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Electrification pathways for Kenya-linking spatial electrification analysis and medium to long term energy planning
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Energy Systems Analysis.
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Energy Systems Analysis.
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Energy Systems Analysis.
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Energy Systems Analysis.
2017 (English)In: Environmental Research Letters, ISSN 1748-9326, E-ISSN 1748-9326, Vol. 12, no 9, article id 095008Article in journal (Refereed) Published
Abstract [en]

In September 2015 UN announced 17 Sustainable Development goals (SDG) from which goal number 7 envisions universal access to modern energy services for all by 2030. In Kenya only about 46% of the population currently has access to electricity. This paper analyses hypothetical scenarios, and selected implications, investigating pathways that would allow the country to reach its electrification targets by 2030. Two modelling tools were used for the purposes of this study, namely OnSSET and OSeMOSYS. The tools were soft-linked in order to capture both the spatial and temporal dynamics of their nature. Two electricity demand scenarios were developed representing low and high end user consumption goals respectively. Indicatively, results show that geothermal, coal, hydro and natural gas would consist the optimal energy mix for the centralized national grid. However, in the case of the low demand scenario a high penetration of stand-alone systems is evident in the country, reaching out to approximately 47% of the electrified population. Increasing end user consumption leads to a shift in the optimal technology mix, with higher penetration of mini-grid technologies and grid extension.

Place, publisher, year, edition, pages
Institute of Physics Publishing (IOPP), 2017. Vol. 12, no 9, article id 095008
Keywords [en]
Kenya, OSeMOSYS, optimization, OnSSET, off-grid, SDG
National Category
Environmental Sciences
Identifiers
URN: urn:nbn:se:kth:diva-214882DOI: 10.1088/1748-9326/aa7e18ISI: 000410459000003Scopus ID: 2-s2.0-85030751684OAI: oai:DiVA.org:kth-214882DiVA, id: diva2:1151367
Note

QC 20171023

Available from: 2017-10-23 Created: 2017-10-23 Last updated: 2018-02-27Bibliographically approved

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Mentis, DimitrisHowells, Mark I.

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