OnSSET - Revision history

Andreas Sahlberg at 17:53, 2 October 2025

2025-10-02T17:53:56Z

Dimitris Mentis at 15:19, 14 March 2017

2017-03-14T15:19:24Z

Dimitris Mentis: Dimitris Mentis moved page ONSSET to OnSSET

2017-03-14T14:19:24Z

Dimitris Mentis moved page ONSSET to OnSSET

Dimitris Mentis at 13:36, 14 March 2017

2017-03-14T13:36:59Z

Robbie Morrison: comma separated the list in the 'References to reports produced using the model' field

2017-03-14T10:42:51Z

comma separated the list in the 'References to reports produced using the model' field

Robbie Morrison: corrected abbreviation to "OnSSET" in the 'Short description' field, added python to the 'Data processing software' field (a bug that this field reports when no value is set)

2017-03-14T10:40:47Z

corrected abbreviation to "OnSSET" in the 'Short description' field, added python to the 'Data processing software' field (a bug that this field reports when no value is set)

Robbie Morrison: corrected abbreviation to "OnSSET", corrected the citation Mentis et al (2015) in the 'Citation reference' field and the associated 'Citation doi' field

2017-03-14T10:36:56Z

corrected abbreviation to "OnSSET", corrected the citation Mentis et al (2015) in the 'Citation reference' field and the associated 'Citation doi' field

Dimitris Mentis at 13:12, 14 December 2016

2016-12-14T13:12:41Z

Robbie Morrison: initial commit

2016-12-06T23:44:26Z

initial commit

New page

{{Model
|Full_Model_Name=OpeN Source Spatial Electrification Toolkit
|Acronym=ONSSET
|author_institution=KTH Royal Institute of Technology
|authors=Christopher Arderne
|source_download=https://github.com/KTH-dESA/PyOnSSET
|text_description=ONSSET is used to estimate, analyze, and visualize the most cost-effective electrification access option, be it grid, mini-grid, or stand-alone. It is designed to be used in developing countries like Ethiopia, India, and Nigeria.
|open_source_licensed=Yes
|license=MIT license (MIT)
|model_source_public=Yes
|Link to source=https://github.com/KTH-dESA/PyOnSSET
|open_future=No
|modelling_software=Python
|GUI=No
|technologies=Renewables, Conventional Generation
|Storage (Gas)=No
|Storage (Heat)=No
|math_modeltype=Optimization
|math_objective=Cost minimization
|is_suited_for_many_scenarios=No
|montecarlo=No
|Model input file format=No
|Model file format=No
|Model output file format=No
}}

@@ Line 3: / Line 3: @@
 |Acronym=OnSSET
 |author_institution=KTH Royal Institute of Technology
-|authors=Dimitrios Mentis,  Mark Howells, Holger Rogner, Alexandros Korkovelos, Christopher Arderne, Oliver Broad, Manuel Welsch, Francesco Fuso Nerini
+|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_persons=Dimitrios Mentis
+|contact_persons=Andreas Sahlberg
-|contact_email=mentis@kth.se
+|website=https://www.linkedin.com/company/onsset-open-source-spatial-electrification-tool
-|source_download=https://github.com/KTH-dESA/PyOnSSET
+|source_download=https://github.com/onsset
 |logo=Onsset logo 3.png
 |text_description=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.
 |Primary outputs=Optimal Electrification Mix, Investment Needs
-|Source of funding=SIDA, UNDESA, UNDP, IEA, ABB, World Bank
+|User documentation=https://onsset.readthedocs.io/en/latest/
 |open_source_licensed=Yes
 |license=MIT license (MIT)
 |model_source_public=Yes
-|Link to source=https://github.com/KTH-dESA/PyOnSSET
+|Link to source=https://github.com/OnSSET/onsset
 |open_future=No
 |modelling_software=Python
 |processing_software=Python
 |GUI=No
 |technologies=Renewables, Conventional Generation
 |Demand sectors=Households
@@ Line 26: / Line 28: @@
 |Storage (Heat)=No
 |georegions=Sub-Saharan Africa, developing Asia, Latin America
-|georesolution=1 km to 10 km
+|georesolution=Settlement level
 |timeresolution=Multi year
 |math_modeltype=Optimization
 |math_objective=Cost minimization
-|is_suited_for_many_scenarios=No
+|is_suited_for_many_scenarios=Yes
 |montecarlo=No
 |citation_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.
 |citation_doi=10.1016/j.esd.2015.09.007
-|report_references=IEA World Energy Outlook 2014, IEA World Energy Outlook 2015, IEA and World Bank Global Tracking Framework 2015
+|report_references=IEA World Energy Outlook 2014, 2015, 2019, 2021, 2022, IEA and World Bank Global Tracking Framework 2015
 |Model input file format=No
 |Model file format=No
 |Model output file format=No
 }}

@@ Line 3: / Line 3: @@
 |Acronym=OnSSET
 |author_institution=KTH Royal Institute of Technology
-|authors=Dimitrios Mentis, Francesco Fuso Nerini, Oliver Broad, Manuel Welsch, Alexandros Korkovelos, Christopher Arderne, Holger Rogner, Mark Howells
+|authors=Dimitrios Mentis,  Mark Howells, Holger Rogner, Alexandros Korkovelos, Christopher Arderne, Oliver Broad, Manuel Welsch, Francesco Fuso Nerini
 |contact_persons=Dimitrios Mentis
 |contact_email=mentis@kth.se

@@ Line 1: / Line 1: @@
 {{Model
-|Full_Model_Name=OpeN Source Spatial Electrification Toolkit
+|Full_Model_Name=Open Source Spatial Electrification Tool
 |Acronym=OnSSET
 |author_institution=KTH Royal Institute of Technology
@@ Line 7: / Line 7: @@
 |contact_email=mentis@kth.se
 |source_download=https://github.com/KTH-dESA/PyOnSSET
-|logo=ONSSET LOGO.png
+|logo=Onsset logo 3.png
 |text_description=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.
 |Primary outputs=Optimal Electrification Mix, Investment Needs
-|Source of funding=SIDA, UNDESA, IEA, ABB, World Bank
+|Source of funding=SIDA, UNDESA, UNDP, IEA, ABB, World Bank
 |open_source_licensed=Yes
 |license=MIT license (MIT)

@@ Line 34: / Line 34: @@
 |citation_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.
 |citation_doi=10.1016/j.esd.2015.09.007
-|report_references=IEA World Energy Outlook 2014
+|report_references=IEA World Energy Outlook 2014, IEA World Energy Outlook 2015, IEA and World Bank Global Tracking Framework 2015
 IEA World Energy Outlook 2015
 IEA and World Bank Global Tracking Framework 2015
 |Model input file format=No
 |Model file format=No
 |Model output file format=No
 }}

@@ Line 8: / Line 8: @@
 |source_download=https://github.com/KTH-dESA/PyOnSSET
 |logo=ONSSET LOGO.png
-|text_description=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.
+|text_description=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.
 |Primary outputs=Optimal Electrification Mix, Investment Needs
 |Source of funding=SIDA, UNDESA, IEA, ABB, World Bank
@@ Line 17: / Line 17: @@
 |open_future=No
 |modelling_software=Python
 |GUI=No
 |technologies=Renewables, Conventional Generation