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No description available.

This thesis describes the development of a new directional relay for the ultra-high-speed protection of EHV transmission lines. The work has been carried out by utilising digital computer simulations, and the relay has been developed assuming that it would be implemented by micro-computer. This has enabled the use of a new digital filtering structure, which has been specifically devised to extract the superimposed quantities that the directional principle is concerned with. A modal transformation is utilised within the relay in order to define decoupled wave signals for a multi-conductor system, the transformation is also shown to provide significant hardware economies in the final design. In order to study the characteristics of the new relay, a number of new primary system digital simulations have been devised and are described in the thesis. These simulations include single and double-circuit multi-terminal systems with advanced fault capabilities. The novel decision process, in combination with the digital filter, enables the relay to provide a secure directional decision within typically, 2.5 ms of a fault occurring. Such an operating time will enable ultra-high-speed clearance of faults to be achieved, if the most recent circuit breaker developments and wide-band communication equipment are also employed.

Interconnected Systems

After the deregulation of the power industry, power systems are required to be operated efficiently and economically in today’s strongly competitive environment. In order to achieve these objectives, it is crucial for power system control centers to accurately monitor the system operating state. State estimation is an essential tool in an energy management system (EMS). It is responsible for providing an accurate and correct estimate for the system operating state based on the available measurements in the power system. A robust state estimation should have the capability of keeping the system observable during different contingencies, as well as detecting and identifying the gross errors in measurement set and network topology. However, this capability relies directly on the system network configuration and measurement locations. In other words, a reliable and redundant measurement system is the primary condition for a robust state estimation. This dissertation is focused on the possible benefits to state estimation of using synchronized phasor measurements to improve the measurement system. The benefits are investigated with respect to the measurement redundancy, bad data and topology error processing functions in state estimation. This dissertation studies how to utilize the phasor measurements in the traditional state estimation. The optimal placement of measurement to realize the maximum benefit is also considered and practical algorithms are designed. It is shown that strategic placement of a few phasor measurement units (PMU) in the system can significantly increase measurement redundancy, which in turn can improve the capability of state estimation to detect and identify bad data, even during loss of measurements. Meanwhile, strategic placement of traditional and phasor measurements can also improve the state estimation’s topology error detection and identification capability, as well as its robustness against branch outages. The proposed procedures and algorithms are illustrated and demonstrated with different sizes of test systems. And numerical simulations verify the gained benefits of state estimation in bad data processing and topology error processing.

The electric power utility industry is presently undergoing a change towards the deregulated environment. This has resulted in unbundling of generation, transmission and distribution services. The introduction of competition into unbundled electricity services may lead system operation closer to its security boundaries resulting in smaller operating safety margins. The competitive environment is expected to lead to lower price rates for customers and higher efficiency for power suppliers in the long run. Under this deregulated environment, security assessment and pricing of transmission services have become important issues in power systems. This dissertation provides new methods for power system security assessment and transmission pricing. In power system security assessment, the following issues are discussed 1) The description of probabilistic methods for power system security assessment 2) The computation time of simulation methods 3) on-line security assessment for operation. A probabilistic method using Monte-Carlo simulation is proposed for power system security assessment. This method takes into account dynamic and static effects corresponding to contingencies. Two different Kohonen networks, Self-Organizing Maps and Learning Vector Quantization, are employed to speed up the probabilistic method. The combination of Kohonen networks and Monte-Carlo simulation can reduce computation time in comparison with straight Monte-Carlo simulation. A technique for security assessment employing Bayes classifier is also proposed. This method can be useful for system operators to make security decisions during on-line power system operation. This dissertation also suggests an approach for allocating transmission transaction costs based on reliability benefits in transmission services. The proposed method shows the transmission transaction cost of reliability benefits when transmission line capacities are considered. The ratio between allocation by transmission line capacity-use and allocation by reliability benefits is computed using the probability of system failure.

This thesis presents a novel technique for prediction of the transient stability status of a power system following a large disturbance such as a fault, and application of the tech-nique for subsequent emergency control. The prediction is made based on the synchro-nously measured samples of the magnitudes of fundamental frequency voltage phasors at major generation/load centers. The voltage samples are taken immediately after a fault is cleared and used as inputs to a binary classifier based on support vector machines to iden-tify the transient stability condition. The classifier is trained using examples of the post-fault recovery voltages (inputs) obtained through simulations and the corresponding sta-bility status (output) determined using a power angle-based stability index. Studies with the New England 39-bus test system indicate that the proposed algorithm can correctly recognize when the power system is approaching transient instability. The proposed sys-tem is then applied to Venezuelan power system and Manitoba Hydro power grid to demonstrate the applicability for large practical power systems. Performance of the pro-posed transient stability prediction scheme under the presence of asymmetrical faults, voltage sensitive loads, unlearned network topologies and measurement noise was found to be satisfactory. Once an impending transient instability situation has been detected, appropriate emer-gency control strategies are triggered to minimize the impact of this on the safe operation of the network and reduce the possibility of a blackout. This thesis examines two differ-ent emergency control schemes: a) A fuzzy logic based emergency load and generator shedding scheme and b) A high voltage direct current (HVdc) power order reduction scheme based on synchronized phasors measurements. These strategies were developed for two power systems with contrasting characteristics: one for the Venezuelan power system which is a conventional power system completely based on alternating current (AC) transmission, and the other for the Manitoba Hydro network which heavily depend on long HVdc transmission for power transfer. The proposed wide area control systems demonstrated good performance on the Venezuelan and Manitoba Hydro power grids.

This thesis presents a novel technique for prediction of the transient stability status of a power system following a large disturbance such as a fault, and application of the tech-nique for subsequent emergency control. The prediction is made based on the synchro-nously measured samples of the magnitudes of fundamental frequency voltage phasors at major generation/load centers. The voltage samples are taken immediately after a fault is cleared and used as inputs to a binary classifier based on support vector machines to iden-tify the transient stability condition. The classifier is trained using examples of the post-fault recovery voltages (inputs) obtained through simulations and the corresponding sta-bility status (output) determined using a power angle-based stability index. Studies with the New England 39-bus test system indicate that the proposed algorithm can correctly recognize when the power system is approaching transient instability. The proposed sys-tem is then applied to Venezuelan power system and Manitoba Hydro power grid to demonstrate the applicability for large practical power systems. Performance of the pro-posed transient stability prediction scheme under the presence of asymmetrical faults, voltage sensitive loads, unlearned network topologies and measurement noise was found to be satisfactory. Once an impending transient instability situation has been detected, appropriate emer-gency control strategies are triggered to minimize the impact of this on the safe operation of the network and reduce the possibility of a blackout. This thesis examines two differ-ent emergency control schemes: a) A fuzzy logic based emergency load and generator shedding scheme and b) A high voltage direct current (HVdc) power order reduction scheme based on synchronized phasors measurements. These strategies were developed for two power systems with contrasting characteristics: one for the Venezuelan power system which is a conventional power system completely based on alternating current (AC) transmission, and the other for the Manitoba Hydro network which heavily depend on long HVdc transmission for power transfer. The proposed wide area control systems demonstrated good performance on the Venezuelan and Manitoba Hydro power grids.