A motivation for integrated resource assessments is that they can capture indirect cross-sectoral effects of sectoral policies. This work investigates the electricity system implications from the implementation of basin-wide electricity and water systems efficiency measures. The spatial scope includes the four states that share the Syr Darya River basin. Different interests dictate the management of water resources in the basin. They are necessary for irrigation downstream in spring and summer and upstream, for hydropower generation during winter. The study investigated options to decrease the need for electricity upstream through efficiency measures and by the expansion of regional electricity trade. The scenarios were simulated by developing a multi-country electricity system model using the open source energy modelling system (OSeMOSYS). The results show that lesser investments in hydropower capacity could be needed and less water required in winter. This would reduce pressure on shared water resources.

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.

The measurement units of yearly wind electricity and hydrogen production in the following sections of the previously published paper as titled above are now changed from (MWh/year and kTon/year) to (GWh/year and tons/year). These changes apply to all the measuring units in text and related tables of the following sections. All the results of this paper are still valid and unchanged. 

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.

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.

Nowadays, more than 620 million people in Africa live without access to electricity. Nowhere in the world is the chasm between available energy resources and access to electricity greater than on the African continent. With the exception of conventional hydropower, the share of renewable energy in the electricity mix remains insignificant, despite the considerable untapped renewable energy potential in the region. A critical issue in the development of renewable energy sources is the cost, which is a function of the resource availability, the geographic and topological characteristics of a studied area as well as the selected energy conversion technologies. This paper applies a detailed Geographic Information Systems (GIS) approach in order to identify the cost of generating electricity using onshore wind turbines considering several localization criteria. The levelized cost of wind generated electricity is calculated geospatially and shall be used as an indicator to compare different suitable sites at the pre-feasibility stage. The levelized cost of generating electricity varies between 0.04 and 0.17 USD/kWh, placing wind power in a cost competitive position in the electricity market of the continental countries.

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.

Developing countries confront the challenge of generating more electricity to meet demands in a sustainable manner. According to the World Bank’s 2015 Global Tracking Framework, roughly 15% of world population (or 1.1 billion people) lack access to electricity, and many more rely on poor quality electricity supplies. In September 2015, the United Nations General Assembly adopted Agenda 2030 comprised of a set of 17 Sustainable Development Goals (SDGs) and defined by 169 targets. “Ensuring access to affordable, reliable, sustainable and modern energy for all by 2030” is the seventh goal (SDG7). While energy access refers to more than electricity, it is the central focus of this work.

Models addressing electrification and access typically need large volumes of reliable energy-related data and information, which in most developing countries have been limited or not available. This paucity of information has decelerated energy planning in the developing World. That situation has fundamentally changed with increasing availability and application of Geographic Information Systems (GIS). GIS layers can provide location specific energy-related information that has not been previously accessible. The focus of this thesis lies on integrating a simple electricity supply model into GIS. In so doing a novel open source spatial electrification tool is developed. It estimates power capacity needs and associated investment (and other) costs for achieving universal access to electricity in developing countries.

The dissertation includes a cover essay and six appended papers presenting quantitative methods on coupling selected aspects of GIS and energy systems. It strives to answer three key research questions. 

The first research question is: What is the spatially explicit renewable energy potential that can be technically and economically exploited? This information is currently either missing or scattered in developing countries. The provision of low cost, locally available energy can provide a significant opportunity to empower a better standard of living. The first paper presents a GIS based approach to assess the onshore technical wind energy potential on the African continent by applying socioeconomic and geographic restrictions regarding the localization of wind farms and state of the art wind data analysis. The second paper builds on this knowledge and moves one step further by assessing the economic potential and providing cost indicators to assess the viability of wind power (this time in India). The third paper maps the economic wind power potential in Africa based on the methodologies developed in the two preceding papers. Not only wind power but most energy resources have a spatial nature and their availability is linked to geography. Evaluating these other energy sources (solar, hydro etc.) are included and analysed in Papers IV-VI.

The second research question is: what is the least-cost set of technologies needed to meet different levels of electricity use accounting for different geographies? Increasing access to electricity effectively requires, inter alia, strategies and programmes that address and account for the geographical, infrastructural and socioeconomic characteristics of a country or region. Paper IV introduces a GIS based methodology to inform electrification planning. It builds on the previous work by taking into account the techno-economic wind, and other resource mapping. This methodology is applied in Nigeria in order to determine the least cost technology mix considering the country’s infrastructure and resource availability on a spatial basis. Paper V utilizes this method and in so doing demonstrates the importance of geospatial calculations in energy access planning. It highlights differences in investment estimates between alternate scenarios with regards to energy demand and technology deployment. Paper VI enhances this methodology and applies it to every square kilometre of Sub-Saharan Africa. The method is subsequently implemented in an Open Source Spatial Electrification Tool (OnSSET) to facilitate education, repeatability and further research.

Finally, the third question is: Are there gains to be had by linking geographically explicit analysis with typical (non-spatially explicit) long term energy systems models? The work shows that not only do long-term systems models influence geospatially optimal technology deployment. But vice versa, their output influences long term systems models’ investment profile.  That is because the geospatial disaggregation allows for a better determination of grid versus off-grid connections, and in turn power demand on the national grid. This thesis demonstrates that energy system models should take into consideration the geographic dimension of energy-related parameters, as these play a fundamental role in determining the optimal energy system of a region.