Accurate value of transmission line parameters is important for power system protection applications, especially for distance relays whose zone settings are based on positive sequence line impedance. The research is devoted to estimating transmission line positive-sequence parameters from synchronized or unsynchronized measurements of voltage and current phasors that are obtained at both terminals of the line. The positive sequence parameters including series impedance and shunt admittance can be linearly estimated. The linear least square algorithm has been derived in this dissertation for different transmission line configurations. The algorithm is able to handle both synchronized and unsynchronized measurements and deal with potential synchronization errors by explicitly modeling the synchronization angle. Sample results are reported to demonstrate the effectiveness of the proposed method. Three types of transmission line models depending on line length (long, medium and short) are studied in this dissertation. Chapter 3 uses unsynchronized data for the long transmission line. The derived method can detect the unsynchronized angle and estimate the positive sequence of long line parameters. The proposed method is examined with negative impacts such as errors on currents and voltages data. These errors are added randomly to one set each time to test the robustness of the developed algorithm. The medium transmission line algorithm derivation is presented in chapter 4. This chapter uses a linear least square to estimate the lumped parameters of a medium transmission line. The two different transmission line circuits are used to model the medium line. The first circuit is a single transmission line with two nodes and is used to evaluate the developed algorithm. The second circuit is a double transmission line. These two lines can have the same or different line parameters or line length. The developed algorithm shows that the proposed method achieves highly accurate results for the estimation of positive sequence line parameters. The short transmission line is studied in chapter 5. The short transmission line uses less data than the long or medium lines because in this model the shunt capacitance is omitted. Thus, the linear estimation yields highly accurate results. Case studies are considered to test the robustness of this developed method. The line temperature mainly affects the series resistance, and the developed algorithms in previous three chapters can accurately estimate the transmission line parameters. To simplify the real-time estimation of line resistance and temperature, the series inductance, and shunt capacitance can be treated as constant and known values. Chapter 6 provides such studies of estimating resistance by treating inductance and capacitance as known values.

A microgrid is a subnetwork of power system that consists of a group of distributed energy sources and loads. It is designed to integrate distributed generation, loads, energy storage devices, converters, and monitoring and protection devices. Generally, a successful microgrid could run both in island mode (off-grid) and in grid-connected mode (on-grid), being able to convert between two modes at any time. With continuous development of the power system, distributed renewable generation unit accounts for an increasing proportion, since microgrid could effectively connect these generation units to the main grid, thereby improving the energy efficiency and the energy structure. Microgrid is increasingly playing an important role in the power system. This thesis focuses on reducing the cost of microgrids through economic operation, including both static and dynamic economic operations. Three cases are tested based on these two methods. Also, each case will include four situations including one without ESS and three situations with 2MWh ESS, 3MWh ESS, 4MWh ESS, respectively.

Considering the significant investment of higher education made by students and their families, graduating in a timely manner is of the utmost importance. Delay attributed to drop out or the retaking of a course adds cost and negatively affects a student’s academic progression. Considering this, it becomes paramount for institutions to focus on student success in relation to term scheduling. Often overlooked, complexity of a course schedule may be one of the most important factors in whether or not a student successfully completes his or her degree. More often than not students entering an institution as a first time full time (FSFT) freshman follow the advised and published schedule given by administrators. Providing the optimal schedule that gives the student the highest probability of success is critical. In efforts to create this optimal schedule, this thesis introduces a novel optimization algorithm with the objective to separate courses which when taken together hurt students’ pass rates. Inversely, we combine synergistic relationships that improve a students probability for success when the courses are taken in the same semester. Using actual student data at the University of Kentucky, we categorically find these positive and negative combinations by analyzing recorded pass rates. Using Julia language on top of the Gurobi solver, we solve for the optimal degree plan of a student in the electrical engineering program using a linear and non-linear multi-objective optimization. A user interface is created for administrators to optimize their curricula at main.optimizeplans.com.

The purpose of this thesis is to use automation to create appropriate models in PSS/E with the data from Hardware-in-Loop real-time simulations. With the increase in technology of power electronics, the use of High Voltage Direct Current Technology and Flexible Alternating Current Transmission System devices in the electrical power system have increased tremendously. Static Var Compensators are widely used and it is important to have accurate and reliable models for studies relating to power systems planning and interaction. An automation method is proposed to find the parameters of an SVC model in PSS/E with the data from the Hardware-in- loop real-time simulation of the SVC physical controller using Hypersim. The effect of the SVC on the system under steady state and fault conditions are analyzed with HIL simulation of an SVC physical controller in Hypersim and its corresponding model in PSS/E in the IEEE 14 bus system. The parameters of the SVC model in PSS/E can be effectively varied to bring its response closer to that of the response from HIL simulations in Hypersim. An error function is used as a measure to understand the extent of difference between the model and the physical controller.

Increased government funding and incentives in recent years has led to an increase in the number of grid-tied renewable energy sources as their economic benefits become more renowned. Unfortunately, the outputs of these renewable resources are often highly variable, resulting in undesirable voltage disruptions that are harmful to sensitive loads. In addition to the energy variability of renewable energy sources, random voltage sags, swells and disruptions are already a major issue in power systems. Recent advances in power electronic devices have provided a platform for new solutions to the voltage support problem in power systems. One promising solution is the Dynamic Voltage Regulator (DVR), a series compensating device used to protect a sensitive load that is connected downstream from voltage sag or swell. For this thesis, the design, modeling, and analysis of a DVR system were performed using PSCAD software. Results from simulation demonstrate the DVR’s effectiveness in protecting a sensitive load from load and source side voltage disturbances as well as regulate the load bus voltage to its rated value.

Single stage cycloconverters generally incorporate hard switching at turn on and soft switching at turn off. This hard switching at turn on combined with the slow switching speeds of thyristors (the switch of choice for standard cycloconverters) limits their use to lower frequency applications. This thesis explores the analysis and design of a pulse density modulated (PDM), soft switching cycloconverter. Unlike standard cycloconverters, the controller in this converter does not adjust thyristor firing angles. It lets only complete half cycles of the input waveform through to the output. This allows and requires a much greater frequency step down from the input to the output. The advantages, shortcomings and tradeoffs of this topology are explored as this converter is designed, built and tested. The resulting cycloconverter has many deficiencies, but proves the concept of the PDM soft switching technique. Cases for further improvement and study are outlined. In the end, this converter shows much promise for applications requiring a high step down in frequency, as well as where the lower electromagnetic interference (EMI) of soft switching may be beneficial.

Cal Poly’s ongoing Energy Harvesting from Exercise Machines (EHFEM) project is a very convenient and cost-effective way for generating DC power from physical exercise and sending it back to the electrical grid as AC power, providing a renewable energy source for the future. The EHFEM project consists of numerous subprojects involving converting different types of exercise machines for power generation. This project is a continuation of one of the previous subprojects, specifically involving an elliptical machine, and focuses on improving system functionality at different machine settings without altering the elliptical user’s experience by selecting a new DC-DC converter design, while keeping the other system components intact. The new proposed DC-DC converter design is based on a non-isolated, PWM-switching single-ended primary inductor converter (SEPIC) topology, as opposed to the resonant zero-current switching/zero-voltage switching (ZCS/ZVS) topology-based off-the-shelf DC-DC converter that the previous project utilized, which had poor system functionality at high physical input levels (greater than 30V input) from the elliptical trainer. This project proves that a PWM-switching SEPIC topology provides a functional DC-DC converter design for DC power generation and inverter interfacing from a dynamic input voltage generator because of its wide input voltage range, high power driving capability and inherent voltage step-up and step-down functions. The proposed DC-DC converter supplies up to 288 watts of power and outputs 36 volts, and simultaneously takes 5-65 volts from its input depending on the elliptical user’s physical input level. This project details the new DC-DC converter’s design and construction processes, compares its topology to other existing DC-DC converter topologies and analyzes unfeasible designs as well as the overall system’s performance when converting the generated DC power to AC power, and documents any potential problems when used for this specific application.

The thesis presents a method of committing generating units in a hydro-thermal power system within practical computer resources such as computer time and data storage.

The solar industry has grown considerably in the last few years. This larger scale has introduced more problems as well as possibilities. One of those possibilities is analyzing the data coming from the sites that are now being monitored, and using the information to answer a variety of questions. We have four questions which are of prime importance identified in this thesis: 1. Can data from customers be trusted? 2. Can we use data from existing sites to determine which sites need the most improvement? 3. Can we implement a location-based algorithm to reduce the amount of false positives for performance, or other alarms? 4. Can we improve upon the current predicted power algorithm? We find that not only can we answer these questions definitively, but the improvements found are of significant value. Each of these items represents an important question that either directly or indirectly translates into increased revenue and engineering improvements for the solar industry as a whole.

Accommodating the continued increase in energy demand in the face of global climate change has been a worldwide concern. With buildings in the US consuming nearly 40% of national energy, a concerted effort must be given to reduce building energy consumption. As new buildings continue to improve their efficiency through more restrictive energy codes, the other 76.9 billion square feet of current building stock falls further behind. The rate at which current buildings are being retrofit is not enough and better tools are needed to access the benefits of retrofits and the uncertainties associated with them. This study proposes a stochastic method of building energy model calibration coupled with a monthly normative building simulation addressed in ISO 13890. This approach takes advantage of the great efficiency of Latin Hypercube Sampling and the lightweight normative building simulation method, to deliver a set of calibrated solutions to assess the effectiveness of energy conservation measure, making uncertainty a part of the modeling process. A case study on a mixed-use university building is conducted to show the strength and performance of this simple method. Limitations and future concerns are also addressed.