The aim of generator maintenance scheduling (GMS) in an electric power system is to allocate a proper maintenance timetable for generators while maintaining a high system reliability, reducing total production cost, extending generator life time etc. In order to solve this complex problem a genetic algorithm technique is proposed here. The paper discusses the implementation of GAs to GMS problems with two approaches: generational and steady state. The results of applying these GAs to a test GMS problem based on a practical power system scenario are presented and analysed. The effect of different GA parameters is also studied

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Much work has been done in applying computer solutions to the problem of power systems fault and stability studies. However, with a few notable exceptions, previous efforts have largely been confined to attempts to solve the problems in the classical manner by having the computer simply take over the tedious portion of the calculations. A few pioneers have succeeded in finding new methods of solving some of the problems by the use of the machine equations, without resorting to the simplifying assumptions necessary for the classical method of solution and their inevitable inaccuracies. These pioneers, however, have only dealt with the balanced condition type of fault, such as a three-phase-fault or a sudden change in load on a machine, and have ignored the far more common although less severe types of fault wherein the system becomes unbalanced due to a fault involving only one or two phases. In contrast, this thesis deals with the unbalanced type of fault on a system. The necessary equations are derived and simple problems are solved for three major types of faults, i.e., the single-phase-to-ground fault, the phase-to-phase fault, and the two-phase-to-ground fault. In addition, a program is written to simulate a field study in order that a comparison can be made. The programs used are written for the single-machine on an infinite bus, and are written so that initial steady conditions and machine and system constants may be entered easily, thus making the thesis method usable by practicing power systems engineers. The thesis method results in a great variety of useful data, which, since they may be transformed into symmetrical components form allows the use of classical methods of system reduction and re-expansion so that fault currents and voltages may be found at any point in the system. All that is required for a system analysis is the reduction of the system, the choice of program for the type of fault under consideration, and the re-expansion of the system. It is hoped that the results of this thesis may prove useful not only to those who wish to continue research in this area, but also to those who are practicing engineers concerned with system fault studies and who are in need of an improved method for the study of unbalanced faults. / Ph. D.

This dissertation presents a new, highly robust algorithm for electric power system state estimation. A graph theory-based system decomposition scheme is coupled with a high breakdown point estimator to allow reliable identification of multiple interacting bad data even in cases of conforming errors. The algorithm is inherently resistant to bad measurements in positions of leverage, makes no a priori measurement error probability distribution assumptions, and is applicable in a real-time environment. In addition to presenting a new state estimation algorithm, the weaknesses of two prominent state determination methods are explored. The comparative advantages of high breakdown point estimators are then summarized. New theorems quantifying the previously unexamined effect system sparsity has on the exact fit point of some members of this estimator family are presented. These results serve as the catalyst for the overall state estimation algorithm presented. Numerous practical implementation issues are addressed with efficient implementation techniques described at each step. / Ph. D.

The problem of incorporating non-dispatchable energy sources such as solar energy into electric utility capacity expansion programs is as yet unsolved. This thesis develops methods to incorporate solar energy as a decision variable into capacity planning and capacity expansion planning algorithms. The model is based on variable or intermittent availability of solar energy. For capacity planning, certain convexity properties are established which lead to an efficient decomposition process using a Newton-type search method. For the capacity expansion planning problem, a modification of Benders' Decomposition is applied, which breaks up the problem into a master program containing the solar decision variable, and a subproblem which involves an expansion problem in conventional equipment types. The primal solution to the subproblem is found with existing algorithms, the dual solution can be obtained from the primal solution employing a network interpretation of the problem. This analysis leads to an efficient tangential approximation method. Illustrative examples, computational experience and further generalizations are also provided. / Master of Science

A real time generation station simulator which is to be used as an operator trainer is developed. The software developed simulates a Y-wound generator connected to an infinite bus through a Δ/Y step up transformer and two parallel lines. The operation of the generator is simulated under normal or abnormal conditions of the power system or the generator itself. The system is simulated in two microcomputers and interaction between the simulator and the operator is provided through the computer's screen and keyboard. Different screen representations show the behavior of the generator at any moment and based on these the operator can take any action through the generator controls provided in his keyboard. / Master of Science

This thesis discusses applications of phasor measurement units to power system monitoring and synchronous generator modeling. Adjustments to a previously developed PMU placement algorithm are described which observe generator and tie line flows explicitly and reduces the number of PMUs required for a system, still observing the major dynamic components of a system. This adjusted methodology leaves some buses unobserved. A method for estimating the state of the unobserved region is developed based on using constant admittance or constant current load models. These models are accurate for a small neighborhood around the operating point when they were calculated. To determine the maximum error expected for any given system estimate, an equation relating the maximum error in the voltages to the maximum change in load power is derived. Once the issue of power system monitoring has been presented, the application of PMUs to the synchronous generator modeling is explored. This thesis deals with the on-line identification of the generator transient model using a recursive version of the generalized least squares algorithm. Simulations have been performed to demonstrate the validity and difficulties with these methods. / 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

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.

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.