Many settlements in Sub Saharan Africa (SSA) lack access to electricity which is a necessary resource for development. Given the geography and population patterns in the region, extending national grids is economically unviable for many of the un-electrified settlements. Meanwhile the region is endowed with renewable resources which can be exploited in off-grid mode for electricity generation. This thesis examines the importance of off-grid technologies for onward electrification in the SSA region. The exercise inspires an electricity planning problem that can be analytically specified but is computationally intensive and impractical for real sized problems. Heuristic methods must therefore be used. We develop two new heuristic solution methods which draw on standard algorithms i.e. lexicographic algorithm and genetic algorithm to solve the problem. The new solution methods together with two existing heuristic algorithms in the literature are applied to a case study of Ghana. We find that the electrification schemes yielded by all four solution methods/algorithms suggest off-grid technologies, especially solar, are important for onward electrification in SSA. Locations that were assigned off-grid technologies in the algorithms mentioned above are typically rural where livelihoods are based on small scale farming. Currently, adoption of renewable resource technologies is low in these locations. We therefore develop a dynamic stochastic farm household model to examine the extent to which market failures impact self-funded investment in solar panels by farmers in rural SSA. We find that credit restrictions and risk affect solar panel investment to varying degrees. Using simulations of the policy functions, we find that the expected investment cycle for a credit constrained household in a stochastic farm income environment is 30 years if investment in solar panels is irreversible. In a reversible investment scenario, the expected investment cycle is 5 years only. Reversibility is therefore a major determinant of solar panel adoption among poor farmers.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:646102 |
| Date | January 2014 |
| Creators | Abdul-Salam, Yakubu |
| Publisher | University of Aberdeen |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=225751 |
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