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Modelling of artificial intelligence based demand side management techniques for mitigating energy poverty in smart grids.

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This research work proposes an artificial intelligence (AI) based model for smart grid initiatives (for South Africa and by extension sub-Saharan Africa, (SSA)) and further incorporates energy justice principles. Spanning the social, technical, economic, environmental, policy and overall impact of smart and just electricity grids, this research begins by investigating declining electricity consumption and demand side management (DSM) potential across South Africa. In addition, technical frameworks such as the combined energy management system (CEMS), co-ordinated centralized energy management system (ConCEMS) and biased load manager home energy management system (BLM-HEMS) are modelled. These systems provide for the integration of all aspects of the electricity grid and their optimization in achieving cost reduction for both the utility and consumers as well as improvement in the consumers quality of life (QoL) and reduction of emissions. Policy and economy-wise, this research work further proposes and models an integrated electrification and expansion model (IEEM) for South Africa, and also addresses the issue of rural marginalization due to poor electricity access for off-grid communities. This is done by proposing a hybrid generation scheme (HGS) which is shown to satisfy sufficiently the requirements of the energy justice framework while significantly reducing the energy burden of households and reducing carbon emissions by over 70%.


Doctoral degree. University of KwaZulu-Natal, Durban.