This thesis investigates different unidirectional topologies for the on-board charger in an electric vehicle and proposes soft-switching solutions in both the AC/DC and DC/DC stage of the converter with a power rating of 3.3 kW. With an overview on different charger topologies and their applicability with respect to the target specification a soft-switching technique to reduce the switching losses of a single phase boost-type PFC is proposed. This work is followed by a modification to the popular soft-switching topology, the dual active bridge (DAB) converter for application requiring unidirectional power flow. The topology named as the semi-dual active bridge (S-DAB) is obtained by replacing the fully active (four switches) bridge on the load side of a DAB by a semi-active (two switches and two diodes) bridge. The operating principles, waveforms in different intervals and expression for power transfer, which differ significantly from the basic DAB topology, are presented in detail. The zero-voltage switching (ZVS) characteristics and requirements are analyzed in detail and compared to those of DAB. A small-signal model of the new configuration is also derived. The analysis and performance of S-DAB are validated through extensive simulation and experimental results from a hardware prototype.



Secondly, a low-loss auxiliary circuit for a power factor correction (PFC) circuit to achieve zero voltage transition is also proposed to improve the efficiency and operating frequency of the converter. The high dynamic energy generated in the switching node during turn-on is diverted by providing a parallel path through an auxiliary inductor and a transistor placed across the main inductor. The paper discusses the operating principles, design, and merits of the proposed scheme with hardware validation on a 3.3 kW/ 500 kHz PFC prototype. Modifications to the proposed zero voltage transition (ZVT) circuit is also investigated by implementing two topological variations. Firstly, an integrated magnetic structure is built combining the main inductor and auxiliary inductor in a single core reducing the total footprint of the circuit board. This improvement also reduces the size of the auxiliary capacitor required in the ZVT operation. The second modification redirects the ZVT energy from the input end to the DC link through additional half-bridge circuit and inductor. The half-bridge operating at constant 50% duty cycle simulates a switching leg of the following DC/DC stage of the converter. A hardware prototype of the above-mentioned PFC and DC/DC stage was developed and the operating principles were verified using the same.

With the status of nuclear proliferation around the world becoming more and more complex, nuclear forensics methods are needed to restrain the unlawful usage of nuclear devices. Lithium-ion batteries are present ubiquitously in consumer electronic devices nowadays. More importantly, the materials inside the batteries have the potential to be used as neutron detectors, just like the activation foils used in reactor experiments. Therefore, in a nuclear weapon detonation incident, these lithium-ion batteries can serve as sensors that are spatially distributed.

In order to validate the feasibility of such an approach, Monte Carlo N-Particle (MCNP) models are built for various lithium-ion batteries, as well as neutron transport from different fission nuclear weapons. To obtain the precise battery compositions for the MCNP models, a destructive inductively coupled plasma mass spectrometry (ICP-MS) analysis is utilized. The same battery types are irradiated in a series of reactor experiments to validate the MCNP models and the methodology. The MCNP nuclear weapon radiation transport simulations are used to mimic the nuclear detonation incident to study the correlation between the nuclear reactions inside the batteries and the neutron spectra. Subsequently, the irradiated battery activities are used in the SNL-SAND-IV code to reconstruct the neutron spectrum for both the reactor experiments and the weapon detonation simulations.

Based on this study, empirical data show that the lithium-ion batteries have the potential to serve as widely distributed neutron detectors in this simulated environment to (1) calculate the nuclear device yield, (2) differentiate between gun and implosion fission weapons, and (3) reconstruct the neutron spectrum of the device.

On-line dynamic security assessment (DSA) analysis has been developed and applied in several power dispatching control centers. Existing applications of DSA systems are limited by the assumption of the present system operating conditions and computational speeds. To overcome these obstacles, this research developed a novel two-stage DSA system to provide periodic security prediction in real time. The major contribution of this research is to develop an open source on-line DSA system incorporated with Phasor Measurement Unit (PMU) data and forecast load. The pre-fault prediction of the system can provide more accurate assessment of the system and minimize the disadvantage of a low computational speed of time domain simulation.

This Thesis describes the development of the novel two-stage on-line DSA scheme using phasor measurement and load forecasting data. The computational scheme of the new system determines the steady state stability and identifies endangerments in a small time frame near real time. The new on-line DSA system will periodically examine system status and predict system endangerments in the near future every 30 minutes. System real-time operating conditions will be determined by state estimation using phasor measurement data. The assessment of transient stability is carried out by running the time-domain simulation using a forecast working point as the initial condition. The forecast operating point is calculated by DC optimal power flow based on forecast load.

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.

In sub transmission systems, many more raptor deaths have been recorded near metal poles rather than wood poles. The metal pole, which is reliable in structure but also grounded, may increase the risk of electrocution when raptors perch on the insulator. This thesis focuses on evaluating the effectiveness of the raptor guard to prevent both debilitating and lethal electrocutions to local wildlife in 69 kV sub transmission systems. First, the two-dimensional (2D) finite difference methods (FDM) were proposed to solve the Poisson and Laplace equations, which describe the electric field. Second, the verification of the FDM algorithm was made based on a parallel-plate capacitor model. Then, the potential and the electric field were simulated by the raptor-insulator model to evaluate the possibility of flashover and leakage current under various conceivable scenarios. Third, several dielectric performance experiments were implemented to gain insight into the physical property of the raptor guard developed by the Salt River Project (SRP) as an example. The proposed initial-tracking-voltage and time-to-track experiments tested the ability of the guard, which is designed to prevent the tracking phenomenon under a contaminated situation such as rain, fog, and snow. A data acquisition also collected the leakage current data for the comparison of maximum raptor tolerance. Furthermore, the puncture voltage of this guard material was performed by the dielectric breakdown voltage experiment in an oil-covered container. With the combination of the model simulation and the experiments in this research, the raptor guard was proven to be practical and beneficial in sub transmission system.

A nonlinear dynamic model for a passively cooled small modular reactor (SMR) is developed. The nuclear steam supply system (NSSS) model includes representations for reactor core, steam generator, pressurizer, hot leg riser and downcomer. The reactor core is modeled with the combination of: (1) neutronics, using point kinetics equations for reactor power and a single combined neutron group, and (2) thermal-hydraulics, describing the heat transfer from fuel to coolant by an overall heat transfer resistance and single-phase natural circulation. For the helical-coil once-through steam generator, a single tube depiction with time-varying boundaries and three regions, i.e., subcooled, boiling, and superheated, is adopted. The pressurizer model is developed based upon the conservation of fluid mass, volume, and energy. Hot leg riser and downcomer are treated as first-order lags. The NSSS model is incorporated with a turbine model which permits observing the power with given steam flow, pressure, and enthalpy as input. The overall nonlinear system is implemented in the Simulink dynamic environment. Simulations for typical perturbations, e.g., control rod withdrawal and increase in steam demand, are run. A detailed analysis of the results show that the steady-state values for full power are in good agreement with design data and the model is capable of predicting the dynamics of the SMR. Finally, steady-state control programs for reactor power and pressurizer pressure are also implemented and their effect on the important system variables are discussed.

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.

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.

The inherent intermittency in solar energy resources poses challenges to scheduling generation, transmission, and distribution systems. Energy storage devices are often used to mitigate variability in renewable asset generation and provide a mechanism to shift renewable power between periods of the day. In the absence of storage, however, time series forecasting techniques can be used to estimate future solar resource availability to improve the accuracy of solar generator scheduling. The knowledge of future solar availability helps scheduling solar generation at high-penetration levels, and assists with the selection and scheduling of spinning reserves. This study employs statistical techniques to improve the accuracy of solar resource forecasts that are in turn used to estimate solar photovoltaic (PV) power generation. The first part of the study involves time series forecasting of the global horizontal irradiation (GHI) in Phoenix, Arizona using Seasonal Autoregressive Integrated Moving Average (SARIMA) models. A comparative study is completed for time series forecasting models developed with different time step resolutions, forecasting start time, forecasting time horizons, training data, and transformations for data measured at Phoenix, Arizona. Approximately 3,000 models were generated and evaluated across the entire study. One major finding is that forecasted values one day ahead are near repeats of the preceding day—due to the 24-hour seasonal differencing—indicating that use of statistical forecasting over multiple days creates a repeating pattern. Logarithmic transform data were found to perform poorly in nearly all cases relative to untransformed or square-root transform data when forecasting out to four days. Forecasts using a logarithmic transform followed a similar profile as the immediate day prior whereas forecasts using untransformed and square-root transform data had smoother daily solar profiles that better represented the average intraday profile. Error values were generally lower during mornings and evenings and higher during midday. Regarding one-day forecasting and shorter forecasting horizons, the logarithmic transformation performed better than untransformed data and square-root transformed data irrespective of forecast horizon for data resolutions of 1-hour, 30-minutes, and 15-minutes.

Present distribution infrastructure is designed mainly for uni-directional power flow with well-controlled generation. An increase in the inverter-interfaced photovoltaic (PV) systems requires a thorough re-examination of the design, operation, protection and control of distribution systems. In order to understand the impact of high penetration of PV generation, this work conducts an automated and detailed modeling of a power distribution system. The simulation results of the modeled distribution feeder have been verified with the field measurements.

Based on the feeder model, this work studies the impact of the PV systems on voltage profiles under various scenarios, including reallocation of the PV systems, reactive power support from the PV inverters, and settings of the load-tap changing transformers in coordination with the PV penetration. Design recommendations have been made based on the simulation results to improve the voltage profiles in the feeder studied.

To carry out dynamic studies related to high penetration of PV systems, this work proposes a differential algebraic equation (DAE) based dynamic modeling and analysis method. Different controllers including inverter current controllers, anti-islanding controllers and droop controllers, are designed and tested in large systems. The method extends the capability of the distribution system analysis tools, to help conduct dynamic analyses in large unbalanced distribution systems.

Another main contribution of this work is related to the investigation of the PV impacts on the feeder protection coordination. Various protection coordination types, including fuse-fuse, recloser-fuse, relay-fuse and relay-recloser have been studied. The analyses provide a better understanding of the relay and recloser settings under different configurations of the PV interconnection transformers, PV penetration levels, and fault types.

A decision tree and fuzzy logic based fault location identification process has also been proposed in this work. The process is composed of the off-line training of the decision tree, and the on-line analysis of the fault events. Fault current contribution from the PV systems, as well as the variation of the fault resistance have been taken into consideration. Two actual fault cases with the event data recorded were used to examine the effectiveness of the fault identification process.