This thesis investigates and develops a direct method for transient stability analysis using the energy approach [1] and the Phasor Measurement Units (PMUs). The originality of this new method results from a combination of a prediction of the post-fault trajectory based on the PMUs and the Transient Energy Function of a multimachine system. Thanks to the PMUs, the weakness of the direct methods, which is the over-simplification of the generator model, is overcome. This new method consists of fitting a curve to the data of the post-fault path provided by PMUs and identifying the controlling unstable equilibrium point (c.u.e.p.). Two second-order linear models have been estimated and evaluated from a prediction viewpoint. These are a polynomial function and an auto-regressive model. These parameters have been estimated by means of the least-squares estimator. They have been compared to the model proposed by Y. Ohura et al. [6], which has been upgraded into an iterative algorithm. The post-fault trajectory is predicted until the exit point located on the Potential Energy Boundary Surface (p.e.b.s.) is reached. In order to detect with efficiency this exit point and to find the c.u.e.p., it is proposed a combination of the so called "Ball-Drop" method [22] and an improved version of the Shadowing method. These combined procedures give accurate results when they are compared to the step-by-step method, which directly integrates the differential equations using a fourth-order Runga-Kutta method. The simulations have been carried out on a 3-machine system and on the 10-machine New-England power system. / Master of Science

A method of calculating the yearly owning and operating cost of a distribution transformer is developed taking into consideration the loss of life due to overload. Using the developed methods, the potential benefits of managing an overloaded distribution transformer was calculated for a transformer on the Virginia Electric and Power Company (Vepco) System. By loading the transformer according to a saturation type load growth curve considered typical for Vepco System, its life was approximated. The fixed carrying charges were then applied at a rate sufficient to recover all invested capital during the life of the transformer. The potential savings were calculated when cutting the secondary and adding a transformer of equal one size smaller and two sizes smaller than the original. The study indicated no savings would be obtained when cutting the secondary. The only savings indicated were obtained by taking down an overloaded transformer and replacing it with the next larger size. The potential savings of managing these transformers presently installed, as well as those to be installed in the next years, as well as those to be installed in the next ten years, was calculated using a critical rate of return of 6, 7, 8, 9, and 10 percent. The calculated savings were $3,251,500 at 6 Percent, $2,674,400 at 7 Percent, $2,075,400 at 8 Percent, $1,602,200 at 9 Percent, $1,257,300 at 10 Percent. / Master of Science

In the early 1990's, with the boom of the Internet and the advancements in telecommunications, the demand for high-speed communications systems has reached every corner of the world in forms such as, phone exchanges, the internet servers, routers, and all other types of telecommunication systems. These communication systems demand more data computing, storage, and retrieval capabilities at higher speeds, these demands place a great strain on the power system. To lessen this strain, the existing power architecture must be optimized. With the arrival of the age of high speed and power hungry microprocessors, the point of load converter has become a necessity. The power delivery architecture has changed from a centralized distribution box delivering an entire system's power to a distributed architecture, in which a common DC bus voltage is distributed and further converted down at the point of load. Two common distributed bus voltages are 12 V for desktop computers and 48 V for telecommunications server applications. As industry strives to design more functionality into each circuit or motherboard, the area available for the point of load converter is continually decreasing. To meet industries demands of more power in smaller sizes power supply designers must increase the converter's switching frequencies. Unfortunately, as the converter switching frequency increases the efficiency is compromised. In particular, the switching, gate drive and body diode related losses proportionally increase with the switching frequency. This thesis introduces a loss saving self-driven method to drive the secondary side synchronous rectifiers. The loss saving self-driven method introduces two additional transformers that increase the overall footprint of the converter. Also, this thesis proposes a new magnetic integration method to eliminate the need for the two additional gate driver magnetic cores by allowing three discrete power signals to pass through one single magnetic structure. The magnetic integration reduces the overall converter footprint. / Master of Science

Robust estimation of statistical parameters is traditionally believed to exist in a trade space between robustness and efficiency. This thesis examines the Minimum Hellinger Distance Estimator (MHDE), which is known to have desirable robustness properties as well as desirable efficiency properties. This thesis confirms that the MHDE is simultaneously robust against outliers and asymptotically efficient in the univariate location case. Robustness results are then extended to the case of simple linear regression, where the MHDE is shown empirically to have a breakdown point of 50%. A geometric algorithm for solution of the MHDE is developed and implemented. The algorithm utilizes the Riemannian manifold properties of the statistical model to achieve an algorithmic speedup. The MHDE is then applied to an illustrative problem in power system state estimation. The power system is modeled as a structured linear regression problem via a linearized direct current model; robustness results in this context have been investigated and future research areas have been identified from both a statistical perspective as well as an algorithm design standpoint. / Master of Science

The power grid has evolved over the course of many decades with the usage of cyber systems and communications such as Supervisory Control And Data Acquisition (SCADA); however, due to their connectivity to the internet, the cyber-power system can be infiltrated by malicious attackers. Encryption is not a singular solution. Currently, there are several cyber security measures in development, including those based on artificial intelligence. However, there is a need for a varying but consistent attack algorithm to serve as a testbed for these AI or other practices to be trained and tested. This is important because in the event of a real attacker, it is not possible to know exactly where they will attack and in what order. Therefore, the proposed method in this thesis is to use criminology concepts and fuzzy logic inference to create this algorithm and determine its effectiveness in making decisions on a cyber-physical system model. The method takes various characteristics of the attacker as an input, builds their ideal target node, and then compares the nodes to the high-impact target and chooses one as the goal. Based on that target and their knowledge, the attackers will attack nodes if they have resources. The results show that the proposed method can be used to create a variety of attacks with varying damaging effects, and one other set of tests shows the possibility for multiple attacks, such as denial of service and false data injection. The proposed method has been validated using an extended cyber-physical IEEE 13-node distribution system and sensitivity tests to ensure that the ruleset created would take each of the inputs well. / Master of Science / For the last decades, information and communications technology has become more commonplace for electric power and energy systems around the world. As a result, it has attracted hackers to take advantage of the cyber vulnerabilities to attack critical systems and cause damage, e.g., the critical infrastructure for electric energy. The power grid is a wide-area, distributed infrastructure with numerous power plants, substations, transmission and distribution lines as well as customer facilities. For operation and control, the power grid needs to acquire measurements from substations and send control commands from the control center to substations. The cyber-physical system has its vulnerabilities that can be deployed by hackers to launch falsified measurements or commands. Much research is concerned with how to detect and mitigate cyber threats. These methods are used to determine if an attack is occurring, and, if so, what to do about it. However, for these techniques to work properly, there must be a way to test how the defense will understand the purpose and target of an actual attack, which is where the proposed modeling and simulation method for an attacker comes in. Using a set of values for their resources, motivation and other characteristics, the defense algorithm determines what the attacker's best target would be, and then finds the closest point on the power grid that they can attack. While there are still resources remaining based on the initial value, the attacker will keep choosing places and then execute the attack. From the results, these input characteristic values for the attacker can affect the decisions the attacker makes, and the damage to the system is reflected by the values too. This is tested by looking at the results for the high-impact nodes for each input value, and seeing what came out of it. This shows that it is possible to model an attacker for testing purposes on a simulation.

In order for photovoltaic systems to gain acceptance as viable energy sources, they must have a sufficient life span and must be optimized to provide maximum power. In order to achieve these goals, several maximum power point tracking (MPPT) algorithms have been developed to ensure the photovoltaic (PV) system operates at maximum efficiency despite changes in temperature, shading, and age of the solar cells. However, the connection of multiple PV systems in parallel cannot be achieved using a single MPPT control due to the characteristic differences in each solar array's orientation, illumination, temperature, composition, and age. The mismatch of the individual PV systems can limit the power output and reliability of the systems, as well as reduce the expected lifetime. Multi-channel PV systems require MPPT controls for each channel, as well as communication between channels so that power extraction is shared among channels. Therefore, an algorithm is presented which includes MPPT and promotes equal power sharing between the sources and the load in order to make multichannel PV systems more robust, reliable, and efficient. The algorithm is implemented using a digital signal processor (DSP), and the validity of the algorithm will be proven using modeling techniques and through the construction of a prototype two-channel PV system. Once the viability of the two channel system has been proven, the expansion of the system to an n-channel system will be discussed.

A new network model has been developed which allows the calculation of state estimates for unbalanced electric power systems. This model incorporates the effects of mutually coupled conductors, earth return paths, unbalanced device configurations, and multiple voltage references. Development of the new model appeals to multiport network theory and graph theoretic principles. Model equations are employed directly to obtain least squares estimators in the phase-voltage reference frame. The concept of power system segments is introduced and segment multiport equations are developed. The concept of power system modified primitive networks is introduced and system multiport equations are developed. Segment and system multiport equations are used to obtain a state estimator formulation in variables suitable for practical systems analysis. / Ph. D.

Modern power substations continue to use hardware that is dated and resistant to modernization. This document discusses the basics of substations, identifies their weaknesses, and suggests a method of improvement. This suggestion implements a centralized protection and control system to make the overall system more robust and flexible to the ever changing power system landscape. / Master of Science / The infrastructure that connects electrical power generators to consumers utilizes a wide range of equipment to safely and reliably prevent interruption to service. New distributed power technologies have been introduced to the power system, such as solar panels, wind farms, and home batteries, which have caused the way this system become more dynamic then it has in the past. Most of these changes have occurred on the generation and consumption sides of the system, but the equipment that connects those two sides have not evolved very much in the last 50 years. This document explores some of the problems that this can cause and discusses a method to improve called Centralized Protection and Control.

A novel probabilistic method has been developed for modelling the operation of energy storage in electricity systems with significant amounts of wind and solar powered generation. This method is based on a spectral analysis of the variations of wind speed and solar irradiance together with profiles of electrical demand. The method has been embodied in two Matlab computer programs: Wind power only: This program models wind power on any time scale from seconds to years, with limited modelling of demand profiles. This program is only capable of modelling stand-alone systems, or systems in which the electrical demand is replaced by a weak grid connection with limited export capacity. 24-hours: This program models wind power, solar PV power and electrical demand, including seasonal and diurnal effects of each. However, this program only models store cycle times (variations within a time scale) of 24 hours. This program is capable of modelling local electrical demand at the same time as a grid connection with import or export capacity and a backup generator. Each of these programs has been validated by comparing its results with those from a time step program, making four Matlab programs in total. All four programs calculate the power flows to and from the store, satisfied demand, unsatisfied demand and curtailed power. The programs also predict the fractions of time that the store spends full, empty, filling or emptying. The results obtained are promising. Probabilistic program results agree well with time step results over a wide range of input data and time scales. The probabilistic method needs further refinement, but can be used to perform initial modelling and feasibility studies for renewable energy systems. The probabilistic method has the advantage that the required input data is less, and the computer run time is reduced, compared to the time step method.

This thesis provides a synchrophasor data analysis methodology that leverages both statistical correlation techniques and a statistical distribution in order to identify data inconsistencies, as well as power system contingencies. This research utilizes archived Phasor Measurement Unit (PMU) data obtained from the Bonneville Power Administration in order to show that this methodology is not only feasible, but extremely useful for power systems monitoring, decision support, and planning purposes. By analyzing positive sequence voltage angles between a pair of PMUs at two different substation locations, an historic record of correlation is established. From this record, a Rayleigh distribution of correlation coefficients is calculated. The statistical parameters of this Rayleigh distribution are used to infer occurrences of power system and data events. To monitor an entire system, a simple solution would be observing each of these parameters for every PMU combination. One issue with this approach is that correlation of some PMU pairs may be redundant or yield little value to monitoring capabilities. Additionally, this approach quickly encounters scalability issues as each additional PMU adds considerably to computation - for example, if the system contains n PMUs the amount of computations will be n(n-1)/2. System-wide monitoring of these parameters in this fashion is cumbersome and inefficient. To address these issues, an alternative scheme is proposed which involves monitoring only a subset of PMUs characterized by electrically coupled zones, or clusters, of PMUs. These clusters include both electrically-distant and electrically-near PMU sites. When monitored over an event, these yield statistical parameters sufficient for detecting event occurrences. This clustering scheme can be utilized to significantly decrease computation time and allocation of resources while maintaining optimal system observability. Results from the statistical methods are presented for a select few case studies for both data and power system event detection. In addition, determination of cluster size and content is discussed in detail. Lastly, the viability of monitoring pertinent statistical parameters over various clustering schemes is demonstrated.