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Sub-Saharan Africa has been at the epicenter of an ongoing global dialogue around the issue of energy poverty. More than half of the world’s population without access to modern energy services lives there. It also happens to be a sub-continent with plentiful renewable energy resource potential. Hydropower is one of them, and to a large extent it remains untapped. This study focuses on the technical assessment of small-scale hydropower (0.01⁻10 MW) in Sub-Saharan Africa. The underlying methodology was based on open source geospatial datasets, whose combination allowed a consistent evaluation of 712,615 km of river network spanning over 44 countries. Environmental, topological, and social constraints were included in the form of constraints in the optimization algorithm. The results are presented on a country and power pool basis.

The provision of modern energy services is recognised as a critical foundation for sustainable development, and is central to the everyday lives of people. Effective policies to dramatically expand modern energy access need to be grounded in a robust information-base. Metrics that can be used for comparative purposes and to track progress towards targets therefore represent an essential support tool. This paper reviews the relevant literature, and discusses the adequacy and applicability of existing instruments to measure energy poverty. Drawing on those insights, it proposes a new composite index to measure energy poverty. Both the associated methodology and initial results for several African countries are discussed. Whereas most existing indicators and composite indices focus on assessing the access to energy, or the degree of development related to energy, our new index – the Multidimensional Energy Poverty Index (MEPI) – focuses on the deprivation of access to modern energy services. It captures both the incidence and intensity of energy poverty, and provides a new tool to support policymaking.

Traditional methods of energy planning are likely to provide results that may be inappropriate in fragile and conflict-prone countries. The risks of violence and damage, or significant delays and cancellations in infrastructure development, are rife in these states. Thus, least-cost planning processes must explicitly address the inherent risks. While there are numerous statistical methods for dealing with decision making under uncertainty, few of them have been applied to power system planning and tailored for these situations. We present a general theoretical framing of the issue, and illustrate application of a very simple method to a case study of the Republic of South Sudan. We find that, in general, the resilience aspects, combined with modular and incremental benefits of distributed generation technologies and systems emerge as attractive options if the various risks of infrastructure development are included in modelling techniques.

The world's poor need more than a token supply of electricity. The goal should be to provide the power necessary to boost productivity and raise living standards.