Recent events, such as the Northeast Blackout of 2003, have highlighted the need for accurate real-time stability assessment techniques to detect when an electric power system is on the brink of voltage collapse. While many techniques exist, most techniques are computationally demanding and cannot be used in an on-line application. A voltage stability index (VSI) can be designed to estimate the distance of the current operating point to the voltage marginally stable point during the system operation. In this research work, a new VSI was developed that not only can detect the system voltage marginally stable point but also is computationally efficient for on-line applications. Starting with deriving a method to predict three types of maximum transferable power of a single source power system, the new VSI is based on the three calculated load margins. In order to apply the VSI to large power systems, a method has been developed to simplify the large network behind a load bus into a single source and a single transmission line given the synchronized phasor measurements of the power system variables and network parameters. The simplified system model, to which the developed VSI can be applied, preserves the power flow and the voltage of the particular load bus. The proposed voltage stability assessment method, therefore, provides a VSI of each individual load bus and can identify the load bus that is the most vulnerable to voltage collapse. Finally, the new VSI was tested on three power systems. Results from these three test cases provided validation of the applicability and accuracy of the proposed VSI.

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As the scale and complexity of an interconnected power grid has increased significantly, power systems can be operated close to the verge of voltage instability. With the application of Phasor Measurement Units (PMUs), dispatchers are able to monitor long term voltage stability in a real time operational environment. This research addresses the critical issues by proposing three different methods. Voltage Stability Assessment Index (VSAI) is a Thévenin Equivalent (TE) based method considering voltage dynamic mechanisms. To extend the model from one load bus to a critical load center, Optimal Power Flow-Loading limit (OPF-LI) is developed to assess the voltage stability margin. To utilize limited available PMU measurements, State Calculator (SC) is included in the algorithm to approximate the dynamic states at the buses where PMU measurements are not available. The online voltage regulating method in terms of On-load Tap Changer (OLTC) control is also investigated. The methods proposed in this research have been validated with the test cases from the WECC 179 bus system. / M.S. / This thesis proposed a hybrid solution of voltage stability monitoring and control in a power system. For the performance of motors, heaters or other loads in the power system, it is important that the customers are supplied with stable voltage. The variation of the voltage may cause damages to the load. Therefore, the methods in this thesis provides a feasible solution to monitor voltage stability of load centers in a power system. In addition, a novel approach for voltage control is proposed to prevent a voltage collapse of the system. The simulation results illustrate that the approach introduced in this thesis is promising for real time application.

The electric power systems in U.S. Navy ships supply energy to sophisticated systems for weapons, communications, navigation and operation. The reliability and survivability of a Shipboard Power System (SPS) are critical to the mission of a Navy ship, especially under battle conditions. When a weapon hits the ship in the event of battle, it can cause severe damage to the electrical systems on the ship. Researchers in the Power System Automation Laboratory (PSAL) at Texas A&M University have developed methods for performing reconfiguration of SPS before or after a weapon hit to reduce the damage to SPS. Reconfiguration operations change the topology of an SPS. When a system is stressed, these topology changes and induced dynamics of equipment due to reconfiguration might cause voltage instability, such as progressive voltage decreases or voltage oscillations. SPS stability thus should be assessed to ensure the stable operation of a system during reconfiguration. In this dissertation, time frames of SPS dynamics are presented. Stability problems during SPS reconfiguration are classified as long-term stability problems. Since angle stability is strongly maintained in SPS, voltage stability is studied in this dissertation for SPS stability during reconfiguration. A test SPS computer model, whose simulation results were used for stability studies, is presented in this dissertation. The model used a new generalized methodology for modeling and simulating ungrounded stiffly grounded power systems. This dissertation presents two new indices, a static voltage stability index (SVSILji) and a dynamic voltage stability index (DVSI), for assessing the voltage stability in static and dynamic analysis. SVSILji assesses system stability by all lines in SPS. DVSI detects local bifurcations in SPS. SVSILji was found to be a better index in comparison with some indices in the literature for a study on a two-bus power system. Also, results of DVSI were similar to the results of conventional bifurcation analysis software when applied to a small power system. Using SVSILji and DVSI on the test SPS computer model, three of four factors affection voltage stability during SPS reconfiguration were verified. During reconfiguration, SVSILji and DVSI are used together to assess SPS stability.

Voltage stability is the ability of the power system to maintain steady acceptable voltages at all the buses in a system under normal operating conditions and after being subjected to a disturbance. The increased consumption of electricity without the augmentation of the necessary transmission infrastructure has resulted in the overloading of the transmission lines. As a result, the transmission lines operate near the steady state stability limit. The transmission of large amounts of power through the lines results in the large voltage drops in the lines. Sudden disturbances like line or generator outage and fault in the transmission lines may occur because of natural or man made causes. Under the above mentioned conditions, the transmission system may not be able to supply the load demand. This results in drops in the system bus voltages which may be sudden or progressive. If the necessary remedial measures are not taken, then this may lead to blackout or collapse of the whole system. As a result of a number of voltage stability incidents reported from various countries, there is a widespread interest in understanding, characterizing and preventing this phenomena. This thesis is essentially concerned with analyzing the existing methods and the development of new methods for the assessment of voltage stability of power systems. We examine four existing methods for assessing voltage stability with regard to the computational effort involved in their calculation, the useful information we get by using them, their relative effectiveness in assessing the voltage stability and their consistency in predicting the voltage stability of the system. We also study the impact of the system conditions on several of these indices. Further, we propose a set of new indices which provide information similar to the conventional indices but are slightly different. The generalized circle diagram approach proposed earlier to study the variation of the system variables with respect to the independent node parameters is shown to be adoptable for finding the voltage stability limit of a system. It has been shown that the well known continuation power flow method used for voltage stability analysis is identical to the generalized circle diagram approach. A computationally simple approach, based on the Thevenin equivalent of the power system is used to determine the loadability limit of a system. In the continuation power flow method, it is inherently assumed that only one generator responds to the real power load increase of the system. However, an alternate view is presented where all the generators respond to the real power increase in the system and an algorithm is proposed to realize this condition. Using this algorithm, the generation pattern of the system is modified so as to increase the loadability limit of the system considerably. The origin of the voltage instability in power systems can be traced to the load characteristics. Induction motors constitute a significant proportion of the total industrial and residential loads. Two algorithms that are useful to study the voltage stability of systems having induction machines have been presented and validated. These methods are based on the induction machine static equations. The first method is useful in assessing the impact of network disturbances on voltage stability and the second facilitates the computation of the loadability limit. A criterion has been proposed to find the stability limit, stable and unstable operating regions for a system considering various types of induction motor loads on the basis of which, a practical algorithm is proposed and validated to determine the stability of the induction motors driving different types of loads in a large power system. In addition, a method is developed to determine the stability aspects when the constant torque loads and the constant input power loads driven by induction motors operate in a power system, which contains other types of loads like the constant P - Q type of loads. Switching capacitors at the induction motor terminals is one of the ways by which voltage instability occurring due to the induction motor loads can be prevented. A new technique is proposed wherein knowing the capacitance and the slip at the instant of switching, the rotor dynamics following the switching and the existence of a steady state operating point following the switching can be predicted. This approach can be used to choose appropriate capacitances to be switched at the induction motor terminals to prevent its stalling following a sudden load disturbance.

Power systems must face new challenges in the current environment. The energy market liberalization and the increase in the loading level make the occurrence of instability phenomena leading to large blackouts more likely. Existing tools must be improved and new tools must be developed to avoid them. The aim of this thesis is the improvement of the voltage stability assessment efficiency. Two orientations are studied: the monitoring methods and the load modeling. The purpose of the monitoring methods is to evaluate the voltage stability using only measurements and without running simulations. The first approach considered is local. The parameters of the Thevenin equivalent seen from a load bus are assessed thanks to a stream of local voltage and current measurements. Several issues are investigated using measurements coming from complete time-domain simulations. The applicability of this approach is questioned. The second approach is global and uses measurements acquired by a Wide-Area Measurement System (WAMS). An original approach with a certain prediction capability is proposed, along with intuitive visualizations that allow to understand the deterioration process leading to the collapse. The load modeling quality is certainly the weak point of the voltage security assessment tools which run simulations to predict the stability of the power system depending on different evolutions. Appropriate load models with accurate parameters lead to a direct improvement of the prediction precision. An innovative procedure starting from data of long measurement campaigns is proposed to automatically evaluate the parameters of static and dynamic load models. Real measurements taken in the Belgian power system are used to validate this approach.

As modern power systems operate closer to the limits due to load growth and financial imperatives, voltage stability becomes a more important issue and there have been more incidents caused by voltage collapse. For example, there have been 11 outages affecting more than 4000MW between 1984 and 2000 in North America [1]. In power systems, load voltages decrease as the supplied loads increase until the maximum power transfer point is reached. The voltage will collapse if the load is increased above this limit. Therefore, it is important to monitor the loadability of a system to avoid voltage collapse. The loadability of a system can be calculated when the Thevenin impedance is available as the maximum power transfer occurs when the Thevenin impedance and the load impedance are the same in magnitude. This thesis suggests a method to estimate the Thevenin impedance of a system. ABB corporation suggests the Voltage Stability Predictor (VIP) method to estimate the Thevenin impedance, but there are problems with this method and it is not gaining popularity in industry. In this thesis, a method is suggested to estimate the Thevenin impedance by taking advantage of the existance of negative sequence components in the system. The concept of this method has been proved mathematically. Simulations were performed on simple systems and on the modified IEEE 13 bus power flow test case to verify the feasibility of the method and the results are promising. Then, the method was verified with field measurements for a 25kV substation. The voltages and currents were analyzed to estimate the Thevenin equivalent impedance of the power system and the results were compared with the design Thevenin equivalent impedance. The result confirms the viability of the method as the estimated Thevenin impedance matched the design value.

As modern power systems operate closer to the limits due to load growth and financial imperatives, voltage stability becomes a more important issue and there have been more incidents caused by voltage collapse. For example, there have been 11 outages affecting more than 4000MW between 1984 and 2000 in North America [1]. In power systems, load voltages decrease as the supplied loads increase until the maximum power transfer point is reached. The voltage will collapse if the load is increased above this limit. Therefore, it is important to monitor the loadability of a system to avoid voltage collapse. The loadability of a system can be calculated when the Thevenin impedance is available as the maximum power transfer occurs when the Thevenin impedance and the load impedance are the same in magnitude. This thesis suggests a method to estimate the Thevenin impedance of a system. ABB corporation suggests the Voltage Stability Predictor (VIP) method to estimate the Thevenin impedance, but there are problems with this method and it is not gaining popularity in industry. In this thesis, a method is suggested to estimate the Thevenin impedance by taking advantage of the existance of negative sequence components in the system. The concept of this method has been proved mathematically. Simulations were performed on simple systems and on the modified IEEE 13 bus power flow test case to verify the feasibility of the method and the results are promising. Then, the method was verified with field measurements for a 25kV substation. The voltages and currents were analyzed to estimate the Thevenin equivalent impedance of the power system and the results were compared with the design Thevenin equivalent impedance. The result confirms the viability of the method as the estimated Thevenin impedance matched the design value.

ABSTRACT Voltage instability has become a major concern in power systems. Many blackouts have been reported where the main cause is voltage instability. This thesis deals with two specific areas of voltage stability in on-line power system security assessments: small-disturbance (long-term) and large-disturbance (short-term) voltage stability assessment. For each category of voltage stability, both voltage stability analysis and controls are studied. The overall objective is to use the learning capabilities of computational intelligence technology to build up the comprehensive on-line power system security assessment and control strategy as well as to enhance the speed and efficiency of the process with minimal human intervention. The voltage stability problems are quantified by voltage stability indices which measure the system for the closeness of current operating point to voltage instability. The indices are different for small-disturbance and large-disturbance voltage stability assessment. Conventional approaches, such as continuation power flow or time-domain simulation, can be used to obtain voltage stability indices. However, these conventional approaches are limited by computation time that is significant for on-line computation. The Artificial Neural Network (ANN) approach is proposed to compute voltage stability indices as an alternative to the conventional approaches. The proposed ANN algorithm is used to estimate voltage stability indices under both normal and contingency operating conditions. The input variables of ANN are obtained in real-time by an on-line measurement system, i.e. Phasor Measurement Units (PMU). This thesis will propose a suboptimal approach for seeking the best locations for PMUs from a voltage stability viewpoint. The ANN-based method is not limited to compute voltage stability indices but can also be extended to determine suitable control actions. Load shedding is one of the most effective approaches against short-term voltage instability under large disturbances. The basic requirement of load shedding for recovering voltage stability is to seek an optimal solution for when, where, and how much load should be shed. Two simulation based approaches, particle swarm optimization (PSO) algorithm and sensitivity based algorithm, are proposed for load shedding to prevent voltage instability or collapse. Both approaches are based on time-domain simulation.

ABSTRACT Voltage instability has become a major concern in power systems. Many blackouts have been reported where the main cause is voltage instability. This thesis deals with two specific areas of voltage stability in on-line power system security assessments: small-disturbance (long-term) and large-disturbance (short-term) voltage stability assessment. For each category of voltage stability, both voltage stability analysis and controls are studied. The overall objective is to use the learning capabilities of computational intelligence technology to build up the comprehensive on-line power system security assessment and control strategy as well as to enhance the speed and efficiency of the process with minimal human intervention. The voltage stability problems are quantified by voltage stability indices which measure the system for the closeness of current operating point to voltage instability. The indices are different for small-disturbance and large-disturbance voltage stability assessment. Conventional approaches, such as continuation power flow or time-domain simulation, can be used to obtain voltage stability indices. However, these conventional approaches are limited by computation time that is significant for on-line computation. The Artificial Neural Network (ANN) approach is proposed to compute voltage stability indices as an alternative to the conventional approaches. The proposed ANN algorithm is used to estimate voltage stability indices under both normal and contingency operating conditions. The input variables of ANN are obtained in real-time by an on-line measurement system, i.e. Phasor Measurement Units (PMU). This thesis will propose a suboptimal approach for seeking the best locations for PMUs from a voltage stability viewpoint. The ANN-based method is not limited to compute voltage stability indices but can also be extended to determine suitable control actions. Load shedding is one of the most effective approaches against short-term voltage instability under large disturbances. The basic requirement of load shedding for recovering voltage stability is to seek an optimal solution for when, where, and how much load should be shed. Two simulation based approaches, particle swarm optimization (PSO) algorithm and sensitivity based algorithm, are proposed for load shedding to prevent voltage instability or collapse. Both approaches are based on time-domain simulation.