Modelling of artificial intelligence based demand side management techniques for mitigating energy poverty in smart grids.
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Date
2018
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Abstract
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%.
Description
Doctoral degree. University of KwaZulu-Natal, Durban.