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Capacity building on geospatial electrification analysis for industrializing countries

KTH has been leading trainings on GIS and geospatial electrification modelling at the Summer Schools on Modelling Tools for Sustainable Development and the Energy Modelling Platforms for Africa. Participants include analysts from both the governmental sector, national utilities and academics in industrializing countries, as well as academics from Europe and North America. The participants have been introduced to geospatial electrification modelling in general, and practiced their skills with hands-on training on the Open Source Spatial Electrification Tool (OnSSET).

To date, more than 200 participants from over 50 countries have participated through the following trainings:

  • The Summer Schools on Modelling Tools for Sustainable Development in Trieste, Italy in 2018, 2019, 2021, 2022
  • The Energy Modelling Platform for Africa in Ethiopia (2018), Cape South Africa (2019) and Mauritius (2021)


Several hundred million people are without access to electricity. In order to quantify investment and technology requirements for electrification a geo-spatial approach is required as people and resources are geographically dispersed. And rural areas often have the lowest electrification rates, their geographies are of importance. The method focuses on the assessment and deployment of conventional and renewable energy technologies aiming at ensuring access to affordable, reliable, sustainable and modern energy for all. It is a complementary approach to existing energy planning models which do not consider geographical characteristics related to energy and aims to provide invaluable support to policy and decision makers on least-cost electrification strategies.

The approach is bottom up optimization energy modelling, that estimates, analyzes and visualizes the most cost effective electrification option (grid, mini grid & stand-alone) for the achievement of electricity access goals. To do so, it takes into account spatially explicit characteristics related to energy. Such data include population density and distribution, proximity to transmission and road network, nighttime lights, local renewable energy potential etc. The GIS data, methods and skills learned are transferable to other tools such as Network-planner, GEOSIM, REM and others. The tool used in these efforts (and by the WBG, IEA, UNDESA and others) is the Open Source Spatial Electrification Tool (OnSSET).

Within the framework of these events, as one of several entry points, the trainees will be trained on geospatial electrification modelling under the guidance of leading academics and researchers in the field of model-informed development strategies. They will get introduced to the basic principles of Geographic Information Systems (GIS) and learn how to use open access data in order to answer policy questions related to electrification. They will also learn to use OnSSET tool in order to investigate electrification investment scenarios for their country. The scope is to develop a first open source geospatial model that can be later expanded and used to support planning efforts towards the achievement of SDG7 and the provision of affordable, reliable, sustainable and modern electricity services for all by 2030 in the country.

Aim and objectives

The aim of the capacity building events is to provide training on geospatial electrification modelling to analysts from different sectors, to be able to better inform decision-making targeting universal access to electricity through a combination of centralized and decentralized electricity supply technologies.

Project partners

The schools have been organized and supported by numerous partners, including but not limited to the World Bank/ESMAP, ICTP, UNECA, UKAID/DFID, UNDP, CCG, University of Cape Town, University of Mauritius, OpTIMUS, Loughborough University.

Funding for participants has been provided by various partners for the different schools. KTH trainers have mainly been funded by the World Bank/ESMAP.

Timeframe: 2018 - present


For further information about this project, please contact Andreas Sahberg .

Babak Khavari
Babak Khavari
Nandi Moksnes
Nandi Moksnes
doctoral student
Jagruti Ramsing Thakur
Jagruti Ramsing Thakur
assistant professor
Shravan Kumar Pinayur Kannan
Shravan Kumar Pinayur Kannan
doctoral student
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