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| | |Acronym=OnSSET | | |Acronym=OnSSET |
| | |author_institution=KTH Royal Institute of Technology | | |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 | | |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. | | |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 | | |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/ |
| | + | |Source of funding=SIDA, UNDESA, UNDP, IEA, ABB, World Bank, GEAPP, SEforALL |
| | |open_source_licensed=Yes | | |open_source_licensed=Yes |
| | |license=MIT license (MIT) | | |license=MIT license (MIT) |
| | |model_source_public=Yes | | |model_source_public=Yes |
| − | |Link to source=https://github.com/KTH-dESA/PyOnSSET | + | |Link to source=https://github.com/OnSSET/onsset |
| | |open_future=No | | |open_future=No |
| | |modelling_software=Python | | |modelling_software=Python |
| | |processing_software=Python | | |processing_software=Python |
| | |GUI=No | | |GUI=No |
| | + | |sectors=Electricity, |
| | |technologies=Renewables, Conventional Generation | | |technologies=Renewables, Conventional Generation |
| | |Demand sectors=Households | | |Demand sectors=Households |
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| | |Storage (Heat)=No | | |Storage (Heat)=No |
| | |georegions=Sub-Saharan Africa, developing Asia, Latin America | | |georegions=Sub-Saharan Africa, developing Asia, Latin America |
| − | |georesolution=1 km to 10 km | + | |georesolution=Settlement level |
| | |timeresolution=Multi year | | |timeresolution=Multi year |
| | + | |network_coverage=transmission, distribution |
| | + | |Observation period=More than one year |
| | + | |Additional dimensions (Ecological)=Greenhouse gas emissions |
| | |math_modeltype=Optimization | | |math_modeltype=Optimization |
| | + | |math_modeltype_shortdesc=Technologies selected based on lowest Levelized Cost of Electricity (LCOE) for each settlement |
| | |math_objective=Cost minimization | | |math_objective=Cost minimization |
| − | |is_suited_for_many_scenarios=No | + | |is_suited_for_many_scenarios=Yes |
| | |montecarlo=No | | |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_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 | | |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 input file format=No |
| | |Model file format=No | | |Model file format=No |
| | |Model output file format=No | | |Model output file format=No |
| | }} | | }} |
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
IEA World Energy Outlook 2014, 2015, 2019, 2021, 2022, IEA and World Bank Global Tracking Framework 2015
