With the increased attention on high efficiency and controllability of industrial processes, as well as reduced weight, volume and cost of consumer products, the applications of nonlinear power electronic converters such as adjustable speed drives (ASDs) are showing a rapid rise. Power Quality (PQ) is becoming an increasing concern with the growth of both sensitive and disturbing nonlinear loads in the residential, commercial and industrial levels of the power system, where PQ related disruptions can cause system malfunction, product loss, and hardware damage resulting in costly data loss and downtime. Investigating and mitigating PQ issues pertaining to the input supply of ASDs and other sensitive power electronic equipment is extremely important in maintaining a high level of productivity. In response to these concerns, this research focuses on the development of a power quality test platform (PQTP) that has been implemented at Oregon State University (OSU), in the Motor Systems Resource Facility (MSRF). The central component of the PQTP is a 120kVA programmable ac power source with an integrated arbitrary waveform generator (AWG) which creates realistic voltage disturbance conditions that can be used to characterize ride-through capabilities of industrial processes in a controlled environment. Also presented is a command driver database that has been created and tested, using Lab VIEW, which contains the functionality necessary to conduct a wide range of power quality research and testing projects by remotely configuring and controlling the AWG. The power quality research and testing capabilities of the PQTP are demonstrated with ASD diode-bridge rectifier operation analysis and ride-through characterization. This research shows the transition of an ASD's three-phase diode rectifier into single-phase diode rectifier operation when relatively small single-phase voltage sags are applied to the input. Also shown are ride-through characterizations of varying sizes and configurations of ASDs when subjected to single, two, and three-phase voltage sags as well as capacitor switching transients. In addition, ASD topologies providing improved ride-through capabilities are determined. / Graduation date: 2002

Extensive studies have been undertaken on the transient stability of large interconnected power systems with flexible ac transmission systems (FACTS) devices installed. Varieties of control methodologies have been proposed to stabilize the postfault system which would otherwise eventually lose stability without a proper control. Generally speaking, regular transient stability is well understood, but the mechanism of load-driven voltage instability or voltage collapse has not been well understood. The interaction of generator dynamics and load dynamics makes synthesis of stabilizing controllers even more challenging. There is currently increasing interest in the research of neural networks as identifiers and controllers for dealing with dynamic time-varying nonlinear systems. This study focuses on the development of novel artificial neural network architectures for identification and control with application to dynamic electric power systems so that the stability of the interconnected power systems, following large disturbances, and/or with the inclusion of uncertain loads, can be largely enhanced, and stable operations are guaranteed. The latitudinal neural network architecture is proposed for the purpose of system identification. It may be used for identification of nonlinear static/dynamic loads, which can be further used for static/dynamic voltage stability analysis. The properties associated with this architecture are investigated. A neural network methodology is proposed for dealing with load modeling and voltage stability analysis. Based on the neural network models of loads, voltage stability analysis evolves, and modal analysis is performed. Simulation results are also provided. The transient stability problem is studied with consideration of load effects. The hierarchical neural control scheme is developed. Trajectory-following policy is used so that the hierarchical neural controller performs as almost well for non-nominal cases as they do for the nominal cases. The adaptive hierarchical neural control scheme is also proposed to deal with the time-varying nature of loads. Further, adaptive neural control, which is based on the on-line updating of the weights and biases of the neural networks, is studied. Simulations provided on the faulted power systems with unknown loads suggest that the proposed adaptive hierarchical neural control schemes should be useful for practical power applications. / Graduation date: 1999

The full capacity of the existing transmission lines is often underutilized due to the system stability requirements. Controllable network devices represent the effective means of improving the system stability, and their deployment allows better use of the existing transmission facilities and can help to avoid construction of new lines. This dissertation addresses system analysis and modeling of controllable network devices. Transient angle stability is one of the major requirements limiting transfer capability of the power transmission systems. The theoretical concepts of transient angle controllability using controllable network devices are considered in this dissertation. The main results are derived for a general transmission network structure and applied to series and shunt compensators as well as braking resistors. The proposed approach allows to quantify controllability and to relate it to the control device size, type and location in the transmission network. Transient stability controllers are needed to maximize the device effect on the transient angle stability enhancement. The transient stability controller functional structure is discussed and the design requirements for each component are specified. The examples of controller designs are presented. Emerging technologies such as Thyristor-Controlled Series Compensators and Synchronous Voltage Sources offer superior control capabilities and performance characteristics as compared to conventional compensators. Unlike conventional compensators, the new controllable network devices are very complex dynamical systems and require more comprehensive modeling for time-domain studies and controller designs. Detailed models of a Thyristor-Controlled Series Compensator and a Synchronous Voltage Source for powerflow, transient stability, and electro-magnetic transient studies are presented. Finally, a detailed planning study for increasing transfer capability of the Montana transmission system using controlled series compensation is presented. A variety of design and performance requirements is considered in this study, which makes it a useful reference for similar planning projects. / Graduation date: 1996

Sherman M. Chan, Michael Athans. / Bibliography: leaf 9. / Caption title. "August 15, 1981." / Supported by the U.S. Department of Energy, Division of Electric Energy Systems, under Contract DE-AC01-78RA03395

Dissertation (PhD)--University of Stellenbosch, 1995. / Bibliography. Also available via the Internet.

Thesis (B.Eng.)--Memorial University of Newfoundland, 2005. / Bibliography: leaves 127-133.

Maintenance optimisation is essential to achieve cost-efficiency, availability and reliability of supply in electric power systems. The process of maintenance optimisation requires information about the costs of preventive and corrective maintenance, as well as the costs of failures borne by both electricity suppliers and customers. To calculate expected costs, information is needed about equipment reliability characteristics and the way in which maintenance affects equipment reliability. The aim of this Ph.D. work has been to develop equipment reliability models taking the effect of maintenance into account. The research has focussed on the interrelated areas of condition estimation, reliability modelling and maintenance modelling, which have been investigated in a number of case studies. In the area of condition estimation two methods to quantitatively estimate the condition of disconnector contacts have been developed, which utilise results from infrared thermography inspections and contact resistance measurements. The accuracy of these methods were investigated in two case studies. Reliability models have been developed and implemented for SF6 circuit-breakers, disconnector contacts and XLPE cables in three separate case studies. These models were formulated using both empirical and physical modelling approaches. To improve confidence in such models a Bayesian statistical method incorporating information from the equipment design process was also developed. This method was illustrated in a case study of SF6 circuit-breaker operating rods. Methods for quantifying the effect of maintenance on equipment condition and reliability have been investigated in case studies on disconnector contacts and SF6 circuit-breakers. The input required by these methods are condition measurements and historical failure and maintenance data, respectively. This research has demonstrated that the effect of maintenance on power system equipment may be quantified using available data. However, realising the full potential of these methods requires the gathering and utilisation of failure and maintenance data as well as condition measurements to be improved. / QC 20100823

University of Macau / Faculty of Science and Technology / Department of Electrical and Computer Engineering

University of Macau / Faculty of Science and Technology / Department of Electromechanical Engineering

University of Macau / Faculty of Science and Technology / Department of Electromechanical Engineering