This thesis presents and investigates Space Vector Modulation (SVM) switching strategies for (i) a multi-level Diode-Clamped Converter (DCC) and (ii) a multi-module Voltage-Sourced Converter (VSC) system in which each module is a conventional two-level VSC. Although the SVM strategies are general and applicable for n-level DCC and n-module VSC systems, this text only concentrates on five-level DCC and four-module VSC systems.
For a five-level DCC, a computationally efficient SVM algorithm is proposed. The algorithm, that is based on a classifier Neural Network (NN), reduces the computational time for the SVM realization. Therefore, adequate saving of processor execution time, in each sampling period of SVM, is provided to carry out other functions, e.g. the calculations required for DC-capacitor voltage balancing task. The thesis also proposes a DC-capacitor voltage
balancing strategy to counteract the voltage drift phenomenon of (i) a passive-front-end five-level DCC, and (ii) a back-to-back
connected five-level DCC system. The proposed balancing strategy, that is based on augmenting the proposed SVM algorithm, takes advantage of the redundant switching states to minimize a quadratic cost function associated with voltage deviations of the
DC-capacitors. The salient features of the proposed balancing strategy are (i) online calculation of SVM to select the best
switching states, (ii) minimization of switching frequency, (iii) minimization of the THD content of the AC-side voltage, and (iv) no requirement for additional power circuitry.
For a four-module VSC system a sequential sampling SVM strategy is proposed. The proposed strategy (i) provides harmonic cancellation/minimization at the net AC-side voltage of the multi-module VSC system, and (ii) offers a low switching frequency
for each VSC module.
Technical feasibility of the proposed SVM strategies for a five-level DCC and a four-module VSC system, as a STATCOM and a
back-to-back HVDC system, are investigated and presented. The studies are conducted in the time-domain, in the PSCAD/EMTDC
software environment.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/17261 |
| Date | 26 February 2009 |
| Creators | Saeedifard, Maryam |
| Contributors | Iravani, Mohammad Reza |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
| Format | 9752748 bytes, application/pdf |
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