In the recent years there has been a great deal of attention on the optimal demand and supply side
strategy. The increase in renewable energy sources and the expansion in demand response programmes
has shown the need for a robust power system. These changes in power system require the control of
the uncertain generation and load at the same time. Therefore, it is important to provide an optimal
scheduling strategy that can meet an adequate energy mix under demand response without affecting
the system reliability and economic performance. This thesis addresses the following four aspects to
these changes.
First, a renewable obligation model is proposed to maintain an adequate energy mix in the economic
dispatch model while minimising the operational costs of the allocated spinning reserves. This method
considers a minimum renewable penetration that must be achieved daily in the energy mix. If the
renewable quota is not achieved, the generation companies are penalised by the system operator. The
uncertainty of renewable energy sources are modelled using the probability density functions and
these functions are used for scheduling output power from these generators. The overall problem is
formulated as a security constrained economic dispatch problem.
Second, a combined economic and demand response optimisation model under a renewable obligation
is presented. Real data from a large-scale demand response programme are used in the model. The
model finds an optimal power dispatch strategy which takes advantage of demand response to minimise
generation cost and maximise renewable penetration. The optimisation model is applied to a South
African large-scale demand response programme in which the system operator can directly control
the participation of the electrical water heaters at a substation level. Actual load profile before and
after demand reduction are used to assist the system operator in making optimal decisions on whether
a substation should participate in the demand response programme. The application of these real
demand response data avoids traditional approaches which assume arbitrary controllability of flexible
loads.
Third, a stochastic multi-objective economic dispatch model is presented under a renewable obligation.
This approach minimises the total operating costs of generators and spinning reserves under renewable
obligation while maximising renewable penetration. The intermittency nature of the renewable energy
sources is modelled using dynamic scenarios and the proposed model shows the effectiveness of the
renewable obligation policy framework. Due to the computational complexity of all possible scenarios,
a scenario reduction method is applied to reduce the number of scenarios and solve the model. A Pareto
optimal solution is presented for a renewable obligation and further decision making is conducted to
assess the trade-offs associated with the Pareto front.
Four, a combined risk constrained stochastic economic dispatch and demand response model is presented
under renewable obligation. An incentive based optimal power dispatch strategy is implemented
to minimise generation costs and maximise renewable penetration. In addition, a risk-constrained
approach is used to control the financial risks of the generation company under demand response
programme. The coordination strategy for the generation companies to dispatch power using thermal
generators and renewable energy sources while maintaining an adequate spinning reserve is presented.
The proposed model is robust and can achieve significant demand reduction while increasing renewable
penetration and decreasing the financial risks for generation companies. / Thesis (PhD (Electrical Engineering))--University of Pretoria, 2020. / Electrical, Electronic and Computer Engineering / PhD (Electrical Engineering) / Unrestricted
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:up/oai:repository.up.ac.za:2263/84811 |
| Date | January 2020 |
| Creators | Hlalele, Thabo Gregory |
| Contributors | Naidoo, Robin, greg.hlalele@gmail.com, Bansal, Ramesh C., Zhang, Jiangfeng |
| Publisher | University of Pretoria |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Rights | © 2021 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
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