Towards building smart energy systems in sub-Saharan Africa: A conceptual analytics of electric power consumption

John, T.M. and Ucheaga, E.G. and Olowo, O.O. and Badejo, J.A. and Atayero, A. A. (2017) Towards building smart energy systems in sub-Saharan Africa: A conceptual analytics of electric power consumption. In: IEEE co-sponsored Future Technologies Conference (FTC’16), 6 – 7 December 2016, Hyatt Fisherman's Wharf, San Francisco, CA, USA.

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Abstract

A fast emerging source of knowledge acquisition through inference from available data is analytics. The convergence of maturity, ubiquity and ease of deployment of Internet of Things (IoT) enabling technologies has engendered this possibility. The need to leverage on available data from credible sources to develop sustainable systems within the smart and connected communities (SCC) paradigm cannot be overemphasized. In this paper, the architecture of an IoT-enabled smart micro-grid system is proposed to harness the potentials of emerging independent power projects in sub-Saharan Africa. As a case study, this paper examines the interrelation between the economy and electric power consumption in Nigeria, Africa's energy giant and most populous nation, from 1981 to 2014 using the off-the-shelf IBM Watson analytics software. The predictive analytics tool provided an in-depth analysis of the determinants of energy-driven economic growth, as a basis for developing a sustainable smart energy system in Nigeria. Insights gained from this predictive analytics afford private investors, policy makers, consumers and other stakeholders an opportunity to work together to meet the increasing demand for energy production in sub-Saharan Africa. © 2016 IEEE.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	cited By 1; Conference of 2016 Future Technologies Conference, FTC 2016 ; Conference Date: 6 December 2016 Through 7 December 2016; Conference Code:126003
Uncontrolled Keywords:	Cyber Physical System; Economics; Electric power transmission networks; Electric power utilization; Electric utilities; Embedded systems; Internet of things; Predictive analytics; Privatization; Smart city, Data analytics; Electric power consumption; Enabling technologies; Independent power projects; Internet of Things (IOT); Smart energy systems; Smart Micro Grids; Sustainable systems, Smart power grids
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science Faculty of Engineering, Science and Mathematics > School of Engineering Sciences
Depositing User:	Dr. Joke Badejo
Date Deposited:	18 Sep 2018 10:02
Last Modified:	18 Sep 2018 10:02
URI:	http://eprints.covenantuniversity.edu.ng/id/eprint/11672

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