This thesis introduces a new method especially designed to control the instantaneous power in voltage sourced converters operating under unbalanced conditions, including positive, negative and zero sequence content. A transformation technique, labelled mno transformation, was developed to enable the decomposition of the total instantaneous power flowing on three-phase transmission topologies into constant and oscillating terms. It is applied to three-wire and four-wire schemes, especially accommodating zero sequence unlike previous approaches. Classical and modern electric power theories are presented, particularly focusing on their definitions for adverse AC scenarios. The main mathematical transformations conceived to analyze such situations are summarized, showing their respective advantages and disadvantages. An enhanced instantaneous power theory is introduced. The novel proposed power equations, named mno instantaneous power components, expands the application of the p-q theory, which is attached to the αβ0 transformation. The mno instantaneous power theory is applied to develop an innovative power control method for grid connected voltage sourced converters in order to minimize power oscillations during adverse AC scenarios, particularly with zero sequence content. The method permits to sustain constant instantaneous three-phase power during unbalanced conditions by controlling independently the constant and the oscillating terms related to the instantaneous power. The effectiveness of the proposed control approach and the proposed power conditioning scheme was demonstrated using electromagnetic transient simulation of a VSC connected to an AC system. / May 2017

Indiana University-Purdue University Indianapolis (IUPUI) / In a wide-area power system, detecting dynamic events is critical to maintaining system stability. Large events, such as the loss of a generator or fault on a transmission line, can compromise the stability of the system by causing the generator rotor angles to diverge and lose synchronism with the rest of the system. If these events can be detected as they happen, controls can be applied to the system to prevent it from losing synchronous stability. In order to detect these events, pattern recognition tools can be applied to system measurements. In this thesis, the pattern recognition tool decision trees (DTs) were used for event detection. A single DT produced rules distinguishing between and the event and no event cases by learning on a training set of simulations of a power system model. The rules were then applied to test cases to determine the accuracy of the event detection. To use a DT to detect events, the variables used to produce the rules must be chosen. These variables can be direct system measurements, such as the phase angle of bus voltages, or indices created by a combination of system measurements. One index used in this thesis was the integral square bus angle (ISBA) index, which provided a measure of the overall activity of the bus angles in the system. Other indices used were the variance and rate of change of the ISBA. Fitting a polynomial curve to a sliding window of these indices and then taking the difference between the polynomial and the actual index was found to produce a new index that was non-zero during the event and zero all other times for most simulations. After the index to detect events was chosen to be the error between the curve and the ISBA indices, a set of power system cases were created to be used as the training data set for the DT. All of these cases contained one event, either a small or large power injection at a load bus in the system model. The DT was then trained to detect the large power injection but not the small one. This was done so that the rules produced would detect large events on the system that could potentially cause the system to lose synchronous stability but ignore small events that have no effect on the overall system. This DT was then combined with a second DT that predicted instability such that the second DT made the decision whether or not to apply controls only for a short time after the end of every event, when controls would be most effective in stabilizing the system.