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A biased load manager home energy management system for low-cost residential building low-income occupants

Author

Listed:
  • Monyei, Chukwuka G.
  • Adewumi, Aderemi O.
  • Akinyele, Daniel
  • Babatunde, Olubayo M.
  • Obolo, Michael O.
  • Onunwor, Joshua C.

Abstract

This research paper presents the development of a biased load manager home energy management system for low-cost residential building occupants. As a smart grid framework, the proposed load manager coordinates the operation of the inverter system of a low cost residential apartment consisting of rooftop solar photovoltaic panels, converter and battery, and provides a platform for discriminating residential loads into on-grid and off-grid supply classes while maximizing solar irradiance for optimum battery charging and improving consumer comfort from base levels. Modelled in a Matlab simulation environment, the system incorporates a converter system for maximum power point tracking using a hopping algorithm, with a dedicated mechanism for smart dispatch of specified loads to meet the users' comfort based on the priority ranking of the loads. Results obtained indicate a 34% reduction in electricity cost, 26% reduction in carbon emissions and a 4% increase in comfort level for the photovoltaic/battery/utility option compared to the utility only option. The results further show that cost is a major factor affecting the users' comfort and not necessarily dispatch of appliances to meet energy needs. The research can be useful for encouraging the adoption of the photovoltaic/battery/utility option by low/middle income energy users in developing countries.

Suggested Citation

  • Monyei, Chukwuka G. & Adewumi, Aderemi O. & Akinyele, Daniel & Babatunde, Olubayo M. & Obolo, Michael O. & Onunwor, Joshua C., 2018. "A biased load manager home energy management system for low-cost residential building low-income occupants," Energy, Elsevier, vol. 150(C), pages 822-838.
  • Handle: RePEc:eee:energy:v:150:y:2018:i:c:p:822-838
    DOI: 10.1016/j.energy.2018.03.016
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    Citations

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    Cited by:

    1. Adlband, Nahid & Biguesh, Mehrzad & Mohammadi, Mohammad, 2020. "A privacy-preserving and aggregate load controlling decentralized energy consumption scheduling scheme," Energy, Elsevier, vol. 198(C).
    2. Ouedraogo, Kiswendsida Elias & Ekim, Pınar Oğuz & Demirok, Erhan, 2023. "Feasibility of low-cost energy management system using embedded optimization for PV and battery storage assisted residential buildings," Energy, Elsevier, vol. 271(C).
    3. Huang, Zhijia & Wang, Fang & Lu, Yuehong & Chen, Xiaofeng & Wu, Qiqi, 2023. "Optimization model for home energy management system of rural dwellings," Energy, Elsevier, vol. 283(C).
    4. de Souza Dutra, Michael David & Anjos, Miguel F. & Le Digabel, Sébastien, 2019. "A general framework for customized transition to smart homes," Energy, Elsevier, vol. 189(C).

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