The power system is the largest man-made physical network in the world. Performing analysis of a large bulk system is computationally complex, especially when the study involves engineering, economic and environmental considerations. For instance, running a unit-commitment (UC) over a large system involves a huge number of constraints and integer variables. One way to reduce the computational expense is to perform the analysis on a small equivalent (reduced) model instead on the original (full) model.

The research reported here focuses on improving the network reduction methods so that the calculated results obtained from the reduced model better approximate the performance of the original model. An optimization-based Ward reduction (OP-Ward) and two new generator placement methods in network reduction are introduced and numerical test results on large systems provide proof of concept.

In addition to dc-type reductions (ignoring reactive power, resistance elements in the network, etc.), the new methods applicable to ac domain are introduced. For conventional reduction methods (Ward-type methods, REI-type methods), eliminating external generator buses (PV buses) is a tough problem, because it is difficult to accurately approximate the external reactive support in the reduced model. Recently, the holomorphic embedding (HE) based load-flow method (HELM) was proposed, which theoretically guarantees convergence given that the power flow equations are structure in accordance with Stahl’s theory requirements. In this work, a holomorphic embedding based network reduction (HE reduction) method is proposed which takes advantage of the HELM technique. Test results shows that the HE reduction method can approximate the original system performance very accurately even when the operating condition changes.

Alternate sources of energy such as wind, solar photovoltaic and fuel cells are coupled to the power grid with the help of solid state converters. Continued deregulation of the power sector coupled with favorable government incentives has resulted in the rapid growth of renewable energy sources connected to the distribution system at a voltage level of 34.5kV or below. Of late, many utilities are also investing in these alternate sources of energy with the point of interconnection with the power grid being at the transmission level. These converter interfaced generation along with their associated control have the ability to provide the advantage of fast control of frequency, voltage, active, and reactive power. However, their ability to provide stability in a large system is yet to be investigated in detail. This is the primary objective of this research.

In the future, along with an increase in the percentage of converter interfaced renewable energy sources connected to the transmission network, there exists a possibility of even connecting synchronous machines to the grid through converters. Thus, all sources of energy can be expected to be coupled to the grid through converters. The control and operation of such a grid will be unlike anything that has been encountered till now. In this dissertation, the operation and behavior of such a grid will be investigated. The first step in such an analysis will be to build an accurate and simple mathematical model to represent the corresponding components in commercial software. Once this bridge has been crossed, conventional machines will be replaced with their solid state interfaced counterparts in a phased manner. At each stage, attention will be devoted to the control of these sources and also on the stability performance of the large power system.

This dissertation addresses various concerns regarding the control and operation of a futuristic power grid. In addition, this dissertation also aims to address the issue of whether a requirement may arise to redefine operational reliability criteria based on the results obtained.

Presently, hard-switching buck/boost converters are dominantly used for automotive applications. Automotive applications have stringent system requirements for dc-dc converters, such as wide input voltage range and limited EMI noise emission. High switching frequency of the dc-dc converters is much desired in automotive applications for avoiding AM band interference and for compact size. However, hard switching buck converter is not suitable at high frequency operation because of its low efficiency. In addition, buck converter has high EMI noise due to its hard-switching. Therefore, soft-switching topologies are considered in this thesis work to improve the performance of the dc-dc converters.

Many soft-switching topologies are reviewed but none of them is well suited for the given automotive applications. Two soft-switching PWM converters are proposed in this work. For low power automotive POL applications, a new active-clamp buck converter is proposed. Comprehensive analysis of this converter is presented. A 2.2 MHz, 25 W active-clamp buck converter prototype with Si MOSFETs was designed and built. The experimental results verify the operation of the converter. For 12 V to 5 V conversion, the Si based prototype achieves a peak efficiency of 89.7%. To further improve the efficiency, GaN FETs are used and an optimized SR turn-off delay is employed. Then, a peak efficiency of 93.22% is achieved. The EMI test result shows significantly improved EMI performance of the proposed active-clamp buck converter. Last, large- and small-signal models of the proposed converter are derived and verified by simulation.

For automotive dual voltage system, a new bidirectional zero-voltage-transition (ZVT) converter with coupled-inductor is proposed in this work. With the coupled-inductor, the current to realize zero-voltage-switching (ZVS) of main switches is much reduced and the core loss is minimized. Detailed analysis and design considerations for the proposed converter are presented. A 1 MHz, 250 W prototype is designed and constructed. The experimental results verify the operation. Peak efficiencies of 93.98% and 92.99% are achieved in buck mode and boost mode, respectively. Significant efficiency improvement is achieved from the efficiency comparison between the hard-switching buck converter and the proposed ZVT converter with coupled-inductor.

The past decades have seen a significant shift in the expectations and requirements re-lated to power system analysis tools. Investigations into major power grid disturbances have suggested the need for more comprehensive assessment methods. Accordingly, sig-nificant research in recent years has focused on the development of better power system models and efficient techniques for analyzing power system operability. The work done in this report focusses on two such topics

1. Analysis of load model parameter uncertainty and sensitivity based pa-rameter estimation for power system studies

2. A systematic approach to n-1-1 analysis for power system security as-sessment

To assess the effect of load model parameter uncertainty, a trajectory sensitivity based approach is proposed in this work. Trajectory sensitivity analysis provides a sys-tematic approach to study the impact of parameter uncertainty on power system re-sponse to disturbances. Furthermore, the non-smooth nature of the composite load model presents some additional challenges to sensitivity analysis in a realistic power system. Accordingly, the impact of the non-smooth nature of load models on the sensitivity analysis is addressed in this work. The study was performed using the Western Electrici-ty Coordinating Council (WECC) system model. To address the issue of load model pa-rameter estimation, a sensitivity based load model parameter estimation technique is presented in this work. A detailed discussion on utilizing sensitivities to improve the ac-curacy and efficiency of the parameter estimation process is also presented in this work.

Cascading outages can have a catastrophic impact on power systems. As such, the NERC transmission planning (TPL) standards requires utilities to plan for n¬-1-1 out-ages. However, such analyses can be computationally burdensome for any realistic pow-er system owing to the staggering number of possible n-1-1 contingencies. To address this problem, the report proposes a systematic approach to analyze n-1-1 contingencies in a computationally tractable manner for power system security assessment. The pro-posed approach addresses both static and dynamic security assessment. The proposed methods have been tested on the WECC system.

This thesis provides a cost to benefit assessment of the proposed next generation distribution system, the Future Renewable Electric Energy Distribution Management (FREEDM) system. In this thesis, a probabilistic study is conducted to determine the payback period for an investment made in the FREEDM distribution system. The stochastic study will help in performing a detailed analysis in estimating the probability density function and statistics associated with the payback period.

This thesis also identifies several parameters associated with the FREEDM system, which are used in the cost benefit study to evaluate the investment and several direct and indirect benefits. Different topologies are selected to represent the FREEDM test bed. Considering the cost of high speed fault isolation devices, the topology design is selected based on the minimum number of fault isolation devices constrained by enhanced reliability. A case study is also performed to assess the economic impact of energy storage devices in the solid state transformers so that the fault isolation devices may be replaced by conventional circuit breakers.

A reliability study is conducted on the FREEDM distribution system to examine the customer centric reliability index, System Average Interruption Frequency Index (SAIFI). It is observed that the SAIFI was close to 0.125 for the FREEDM distribution system. In addition, a comparison study is performed based on the SAIFI for a representative U.S. distribution system and the FREEDM distribution system.

The payback period is also determined by adopting a theoretical approach and the results are compared with the Monte Carlo simulation outcomes to understand the variation in the payback period. It is observed that the payback period is close to 60 years but if an annual rebate is considered, the payback period reduces to 20 years. This shows that the FREEDM system has a significant potential which cannot be overlooked. Several direct and indirect benefits arising from the FREEDM system have also been discussed in this thesis.

This research mainly focuses on improving the utilization of photovoltaic (PV) re-sources in distribution systems by reducing their variability and uncertainty through the integration of distributed energy storage (DES) devices, like batteries, and smart PV in-verters. The adopted theoretical tools include statistical analysis and convex optimization. Operational issues have been widely reported in distribution systems as the penetration of PV resources has increased. Decision-making processes for determining the optimal allo-cation and scheduling of DES, and the optimal placement of smart PV inverters are con-sidered. The alternating current (AC) power flow constraints are used in these optimiza-tion models. The first two optimization problems are formulated as quadratically-constrained quadratic programming (QCQP) problems while the third problem is formu-lated as a mixed-integer QCQP (MIQCQP) problem. In order to obtain a globally opti-mum solution to these non-convex optimization problems, convex relaxation techniques are introduced. Considering that the costs of the DES are still very high, a procedure for DES sizing based on OpenDSS is proposed in this research to avoid over-sizing.

Some existing convex relaxations, e.g. the second order cone programming (SOCP) relaxation and semidefinite programming (SDP) relaxation, which have been well studied for the optimal power flow (OPF) problem work unsatisfactorily for the DES and smart inverter optimization problems. Several convex constraints that can approximate the rank-1 constraint X = xxT are introduced to construct a tighter SDP relaxation which is referred to as the enhanced SDP (ESDP) relaxation using a non-iterative computing framework. Obtaining the convex hull of the AC power flow equations is beneficial for mitigating the non-convexity of the decision-making processes in power systems, since the AC power flow constraints exist in many of these problems. The quasi-convex hull of the quadratic equalities in the AC power bus injection model (BIM) and the exact convex hull of the quadratic equality in the AC power branch flow model (BFM) are proposed respectively in this thesis. Based on the convex hull of BFM, a novel convex relaxation of the DES optimizations is proposed. The proposed approaches are tested on a real world feeder in Arizona and several benchmark IEEE radial feeders.

Due to the increasing trend of electricity price for the future and the price reduction of solar electronics price led by the policy stimulus and the technological improvement, the residential distribution solar photovoltaic (PV) system’s market is prosperous. Excess energy can be sold back to the grid, however peak demand of a residential customer typically occurs in late afternoon/early evening when PV systems are not a productive. The solar PV system can provide residential customers sufficient energy during the daytime, even the exceeding energy can be sold back to the grid especially during the day with good sunlight, however, the peak demand of a regular family always appears during late afternoon and early evening which are not productive time for PV system. In this case, the PV customers only need the grid energy when other customers also need it the most. Because of the lower contribution of PV systems during times of peak demand, utilities are beginning to adjust rate structures to better align the bills paid by PV customers with the cost to the utility to serve those customers. Different rate structures include higher fixed charges, higher on-peak electricity prices, on-peak demand charges, or prices based on avoided costs. The demand charge and the on-peak energy charge significantly reduced the savings brought by the PV system. This will result in a longer the customer’s payback period. Eventually PV customers are not saving a lot in their electricity bill compare to those customers who do not own a PV system.



A battery system is a promising technology that can improve monthly bill savings since a battery can store the solar energy and the off-peak grid energy and release it later during the on-peak hours. Sponsored by Salt River Project (SRP), a smart home model consists 1.35 kW PV panels, a 7.76 kWh lithium-ion battery and an adjustable resistive load bank was built on the roof of Engineering Research Center (ERC) building. For analysis, data was scaled up by 6/1.35 times to simulate a real residential PV setup. The testing data had been continuously recorded for more than one year (Aug.2014 - Oct.2015) and a battery charging strategy was developed based on those data. The work of this thesis deals with the idea of this charging strategy and the economic benefits this charging strategy can bring to the PV customers. Part of this research work has been wrote into a conference paper which is accepted by IEEE PES General Meeting 2016. A new and larger system has been installed on the roof with 6 kW PV modules and 6 kW output integrated electronics. This project will go on and the method come up by this thesis will be tested.

This dissertation presents innovative techniques to develop performance-based models and complete transient models of induction motor drive systems with vector controls in electro-magnetic transient (EMT) and positive sequence transient stability (PSTS) simulation programs. The performance-based model is implemented by obtaining the characteristic transfer functions of perturbed active and reactive power consumptions with respect to frequency and voltage perturbations. This level of linearized performance-based model is suitable for the investigation of the damping of small-magnitude low-frequency oscillations. The complete transient model is proposed by decomposing the motor, converter and control models into d-q axes components and developing a compatible electrical interface to the positive-sequence network in the PSTS simulators. The complete transient drive model is primarily used to examine the system response subject to transient voltage depression considering increasing penetration of converter-driven motor loads.

For developing the performance-based model, modulations are performed on the supply side of the full drive system to procure magnitude and phase responses of active and reactive powers with respect to the supply voltage and frequency for a range of discrete frequency points. The prediction error minimization (PEM) technique is utilized to generate the curve-fitted transfer functions and corresponding bode plots. For developing the complete drive model in the PSTS simulation program, a positive-sequence voltage source is defined properly as the interface of the model to the external system. The dc-link of the drive converter is implemented by employing the average model of the PWM converter, and is utilized to integrate the line-side rectifier and machine-side inverter.

Numerical simulation is then conducted on sample test systems, synthesized with suitable characteristics to examine performance of the developed models. The simulation results reveal that with growing amount of drive loads being distributed in the system, the small-signal stability of the system is improved in terms of the desirable damping effects on the low-frequency system oscillations of voltage and frequency. The transient stability of the system is also enhanced with regard to the stable active power and reactive power controls of the loads, and the appropriate VAr support capability provided by the drive loads during a contingency.

Overhead high voltage transmission lines are widely used around the world to deliver power to customers because of their low losses and high transmission capability. Well-coordinated insulation systems are capable of withstanding lightning and switching surge voltages. However, flashover is a serious issue to insulation systems, especially if the insulator is covered by a pollution layer. Many experiments in the laboratory have been conducted to investigate this issue. Since most experiments are time-consuming and costly, good mathematical models could contribute to predicting the insulator flashover performance as well as guide the experiments. This dissertation proposes a new statistical model to calculate the flashover probability of insulators under different supply voltages and contamination levels. An insulator model with water particles in the air is simulated to analyze the effects of rain and mist on flashover performance in reality. Additionally, insulator radius and number of sheds affect insulator surface resistivity and leakage distance. These two factors are studied to improve the efficiency of insulator design. This dissertation also discusses the impact of insulator surface hydrophobicity on flashover voltage.

Because arc propagation is a stochastic process, an arc could travel on different paths based on the electric field distribution. Some arc paths jump between insulator sheds instead of travelling along the insulator surfaces. The arc jumping could shorten the leakage distance and intensify the electric field. Therefore, the probabilities of arc jumping at different locations of sheds are also calculated in this dissertation.

The new simulation model is based on numerical electric field calculation and random walk theory. The electric field is calculated by the variable-grid finite difference method. The random walk theory from the Monte Carlo Method is utilized to describe the random propagation process of arc growth. This model will permit insulator engineers to design the reasonable geometry of insulators, to reduce the flashover phenomena under a wide range of operating conditions.

Transmission voltages worldwide are increasing to accommodate higher power transfer from power generators to load centers. Insulator dimensions cannot increase linearly with the voltage, as supporting structures become too tall and heavy. Therefore, it is necessary to optimize the insulator design considering all operating conditions including dry, wet and contaminated. In order to design insulators suitably, a better understanding of the insulator flashover is required, as it is a serious issue regarding the safe operation of power systems. However, it is not always feasible to conduct field and laboratory studies due to limited time and money.

The desire to accurately predict the performance of insulator flashovers requires mathematical models. Dynamic models are more appropriate than static models in terms of the instantaneous variation of arc parameters. In this dissertation, a dynamic model including conditions for arc dynamics, arc re-ignition and arc motion with AC supply is first developed.

For an AC power source, it is important to consider the equivalent shunt capacitance in addition to the short circuit current when evaluating pollution test results. By including the power source in dynamic models, the effects of source parameters on the leakage current waveform, the voltage drop and the flashover voltage were systematically investigated. It has been observed that for the same insulator under the same pollution level, there is a large difference among these flashover performances in high voltage laboratories and real power systems. Source strength is believed to be responsible for this discrepancy. Investigations of test source strength were conducted in this work in order to study its impact on different types of insulators with a variety of geometries.

Traditional deterministic models which have been developed so far can only predict whether an insulator would flashover or withstand. In practice, insulator flashover is a statistical process, given that both pollution severity and flashover voltage are probabilistic variables. A probability approach to predict the insulator flashover likelihood is presented based on the newly developed dynamic model.