Explore the vast range of titles available.

In September 2015, the United Nations General Assembly adopted Agenda 2030, which comprises a set of 17 Sustainable Development Goals (SDGs) defined by 169 targets. 'Ensuring access to affordable, reliable, sustainable and modern energy for all by 2030' is the seventh goal (SDG7). While access to energy refers to more than electricity, the latter is the central focus of this work. According to the World Bank's 2015 Global Tracking Framework, roughly 15% of the world's population (or 1.1 billion people) lack access to electricity, and many more rely on poor quality electricity services. The majority of those without access (87%) reside in rural areas. This paper presents results of a geographic information systems approach coupled with open access data. We present least-cost electrification strategies on a country-by-country basis for Sub-Saharan Africa. The electrification options include grid extension, mini-grid and stand-alone systems for rural, peri-urban, and urban contexts across the economy. At low levels of electricity demand there is a strong penetration of standalone technologies. However, higher electricity demand levels move the favourable electrification option from stand-alone systems to mini grid and to grid extensions.

In September 2015 UN announced 17 Sustainable Development goals (SDG) from which goal number 7 envisions universal access to modern energy services for all by 2030. In Kenya only about 46% of the population currently has access to electricity. This paper analyses hypothetical scenarios, and selected implications, investigating pathways that would allow the country to reach its electrification targets by 2030. Two modelling tools were used for the purposes of this study, namely OnSSET and OSeMOSYS. The tools were soft-linked in order to capture both the spatial and temporal dynamics of their nature. Two electricity demand scenarios were developed representing low and high end user consumption goals respectively. Indicatively, results show that geothermal, coal, hydro and natural gas would consist the optimal energy mix for the centralized national grid. However, in the case of the low demand scenario a high penetration of stand-alone systems is evident in the country, reaching out to approximately 47% of the electrified population. Increasing end user consumption leads to a shift in the optimal technology mix, with higher penetration of mini-grid technologies and grid extension.

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.

We have identified input values that were not harmonized with the paper and have therefore submitted this corrigendum. Qualitatively, there are no major differences between the two versions, and the insights generated are unchanged. However, part of the results, figures and discussion needed to be updated based on the new findings. We present those in the form of a corrigendum. In the model runs there were input parameters that were not harmonized with the published paper as seen in annex in table 1. Therefore, to amend the incurred values, we have re-run the model and updated the following sections of the paper.

Access to modern energy services is a precondition to improving livelihoods and building resilience against climate change. Still, electricity reaches only about half of the population in Sub-Saharan Africa (SSA), while about 40% live under the poverty line. Heavily reliant on the agriculture sector and increasingly affected by prolonged droughts, small-scale irrigation could be instrumental for development and climate change adaptation in SSA countries. A bottom-up understanding of the demand for irrigation and associated energy services is essential for designing viable energy supply options in an effective manner. Using Uganda as a case study, the study introduces a GIS-based methodology for the estimation of groundwater irrigation requirements through which energy demand is derived. Results are generated for two scenarios: (a) a reference scenario and (b) a drought scenario. The most critical need is observed in the northern and southern regions of the country. The total annual irrigation demand is estimated to be ca. 90 thousand m3, with the highest demand observed in the months of December through February, with an average irrigation demand of 445 mm per month. The highest energy demand is observed in the northern part of the study area in January, reaching 48 kWh/ha. The average energy demand increases by 67% in the drought scenario. The study contributes to current gaps in the existing literature by providing a replicable methodological framework and data aimed at facilitating energy system planning through the consideration of location-specific characteristics at the nexus of energy–water–agriculture.

The authors wish to make a change in author names (adding new author—Dimitrios Mentis) to this paper [...]

We have identified input values that were not harmonized with the paper and have therefore submitted this corrigendum. Qualitatively, there are no major differences between the two versions, and the insights generated are unchanged. However, part of the results, figures and discussion needed to be updated based on the new findings. We present those in the form of a corrigendum. In the model runs there were input parameters that were not harmonized with the published paper as seen in annex in table 1. Therefore, to amend the incurred values, we have re-run the model and updated the following sections of the paper.

The authors wish to make a change in author names (adding new author—Dimitrios Mentis) to this paper [1]: Author Contributions On page 19, author contributions are updated as follows: Conceptualization, A.K., D.M. and M.H.; Methodology, A.K., A.S., B.K. and D.M.; Software, A.K., B.K., A.S. and C.A.; Validation, M.H.; Formal Analysis, A.K.; Investigation, A.K.; Resources, A.K. and B.K.; Data Curation, A.K., B.K. and A.S.; Writing—Original Draft Preparation, A.K.; Writing—Review and Editing, A.K., D.M., M.H., C.A.; Visualization, A.K. and B.K.; Supervision, M.H.; Project Administration, M.H.; Funding Acquisition, M.H., D.M. and A.K. All authors have read and agreed to the published version of the manuscript. Funding On page 19, funding sources are updated as follows: This research was funded by the World Bank under the contract number 7185716 and partially by (a) the Swedish Center for Smart Grids and Energy Storage (SweGRIDS-ABB) under grant VF-2015-0018 and (b) the ÅForsk Foundation under grant 17-604. The authors would like to apologize for any inconvenience caused to the readers and contributors by these changes. The changes do not a ect the scientific results. The manuscript will be updated, and the original will remain online on the article webpage, with a reference to this correction.

Roughly two billion people live in areas that regularly suffer from conflict, violence, and instability. Infrastructure development in those areas is very difficult to implement and fund. As an example, electrification systems face major challenges such as ensuring the security of the workforce or reliability of power supply. This paper presents electrification results from an explorative methodology, where the costs and risks of conflict are explicitly considered in a geo-spatial, least cost electrification model. Discount factor and risk premium adjustments are introduced per technology and location in order to examine changes in electrification outlooks in Afghanistan. Findings indicate that the cost optimal electrification mix is very sensitive to the local context; yet, certain patterns emerge. Urban populations create a strong consumer base for grid electricity, in some cases even under higher risk. For peri-urban and rural areas, electrification options are more sensitive to conflict-induced risk variation. In this paper, we identify these inflection points, quantify key decision parameters, and present policy recommendations for universal electrification of Afghanistan by 2030.

Kenya has made significant progress towards universal electrification. Since 2010, access to electricity has increased by more than 7% annually across the country. According to Kenya Census data, while grid-powered homes grew steadily from 16% in 2005 to 50.4% in 2019, solar-powered homes also tracked considerable growth, increasing from about 2% to 19% during the same period. According to 2019 census data, seven counties in northern Kenya experience both a low adoption of solar home systems and the grid.