This dissertation focuses on daily volt/var control in distribution networks with feeder capacitors,
substation capacitors and transformers equipped with on-load tap changers. A hybrid
approach is proposed to solve the daily volt/var control problem. To reduce the computational
requirements of the problem, this approach combines two methods, namely heuristic
and optimal scheduling for the substation and feeder sub-problems respectively.
The feeder capacitor dispatch schedule is determined based on a heuristic reactive power setpoint
method. At this stage the objective is to minimize the reactive power flow through the
substation bus in every time-interval. And as such, mathematical modeling of the distribution
network components is adapted to suit time-varying conditions. Furthermore, an optimization
model to determine a proper dispatch schedule of the substation devices is formulated.
The objective of this model is to minimize the daily total energy loss and voltage deviations.
Additionally, the reference voltage of the substation secondary bus and the transformer tap
position limits are modified to adapt to given load profiles. The optimization model is solved
with a discrete particle swarm optimization algorithm, which incorporates Newton’s method
to determine the power-flow solution. The proposed method is applied to a time-varying distribution system and evaluated under
different operational scenarios. It is also compared to on-line volt/var control with various
settings. Simulation results show that the proposed approach minimizes both the voltage deviations
and the total energy loss, while on-line control prioritizes one objective over the other depending
on the specified settings. / Dissertation (MEng)--University of Pretoria, 2015. / Electrical, Electronic and Computer Engineering / Unrestricted
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:up/oai:repository.up.ac.za:2263/43905 |
| Date | January 2015 |
| Creators | Mokgonyana, Lesiba |
| Contributors | Xia, Xiaohua, Zhang, Lijun |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Rights | © 2015 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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