Abstract
Traditional power grid is presented with challenges at every section of the grid, from generation
through to transmission and distribution networks. These challenges include aging power system
infrastructure, high-carbon emitting generating plants, demand and supply imbalances in (near)
real time, increasing energy demand and expenditure, and more frequent blackouts and loadshedding.
In this thesis, it is proposed that implementation of distributed energy management
technologies at consumer and utility edges of the smart grid can reduce or at best, eliminate the
challenges facing the present traditional grid. Such technologies when deployed as part of
Demand Side Management (DSM) can contribute to mitigating demand-related challenges of the
grid. These would lead to the transformation of the present uni-directional and centralised grid to
a future multi-directional and decentralised grid through efficient and reliable consumer-driven,
utility-driven, policy-driven and environmental-driven DSM programmes.
Mathematical optimisation techniques are applied in this thesis to formulate the different
DSM problems proposed for Flat Rate Pricing (FRP) and Time-of-Use (TOU) residential
consumers. Linear programming, Mixed Integer Linear Programming (MILP) and convex
programming methods are applied in the problem formulations and solutions. The novel DSM
algorithms proposed in the thesis involve Energy Consumption Scheduling (ECS), Distributed
Energy Storage (DES) and Distributed Energy Generation (DEG) algorithms that are utilityfriendly,
consumer-friendly and environmental-friendly through incentivized time-based tariff
schemes.
Although many DSM algorithms have been presented in the literature, none have applied
DSM techniques to solve the problem of household-level energy-poverty as is attempted in this
thesis, as far as we know. This thesis therefore proposes Daily Maximum Energy Scheduling
(DMES) and Energy Scheduling and Distributed Storage (ESDS) DSM algorithms resulting in
affordable electricity bills for consumers with respect to their income. A Graphic User Interface...
D.Ing.