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Mid- to long-term capacity planning for a reliable power system in Kenya

تخطيط القدرات على المدى المتوسط إلى الطويل لنظام طاقة موثوق به في كينيا
Authors: Kihara, Mungai; Lubello, Pietro; Millot, Ariane; Akute, Michelle; Kilonzi, Julius; Kitili, Monicah; Mukuri, Felister; +6 Authors

Mid- to long-term capacity planning for a reliable power system in Kenya

Abstract

Over the coming decades, Kenya is likely to see a large increase in electricity demand driven by economic growth and wider electrification of different sectors. At the same time, Kenya remains committed to maintain its high share of renewable generation. This study proposes a novel framework to soft link OSeMOSYS, a capacity expansion model (CEM), and FlexTool, a production cost model (PCM), to address the limitations of CEMs in the representation of variable renewable energy sources. Results show the effectiveness of the methodology in identifying critical grid issues that would have been missed by the capacity expansion model alone, especially in the case of a higher penetration of non-dispatchable sources. They also confirm that based on robust planning approaches, Kenya is well placed to maintain its very low carbon generation system under different demand growth projections, leveraging on firm generation from geothermal and high wind potential.

Keywords

Energy scenarios, Energy Engineering and Power Technology, Energy modelling, Energy industries. Energy policy. Fuel trade, Quantum mechanics, Term (time), Engineering, Soft linking, FOS: Electrical engineering, electronic engineering, information engineering, Indoor Air Pollution in Developing Countries, Risk analysis (engineering), Business, Electrical and Electronic Engineering, Energy, Energy Modeling, Integration of Renewable Energy Systems in Power Grids, Physics, Hydrogen Energy Systems and Technologies, Pollution, Computer science, Kenya, Power system planning, Power Grid Flexibility, Physical Sciences, Environmental Science, HD9502-9502.5

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    6
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Average
Top 10%
Related to Research communities
Energy Research