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Assessment of optimal pathways for power generation system in Ghana

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dc.contributor.author Awopone A.K.
dc.contributor.author Zobaa A.F.
dc.contributor.author Banuenumah W.
dc.date.accessioned 2022-10-31T15:05:40Z
dc.date.available 2022-10-31T15:05:40Z
dc.date.issued 2017
dc.identifier.issn 23311916
dc.identifier.other 10.1080/23311916.2017.1314065
dc.identifier.uri http://41.74.91.244:8080/handle/123456789/511
dc.description Awopone, A.K., Department of Computer and Electronic Engineering, Brunel University London, Uxbridge, UB8 3PH, United Kingdom; Zobaa, A.F., Department of Computer and Electronic Engineering, Brunel University London, Uxbridge, UB8 3PH, United Kingdom; Banuenumah, W., Department of Automotive and Electrical Engineering, University of Education Winneba, P.O. Box 1277, Kumasi, Ghana en_US
dc.description.abstract This study applied the Open Source Energy Modelling System (OSeMOSYS), an optimisation model for long term energy planning, which is integrated in Long-range Energy Alternatives Planning (LEAP) to develop optimal generation pathways and dispatch scheduling of selected generating technologies for power generation in Ghana. Simulating conventional and non-conventional energy technologies, the study examines the technological, economic and environmental implications of renewable energy policies from 2010 to 2040. Sensitivity analyses were undertaken to determine the effect of varied development in non-conventional renewable energy technologies investment cost as well as fuel prices. The findings suggest that, with a comprehensive implementation of energy efficiency and other strategies, renewable energy technologies can contribute more than 70% of the generation requirement in Ghana by 2040. This will result in significant economic and environmental benefits as well as sustainability of the energy sector. � 2017 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. en_US
dc.publisher Cogent OA en_US
dc.subject Ghana en_US
dc.subject greenhouse gases en_US
dc.subject LEAP en_US
dc.subject optimisation en_US
dc.subject renewable energy en_US
dc.subject scenario en_US
dc.title Assessment of optimal pathways for power generation system in Ghana en_US
dc.type Article en_US


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