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Predictive Factors Associated with Solar Energy Development in Laikipia District Central Kenya

Environmental Health Sciences, California State University, East Bay 25800 Carlos Bee Blvd., Hayward 94542, CA,, United States

Published: 15 Oct 2015.
Editor(s): H Hadiyanto
Open Access Copyright (c) 2015 The Authors. Published by Centre of Biomass and Renewable Energy (CBIORE)
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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The abundance of sunlight and the availability affordable solar technologies in many areas far from grid-based electricity has sparked the development of renewable energy technologies (RETs) which tap solar radiation energy to provide electricity. A study on solar photovoltaics (SPVs) use and utilization took place in the Wiyumiririe Location of Kenya. A purposive randomized convenience sample of 246 households was selected and landowner interviews conducted guided by a questionnaire, followed by field surveys and observations. Although solar energy contributed less than a quarter of total household energy needs, residents specifically associated it with specific developmental initiatives. Correlation and logistic regression model analyses showed that solar power development was closely associated (and thus can be predicted) from five main independent variables. The findings of the study allowed the development of a probabilistic model general enough to be applicable elsewhere in the development of alternative energy resources particularly those based on solar input.
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Keywords: SPV; solar panel; RET; predictive factors; logistic regression; solar development

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