1016/j.renene.2018.01.114
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    References listed on IDEAS

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    Cited by:

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    2. Mohammad Shakeri & Jagadeesh Pasupuleti & Nowshad Amin & Md. Rokonuzzaman & Foo Wah Low & Chong Tak Yaw & Nilofar Asim & Nurul Asma Samsudin & Sieh Kiong Tiong & Chong Kok Hen & Chin Wei Lai, 2020. "An Overview of the Building Energy Management System Considering the Demand Response Programs, Smart Strategies and Smart Grid," Energies, MDPI, vol. 13(13), pages 1-15, June.
    3. Binghui Han & Younes Zahraoui & Marizan Mubin & Saad Mekhilef & Mehdi Seyedmahmoudian & Alex Stojcevski, 2023. "Optimal Strategy for Comfort-Based Home Energy Management System Considering Impact of Battery Degradation Cost Model," Mathematics, MDPI, vol. 11(6), pages 1-26, March.
    4. Fahad R. Albogamy & Ghulam Hafeez & Imran Khan & Sheraz Khan & Hend I. Alkhammash & Faheem Ali & Gul Rukh, 2021. "Efficient Energy Optimization Day-Ahead Energy Forecasting in Smart Grid Considering Demand Response and Microgrids," Sustainability, MDPI, vol. 13(20), pages 1-29, October.
    5. López-Vargas, Ascensión & Fuentes, Manuel & Vivar, Marta, 2021. "Current challenges for the advanced mass scale monitoring of Solar Home Systems: A review," Renewable Energy, Elsevier, vol. 163(C), pages 2098-2114.
    6. Mohammad Shakeri & Nowshad Amin & Jagadeesh Pasupuleti & Abolfazl Mehbodniya & Nilofar Asim & Sieh Kiong Tiong & Foo Wah Low & Chong Tak Yaw & Nurul Asma Samsudin & Md Rokonuzzaman & Chong Kok Hen & C, 2020. "An Autonomous Home Energy Management System Using Dynamic Priority Strategy in Conventional Homes," Energies, MDPI, vol. 13(13), pages 1-14, June.
    7. Zhao, Xueyuan & Gao, Weijun & Qian, Fanyue & Ge, Jian, 2021. "Electricity cost comparison of dynamic pricing model based on load forecasting in home energy management system," Energy, Elsevier, vol. 229(C).
    8. Gholami, M. & Sanjari, M.J., 2021. "Multiobjective energy management in battery-integrated home energy systems," Renewable Energy, Elsevier, vol. 177(C), pages 967-975.
    9. Schmitz, William Ismael & Schmitz, Magdiel & Canha, Luciane Neves & Garcia, Vinícius Jacques, 2020. "Proactive home energy storage management system to severe weather scenarios," Applied Energy, Elsevier, vol. 279(C).
    10. Alexandru G. Berciu & Eva H. Dulf & Dan D. Micu, 2022. "Improving the Efficiency of Electricity Consumption by Applying Real-Time Fuzzy and Fractional Control," Mathematics, MDPI, vol. 10(20), pages 1-16, October.
    11. Mahmoud Elkazaz & Mark Sumner & Seksak Pholboon & Richard Davies & David Thomas, 2020. "Performance Assessment of an Energy Management System for a Home Microgrid with PV Generation," Energies, MDPI, vol. 13(13), pages 1-23, July.
    12. Gao, Yuan & Miyata, Shohei & Akashi, Yasunori, 2022. "Interpretable deep learning models for hourly solar radiation prediction based on graph neural network and attention," Applied Energy, Elsevier, vol. 321(C).
    13. Zurisaddai de la Cruz Severiche Maury & Ana Fernández Vilas & Rebeca P. Díaz Redondo, 2022. "Low-Cost HEM with Arduino and Zigbee Technologies in the Energy Sector in Colombia," Energies, MDPI, vol. 15(10), pages 1-19, May.
    14. Baum, Zvi & Palatnik, Ruslana Rachel & Ayalon, Ofira & Elmakis, David & Frant, Shimon, 2019. "Harnessing households to mitigate renewables intermittency in the smart grid," Renewable Energy, Elsevier, vol. 132(C), pages 1216-1229.

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