A biased load manager home energy management system for low-cost residential building low-income occupants. (1st May 2018)

• Record Type: Journal Article
• Authors: Monyei, Chukwuka G.; Adewumi, Aderemi O.; Akinyele, Daniel; Babatunde, Olubayo M.; Obolo, Michael O.; Onunwor, Joshua C.
• Is Part Of: Energy. Volume 150(2018)
• Page Start: 822
• Page End: 838
• Publication Date: 2018-05-01
• Subjects: Low-cost residential buildings -- BLM-HEMS -- Hopping algorithm -- Consumer comfort -- Return on investment -- Carbon footprint; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2018.03.016
• Languages: English
• ISSNs: 0360-5442

Abstract

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. Highlights: Presents a load manager for low-income residential homes. Evaluates the contribution of the load manager in improving household comfort. Evaluates associated reduction in carbon emissions and electricity cost. Discusses and presents solution to the challenge of adopting the load manager.