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

In this work we consider the overhead power transmission lines (OHL). Their specifics are related to the presence of cables (conductors) whose length between supporting towers may extend to dozens of thousand meters. The OHL components are exposed to a combination of natural actions wind, rain, ice / snow / frost deposits. Compared to other structural parts, conductors have the highest flexibility and very low structural self-damping (of the order of 0.1 % of critical damping or lower, depending on frequencies). They are among structural elements the most sensitive to these actions. Since early fifties the increased energy demand gave a rise to large construction of high-voltage and extra-high-voltage overhead lines equipped with bundled electrical conductors. For such arrangements there was noticed a kind of wind-induced oscillations originated by a zone of disturbed and retarded air flow (wake), that the cables located upwind(windward) cast onto the downwind (leeward) ones. The effect of this phenomenon called Wake-Induced Oscillations (WIO) resulted in fatigue damages of conductors, failures of insulator strings and cable suspension hardware and fatigue failures of spacers. There have been identified analogues to transmission lines WIO in other regular structures subjectto the cross-flow of viscous fluids (air, gas, water etc.): heat exchanger tubes, clusters of fuel rods of nnuclear reactors, groups of chimneys, buildings. Early works in this field relate to the aerodynamics of tandem and staggered twin struts to support the wings of biplanes and published by Pannell, Griffits and Coales in 1915. Other cable structures like suspenders in suspension bridges or stays in cable-stayed bridges may be also subject to wake-induced oscillations. In each of these cases, conditions of oscillations occurrence and structural response depend on cables specific mass and stiffness, kind of fixation, dimension scale versus fluid viscosity and velocity (Reynolds number) etc. The cables separation plays important role, as there are different kinds of wake interference especially when the cables are closely spaced. A number of research projects were entertained to study the wake-induced oscillations of different structures, which brought to development of analytical and experimental models and methods of protection against this phenomenon. A particular solution to overhead lines was found by unevenly distributing the spacers along the line span. To achieve that, no unique approach exists; virtually each grid company, or manufacturer of spacers proceeds with its own method. It may rely on different basis, either field experience or analytical study or a mixture of them. And, despite advances in numerical modelling of latest decades, few publications uncover phenomenological side of WIO. The issues of modelling WIO in a view of helping to develop methods for protection of line against WIO are a main subject of this work. Original advances studied in this thesis include: - Current state-of-the art for analytical calculation of WIO, including the loads in the wake - Overview of classic theory of wake-induced flutter and its evaluation from the standpoint of modern numerical tools for analytical applications (e.g., Matlab) - Nonlinear Finite-Element Modelling of WIO using classic theory of wake-induced flutter, study of its domains of application, advantages and limitations, including validation upon field experiments - Foundation of basic methodology for optimal placement of spacers over the bundle conductor span

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All-electric ship power systems have limited generation capacity and finite rotating inertia compared with large power systems. Moreover, all-electric ship power systems include large portions of nonlinear loads and dynamic loads relative to the total power capacity, which may significantly reduce the stability margin. Pulse loads and other high-energy weapon loads in the system draw a large amount of power intermittently, which may cause significant frequency and voltage oscillations in the system. Thus, an effective real-time load management technique is needed to dynamically balance the load and generation to operate the system normally. Multi-agent systems, inspired by biological phenomena, aim to cooperatively achieve system objectives that are difficult to reach by a single agent or centralized controller. Since power systems include various electrical components with different dynamical systems, conventional homogeneous multi-agent system cooperative controllers have difficulties solving the real-time load management problem with heterogeneous agents. In this dissertation, a novel heterogeneous multi-agent system cooperative control methodology is presented based on artificial potential functions and reduced-order agent models to cooperatively achieve real-time load management for all-electric ship power systems. The technique integrates high-order system dynamics and various kinds of operational constraints into the multi-agent system, which improves the accuracy of the cooperative controller. The multi-agent system includes a MVAC multiagent system and a DC zone multi-agent, which are coordinated by an AC-DC communication agent. The developed multi-agent system framework and the notional all-electric ship power system model were simulated in PSCAD software. Case studies and performance analysis of the MVAC multi-agent system and the DC zone multi-agent system were performed. The simulation results indicated that propulsion loads and pulse loads can be successfully coordinated to reduce the impact of pulse loads on the power quality of all-electric ship power systems. Further, the switch status or power set-point of loads in DC zones can be optimally determined to dynamically balance the generation and load while satisfying the operational constraints of the system and considering load priorities. The method has great potential to be extended to other isolated power systems, such as microgrids.

Classical view of power system is characterized by a unidirectional power flow from centralized generation to consumers. Power system deregulation gave impetus to a modern view by introducing distributed generations (DGs) into distribution systems, leading to a bi-directional power flow. Several benefits of embedding DGs into distribution systems, such as increased reliability and reduced system losses, can be achieved. However, when a zone of the distribution system remains energized after being disconnected from the grid, DGs become islanded and early detection is needed to avoid several operational issues. In response to this call, a wavelet-based approach that uses the mean voltage index is proposed in this work to detect islanding operation in distribution systems embedding DGs. The proposed approach has been tested in several islanding and non-islanding scenarios using IEEE 13-bus distribution system. The results have shown the effectiveness of the proposed approach compared to other islanding approaches previously published in the literature. / UOIT

There has been significant development in the area of neural network based power system protection in the previous decade. Neural network technology has been applied for various protective relaying functions including distance protection. The reliability and efficiency of ANN based distance relays is improving with the developing digital technologies. There are, however, some inherent deficiencies that still exist in the way these relays are designed. This research addresses some of these issues and proposes an improved protective relaying scheme.<p> The traditional ANN distance relay designs use parameter estimation algorithms to determine the phasors of currents and voltages. These phasors are used as inputs to determine the distance of a fault from relay location. The relays are trained and tested on this criterion; however, no specific relay characteristic has been defined. There is a need for development of a new methodology that will enable designing of an ANN that works as a generic distance relay with clearly defined operating boundary.<p> This research work presents a modified distance relaying algorithm that has been combined with a neural network approach to eliminate the use of phasors. The neural network is trained to recognize faults on basis of a specific relay characteristic. The algorithm is flexible and has been extended for the design of other relays. The neural network has been trained using pure sinusoidal values and has been tested on a 17-bus power system simulated in PSCAD. The training and testing of the neural network on different systems ensures that the relay is generic in nature. The proposed relay can be used on any transmission line without re-training the neural network.<p> The design has been tested for different fault conditions including different fault resistances and fault inception angles. The test results show that the relay is able to detect faults in lesser time as compared to conventional relay algorithms while maintaining the integrity of relay boundaries.

This dissertation presents dynamic reactive power control of isolated power systems. Isolated systems include MicroGrids in islanded mode, shipboard power systems operating offshore, or any other power system operating in islanded mode intentionally or due to a fault. Isolated power systems experience fast transients due to lack of an infinite bus capable of dictating the voltage and frequency reference. This dissertation only focuses on reactive control of islanded MicroGrids and AC/DC shipboard power systems. The problem is tackled using a Model Predictive Control (MPC) method, which uses a simplified model of the system to predict the voltage behavior of the system in future. The MPC method minimizes the voltage deviation of the predicted bus voltage; therefore, it is inherently robust and stable. In other words, this method can easily predict the behavior of the system and take necessary control actions to avoid instability. Further, this method is capable of reaching a smooth voltage profile and rejecting possible disturbances in the system. The studied MicroGrids in this dissertation integrate intermittent distributed energy resources such as wind and solar generators. These non-dispatchable sources add to the uncertainty of the system and make voltage and reactive control more challenging. The model predictive controller uses the capability of these sources and coordinates them dynamically to achieve the voltage goals of the controller. The MPC controller is implemented online in a closed control loop, which means it is self-correcting with the feedback it receives from the system.

This dissertation investigates the distribution and transmission systems reliability and economic impact of energy storage and renewable energy integration. The reliability and economy evaluation framework is presented. Novel operation strategies of energy storage and renewable energy are proposed. The method for optimizing the energy storage sizing and operation strategy in order to achieve optimal reliability and economy level is developed. The objectives of the movement towards the smart grid include making the power systems more reliable and economically efficient. The rapid development of the large scale energy storage technology makes it an excellent candidate in achieving these goals. A novel Model Predictive Control (MPC)-based operation strategy is proposed to optimally manage the charging and discharging operation of energy storage in order to minimize the energy purchasing cost for a distribution system load aggregator in power markets. Different operation strategies of energy storage have different reliability and economic impact on power systems. Simulation results illustrate the importance of the energy storage operation strategies. A hybrid operation strategy which combines the MPC-based operation strategy and the standby backup operation strategy is proposed to flexibly adjust the reliability and economic improvement brought by energy storage. A particle swarm optimization approach is developed to determine the optimal energy storage sizing and operation strategy while maximizing reliability and economic improvement. A reliability and economy assessment framework based on sequential Monte Carlo method integrated with the operation strategies is proposed. The impact on the transmission systems reliability brought by energy storage and renewable energy with the proposed operation strategies is investigated. Case studies are conducted to demonstrate the effectiveness of the proposed operation strategies, optimization approach, and the reliability and economy evaluation framework. Insights into how energy storage and renewable energy affect power system reliability and economy are obtained.

Modern power networks are being driven ever closer to both their physical and operational limits. As a result, control systems are being increasingly relied on to assure satisfactory system performance. Power system stabilizers (PSSs) are one example of such controllers. Their purpose is to increase system damping and they are typically designed using a model of the network that is valid during nominal operating conditions. The limitation of this design approach is that during off-nominal operating conditions, such as those triggered by daily load fluctuations, performance of the controller can degrade. The research presented in this report attempts to evaluate the possibility of employing an adaptive PSS as a means of avoiding the performance degradation precipitated by off-nominal operation. Conceptually, an adaptive PSS would be capable of identifying changes in the network and then adjusting its parameters to ensure suitable damping of the identified network. This work begins with a detailed look at the identification algorithm employed followed by a similarly detailed examination of the control algorithm that was used. The results of these two investigations are then combined to allow for a preliminary assessment of the performance that could be expected from an adaptive PSS. The results of this research suggest that an adaptive PSS is a possibility but further work is needed to confirm this finding. Testing using more complex network models must be carried out, details pertaining to control parameter tuning must be resolved and closed-loop time domain simulations using the adaptive PSS design remain to be performed. / May 2007

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