Multi-pulse transformer/rectifier systems are becoming increasingly popular in power distribution systems. These topologies can be found in aircraft power systems, motor drives, and other applications that require low total harmonic distortion (THD) of the input line current. This increase in the use of multi-pulse transformer topologies has led to the need to study large systems composed of said units and their interactions within the system. There is also an interest in developing small-signal models so that stability issues can be studied. This thesis presents a procedure for the average model of multi-pulse transformer/rectifier topologies. The dq rotating reference frame was used to develop the average model and parameter estimation is incorporated through the use of polynomial fits. The average model is composed of nonlinear dependent sources and linear passive components. A direct benefit from this approach is a reduction in simulation time by two orders of magnitude. The average model concept demonstrates that it accurately predicts the dynamics of the system being studied. In particular, two specific topologies are studied, the 12-pulse hexagon transformer/rectifier (hex t/r) and the 18-pulse autotransformer rectifier unit (ATRU). In both cases, detailed switching model results are used to verify the operation of the average model. In the case of the hex t/r, the average model is further validated with experimental data from an 11 kVA prototype. The hex t/r output impedance, obtained from the linearized average model, has also been verified experimentally. / Master of Science

This work focuses on the safe and stable operation of an autonomous power system interconnecting an AC source with various types of power electronic loads. The stability of these systems is a challenge due to the inherent nonlinearity of the circuits involved. Traditionally, the stability analysis in this type of power systems has been approached by means of small-signal methodology derived from the Nyquist stability criterion. The small-signal analysis combined with physical insight and the adoption of safety margins is sufficient, in many cases, to achieve a stable operation with an acceptable system performance. Nonetheless, in many cases, the margins adopted result in conservative measures and consequent system over designs. This work studies the system stability under large-perturbations by means of three different tools, namely parameter space mapping, energy functions, and time domain simulations. The developed parameters space mapping determines the region of the state and parameter space where the system operation is locally stable. In this way stability margins in terms of physical parameters can be established. Moreover, the boundaries of the identified stability region represent bifurcations of the system where typical nonlinear behavior appears. The second approach, based on the Lyapunov direct method, attempts to determine the region of attraction of an equilibrium point, defined by an operation condition. For this a Lyapunov function based on linear matrix inequalities was constructed and tested on a simplified autonomous system model. In Addition, the third approach simulates the system behavior on a computer using a detailed system model. The higher level of model detail allows identifying unstable behavior difficult to observe when simpler models are used. Because the stability of the autonomous power system is strongly associated with the characteristics of the energy source, an improved voltage controller for the generator is also presented. The generator of an autonomous power system must provide a good performance under a wide variety of regimes. Under these conditions a model based controller is a good solution because it naturally adapts to the changing requirements. To this extent a controller based on the model of a variable frequency synchronous generator has been developed and tested. The results obtained show a considerable improvement performance when compared to previous practices. / Ph. D.