Modelling an Artificial Intelligence-Based Energy Management for Household in Nigeria

Ohunene Ibrahim, Rabiat, Tambo, Erick, Tsuanyo, David and Nguedia, Axel, (2022). Modelling an Artificial Intelligence-Based Energy Management for Household in Nigeria. Engineering Letters, 30(1), 140-151

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  • Sub-type Journal article
    Author Ohunene Ibrahim, Rabiat
    Tambo, Erick
    Tsuanyo, David
    Nguedia, Axel
    Title Modelling an Artificial Intelligence-Based Energy Management for Household in Nigeria
    Appearing in Engineering Letters
    Volume 30
    Issue No. 1
    Publication Date 2022-03
    Place of Publication Hong Kong
    Publisher International Association of Engineers
    Start page 140
    End page 151
    Language eng
    Abstract Sub-Saharan Africa’s low access to electricity and high vulnerability to climate change can be anticipated to constrain the region’s future human and economic development prospects. The need for energy conservation, especially electricity, is of crucial importance as it is an economic solution to the problem of energy shortage and atmospheric carbon reduction. The role of Artificial intelligence (AI) has also been displayed by researchers in the promotion of energy management. Most of the past literature in the line of energy management strategies proposed various energy management models based on smart grid and smart meter technology, demand side management, home energy management schemes and management based on AI. This paper proposes an AI-based energy management for households in Nigeria. Genetic algorithm was used on smart meter-like data to optimize the energy consumption of households for 24 hours on a weekday and weekend. To achieve this aim, we determine the typical load profile of a mini-grid setting (for household and commercial load profile), develop a simulation of smart meter-like data and develop an energy management system to optimize electricity consumption during a weekday and weekend in a household. We corroborate our theoretical model with numerical results showing the energy (and consumption) saved during these periods. The algorithm will assist electricity consumers in rural communities to effectively manage their usage by avoiding wastage and the unnecessary payment for energy waste.
    Keyword Energy management
    Mini grid
    Sub-saharan Africa
    Smart system
    Copyright Holder The Authors
    Copyright Year 2022
    Copyright type Creative commons
    ISSN 18160948
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    Created: Thu, 09 Jun 2022, 22:26:19 JST by Aarti Basnyat on behalf of UNU EHS