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| | |Acronym=ONSSET | | |Acronym=ONSSET |
| | |author_institution=KTH Royal Institute of Technology | | |author_institution=KTH Royal Institute of Technology |
| − | |authors=Christopher Arderne | + | |authors=Dimitrios Mentis, Francesco Fuso Nerini, Oliver Broad, Manuel Welsch, Alexandros Korkovelos, Christopher Arderne, Holger Rogner, Mark Howells |
| | + | |contact_persons=Dimitrios Mentis |
| | + | |contact_email=mentis@kth.se |
| | |source_download=https://github.com/KTH-dESA/PyOnSSET | | |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. | + | |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. |
| | + | |
| | + | |
| | + | |Primary outputs=Optimal Electrification Mix, Investment Needs |
| | + | |Source of funding=SIDA, UNDESA, IEA, ABB, World Bank |
| | |open_source_licensed=Yes | | |open_source_licensed=Yes |
| | |license=MIT license (MIT) | | |license=MIT license (MIT) |
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| | |GUI=No | | |GUI=No |
| | |technologies=Renewables, Conventional Generation | | |technologies=Renewables, Conventional Generation |
| | + | |Demand sectors=Households |
| | + | |Energy carriers (Renewable)=Hydro, Sun, Wind |
| | + | |Transfer (Electricity)=Distribution, Transmission |
| | |Storage (Gas)=No | | |Storage (Gas)=No |
| | |Storage (Heat)=No | | |Storage (Heat)=No |
| | + | |georegions=Sub-Saharan Africa, developing Asia, Latin America |
| | + | |georesolution=1 km to 10 km |
| | + | |timeresolution=Multi year |
| | |math_modeltype=Optimization | | |math_modeltype=Optimization |
| | |math_objective=Cost minimization | | |math_objective=Cost minimization |
| | |is_suited_for_many_scenarios=No | | |is_suited_for_many_scenarios=No |
| | |montecarlo=No | | |montecarlo=No |
| | + | |citation_references=Mentis, D., Welsch, M., Fuso Nerini, F., Broad, O., Howells, M., Bazil-ian, M., Rogner, H., 2015. A GIS-based approach for electrification planning—A case study on Nigeria. Elsevier Energy for Sustainable Development. 29, 142–150. |
| | + | |citation_doi=Mentis, D., Welsch, M., Fuso Nerini, F., Broad, O., Howells, M., Bazil-ian, M., Rogner, H., 2015. A GIS-based approach for electrification planning—A case study on Nigeria. Elsevier Energy for Sustainable Development. 29, 142–150. |
| | + | |report_references=IEA World Energy Outlook 2014 |
| | + | IEA World Energy Outlook 2015 |
| | + | 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, D., Welsch, M., Fuso Nerini, F., Broad, O., Howells, M., Bazil-ian, M., Rogner, H., 2015. A GIS-based approach for electrification planning—A case study on Nigeria. Elsevier Energy for Sustainable Development. 29, 142–150.
https://dx.doi.org/Mentis, D., Welsch, M., Fuso Nerini, F., Broad, O., Howells, M., Bazil-ian, M., Rogner, H., 2015. A GIS-based approach for electrification planning—A case study on Nigeria. Elsevier Energy for Sustainable Development. 29, 142–150.
IEA World Energy Outlook 2014
IEA World Energy Outlook 2015
IEA and World Bank Global Tracking Framework 2015
