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Open Source Spatial Electrification Tool
by KTH Royal Institute of Technology
Authors:
Andreas Sahlberg, Alexandros Korkovelos, Dimitrios Mentis, Babak Khavari, Mark Howells, Holger Rogner, Christopher Arderne, Oliver Broad, Manuel Welsch, Francesco Fuso Nerini, Julian Cantor
Contact:
Andreas Sahlberg
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OnSSET has been designed for identifying least-cost technology options to electrify areas presently unserved by grid-based electricity and to estimate associated investment needs related to electrification. OnSSET uses energy-related data and information on a geographical basis such as settlement sizes and locations, distances from existing and planned transmission network, power plants, economic activity, local renewable energy flows,road network, nighttime light etc.
Based on Python. Using Python for data processing.
Website / Documentation
Download
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 Open Source
MIT license (MIT)
Directly downloadable
 No data shipped
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| Model Scope |
Model type and solution approach |
| Model class
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| Sectors
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Electricity
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| Technologies
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Renewables, Conventional Generation
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| Decisions
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| Regions
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Sub-Saharan Africa, developing Asia, Latin America
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| Geographic Resolution
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Settlement level
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| Time resolution
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Multi year
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| Network coverage
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transmission, distribution
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| Model type
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Optimization
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Technologies selected based on lowest Levelized Cost of Electricity (LCOE) for each settlement
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| Variables
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| Computation time
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minutes
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| Objective
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Cost minimization
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| Uncertainty modeling
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| Suited for many scenarios / monte-carlo
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Yes
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References
Scientific references
Mentis, Dimitrios; Welsch, Manuel; Fuso Nerini, Francesco; Broad, Oliver; Howells, Mark; Bazilian, Morgan; Rogner, Holger (December 2015). "A GIS-based approach for electrification planning: a case study on Nigeria". Energy for Sustainable Development. 29: 142–150. doi:10.1016/j.esd.2015.09.007. ISSN 0973-0826.
https://dx.doi.org/10.1016/j.esd.2015.09.007
Reports produced using the model
IEA World Energy Outlook 2014, 2015, 2019, 2021, 2022, IEA and World Bank Global Tracking Framework 2015
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