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Computer-based Decision Making Systems for Improved Energy Access in Sub-Saharan Africa

Taha Selim Ustun
School of Electrical and Computer Enginnering, Carnegie Mellon University, PA, USA

Abstract—Nearly 20% of the world’s, and 60 to 80 % of Sub-Saharan Africa’s, population does not have access to electricity, and because of the prohibitive cost of constructing traditional generation, transmission and distribution systems, it is unlikely many of these people will be connected to the electrical grid for many years. Consequently, highly distributed off-grid electrical systems will be the only way a large percentage of the unreached households will have even basic electrical service in the foreseeable future. Nevertheless, most governmental programs in emerging economies are focusing exclusively on the development of the electrical grid with larger-scale grid-connected power supplies. Private investors for generation facilities are wooed with long-term power-purchase agreements and grid power is heavily subsidized. In contrast, few incentives offered for deploying off-grid power, so these projects have been carried out with donor funding rather than private investment. New technologies and business models are needed to provide first-access to energy that is economically and environmentally sustainable. Recently, some private companies have begun to offer off-grid household and micro-grid systems with business models designed for rural customers in emerging economies. However, all of these projects are tailored-made, one-time applications with no interest in scalability or replicability. There is an absolute need to create a toolbox for Energy Access Planning in underserved locations. With the help of these tools, a systematic approach can be developed for planning, studying and sizing Renewable Energy projects. This paper explains the developed Computer-based First-access Demand Estimation tool. It is a step towards creating a complete Energy planning toolbox which can support systematic Energy planning.

Index Terms—off-grid microgrids, renewable energy, planning tools, energy policy, sustainable development, rural electrification

Cite: Taha Selim Ustun, "Computer-based Decision Making Systems for Improved Energy Access in Sub-Saharan Africa," Jounal of Automation and Control Engineering, Vol. 4, No. 3, pp. 247-251, June, 2016. doi: 10.18178/joace.4.3.247-251
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