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

Monyei, Chukwuka; Adewumi, Aderemi O.; Akinyele, Daniel; Babatunde, Olubayo M.; Obolo, Michael O.; Onunwor, Joshua C.

Abstract

© 2018 Elsevier Ltd 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.

Citation

Monyei, C., Adewumi, A. O., Akinyele, D., Babatunde, O. M., Obolo, M. O., & Onunwor, J. C. (2018). A biased load manager home energy management system for low-cost residential building low-income occupants. Energy, 150, 822-838. https://doi.org/10.1016/j.energy.2018.03.016

• Journal Article Type: Article
• Acceptance Date: Mar 3, 2018
• Publication Date: May 1, 2018
• Deposit Date: Dec 20, 2018
• Publicly Available Date: Mar 5, 2019
• Journal: Energy
• Print ISSN: 0360-5442
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 150
• Pages: 822-838
• DOI: https://doi.org/10.1016/j.energy.2018.03.016
• Keywords: low-cost residential buildings, BLM-HEMS, hopping algorithm, consumer comfort, return on investment, carbon footprint
• Public URL: https://uwe-repository.worktribe.com/output/868506
• Publisher URL: http://dx.doi.org/10.1016/j.energy.2018.03.016