Photovoltaics panel (PV) integration with the utility grid has been installed throughout the globe. The fault-monitoring technology for photovoltaics (PV) panels is a method to save energy production losses and become a key contributor to overall cost reduction in variable operating costs for photovoltaics systems. PV researchers today explore factors such as reducing utility energy bills and CO2 emissions, grid voltage stability, peak demand shaving, supply of electric power off-grid areas, and many more. The technology discussed is easy to incorporate, requires no additional hardware, doesn't alter the system’s stability, is implemented at a steady state point, and is helpful to record changes in PV cell operation from forward bias to reverse bias state. PV panel AC impedance can be used as an early-stage fault indicator. Also, comparing AC impedance magnitude and phase at maximum power point (MPP) or near MPP can help identify the nature of the fault in a PV system. The focus of the thesis is proposing the fault detection of 300 W PV panels using online AC impedance measurement, utilizing existing panel-level power optimizers and microinverters in a PV system to actively perturb small signals into the PV panel and compute its small signal impedance. The technology is incorporated in a power optimizer with C2000 MCU and helps identify hot spot faults and short circuit faults in a 300 W rooftop PV panel. Multiple PV panel faults scenarios such as hot spot faults, short circuit faults, junction box faults, and capacitor faults are investigated to deduct further the effectiveness of the online impedance measurement using a small signal. This thesis’s focus areas are, first, modeling the PV panel and power converter and incorporating fault scenarios to identify the fault indicators. Secondly, measuring PV panel impedance under normal and faulty conditions using an equipment-based offline technique. Lastly, measuring PV panel impedance under normal and faulty conditions using a power optimizer. / M.S. / A Photovoltaics panel is a series and parallel combination of many photovoltaics cells to generate electricity from sunlight via a photoelectric process. The fault-monitoring technology for photovoltaics (PV) panels is a method to save energy production losses and become a key contributor to overall cost reduction in variable operating costs for photovoltaics systems. The PV panel, over a period of time, can degrade with fluctuations in temperature and weather. Photovoltaics panel (PV) integration with the utility grid has been installed throughout the globe. PV researchers today explore factors such as reducing utility energy bills and CO2 emissions, grid voltage stability, peak demand shaving, supply of electric power off-grid areas, and many more. The technology discussed is easy to incorporate, requires no additional hardware, doesn't alter the system’s stability, is implemented at a steady state point, and is helpful to record changes in PV cell operation from forward bias to reverse bias state. A PV panel operating at maximum power point (MPP) generates direct current (DC) and maintains a stable voltage across the PV panel load. A small signal injection in PV panel current or voltage is an addition of a sinusoidal signal with an amplitude of 10 % to the operating point of PV panel voltage or current and frequency sweep between 10 Hz to 200 kHz. The PV panel's AC impedance is measured under small signal injection and can be used as an early-stage fault indicator. Also, comparing AC impedance magnitude and phase at maximum power point (MPP) or near MPP can help identify the nature of the fault in a PV system. The focus of the thesis is proposing the fault detection of PV panels using online AC impedance measurement and utilizing existing panel-level power optimizers and microinverters in a PV system to actively perturb small signals into the PV panel and compute its small signal impedance. The technology is incorporated in a power optimizer with C2000 MCU and helps identify hot spot faults and short circuit faults in a 300 W rooftop PV panel. This thesis’s focus areas are, modeling the PV panel and power converter and incorporating fault scenarios to identify the fault indicators. Multiple PV panel faults scenarios such as hot spot fault, short circuit fault, junction box fault, and capacitor fault are investigated to further deduct the effectiveness of the online impedance measurement using a small signal. Secondly, measuring PV panel impedance under normal and faulty conditions using an equipment-based offline technique. Lastly, measuring PV panel impedance under normal and faulty conditions using a power optimizer.

"A Low Noise Amplifier (LNA) is an important building block in the RF receiver chain. Typically the LNA should provide acceptable gain and high linearity while maintaining low noise and power consumption. To optimize these conflicting goals the so-called Cascode topology is widely used in industry. Here the gain cell is comprised of two transistors, one in common-source and the other in common gate configuration. Cascode has a number of competitive advantages over other topologies such as high output impedance that shields the input device from voltage variations at the output, good reverse isolation resulting in improved stability, and acceptable input matching. Moreover, the topology features excellent frequency characteristics. Unfortunately, a Cascode design is expensive to deploy in RF systems and it requires more careful tuning and matching. Since the design relies on many circuit components, optimization methods are generally difficult to implement and often inaccurate in their predictions. To overcome these problems, this thesis proposes a modeling environment within the Advanced Design Systems (ADS) simulator that utilized DC and RF measurements in an effort to characterize each transistor separately. The model creates an easy-to-apply design approach capable of predicting the most important circuit components of the Cascode topology. The validity of the method is tested in ADS with a realistic p-HEMT library device. The comparison between model prediction and the realistic device involves both standard transistor parameters and high-frequency parasitic effects. "

Recent advances in wireless communication industry, radio- frequency circuits are developing fast. For power amplifiers, the active circuits are mainly composed of transistors where withstand high voltage and current. The excellent transistors characteristic result in good circuit performances. In the thesis, the modeling of InGaAs pseudomorphic high electron mobility transistor was provided by Win Semiconductor Corporation. The established small signal model contains extrinsic and intrinsic elements. The extrinsic elements are extracted by simple method without fitting process for long time. Then, the intrinsic elements are obtained by conventional matrix transformations. The each element of models is varied with different gate width area are also discussed. Finally, the nonlinear models are expanded upon the concept of small signal model. Due to some of intrinsic elements are significantly varied with bias, small signal models have not applied to nonlinear circuit simulations. For developing nonlinear models, the nonlinear elements characteristics are described by empirical fitting equations. The accuracy of models is achieved by comparing simulated and on wafer measurement results, including DC¡Bsmall signal and large signal power characteristics.

A major issue with respect to VSC based systems is the propagation of harmonics to DC side loads due to AC voltage source unbalance. Standard dq-frame control techniques currently utilized offer little mitigation of these unwanted harmonics. Recently, resonant controllers have emerged as an alternative to dq-frame controllers for regulation of grid connected converters for distributed resources. Although these control systems behave somewhat similar to dq-frame controllers under balanced operating conditions, their behaviour under unbalanced operation is superior. Currently, there are no linearized state space models of resonant controlled VSC systems. This work will develop a linearized small signal state space model of a VSC system, where resonant current controllers are used for regulation of the grid currents. It will also investigate the stability of resonant controlled VSC based systems using eigenvalue analysis for HVDC applications.

A major issue with respect to VSC based systems is the propagation of harmonics to DC side loads due to AC voltage source unbalance. Standard dq-frame control techniques currently utilized offer little mitigation of these unwanted harmonics. Recently, resonant controllers have emerged as an alternative to dq-frame controllers for regulation of grid connected converters for distributed resources. Although these control systems behave somewhat similar to dq-frame controllers under balanced operating conditions, their behaviour under unbalanced operation is superior. Currently, there are no linearized state space models of resonant controlled VSC systems. This work will develop a linearized small signal state space model of a VSC system, where resonant current controllers are used for regulation of the grid currents. It will also investigate the stability of resonant controlled VSC based systems using eigenvalue analysis for HVDC applications.

The work presented in this thesis was undertaken to explain the differences in output powers and small-signal gain coefficients observed in cw N20 and C02 lasers. To isolate the factors limiting small-signal gain, the dynamics of conventional cw N20 laser discharges were investigated using a tunable diode laser (TDL) operating in the 2120-2350 cm-1 frequency region. Absorption measurements were made with the TDL on more than 10 different vibrational bands, allowing vibrational population distributions in the three normal modes of vibration of N20 to be determined. The vibrational populations follow a Boltzmann distribution, and the v1 and v2 mode temperatures are found to be strongly coupled, and to maintain equilibrium with the background gas temperature under all discharge conditions. It is observed that the v3 mode temperature saturates at high discharge currents. This saturation, which is attributed to electron de-excitation, is determined to be the primary factor limiting small-signal 10-μm gain in the N20 laser and is much more important than N20 dissociation. The maximum small-signal gain coefficients achievable in cw N20 lasers are calculated, and the results of the work indicates the measures that must be taken to optimize small-signal gain in the N20 laser. / Thesis / Master of Science (MSc)

Recent developments in high power rated Voltage Source Converters (VSCs) have resulted in their successful application in Multi-Terminal HVDC (MTDC) transmission systems and also have potential in the Medium Voltage DC (MVDC) distribution systems. This work presents the findings of stability studies carried out on a zonal MVDC architecture for the shipboard power distribution system. The stability study is confined to rotor angle stability of the power system, i.e. the transient and small signal stability analysis. The MTDC ring structure similar to MVDC shipboard power system was implemented in MATLAB/Simulink to look at the transient behavior of the MVDC system. Small signal stability analysis has been carried out with the help of Power System Toolbox (PST) for both MVAC as well as MVDC architectures. Later, Participation Analysis has been carried out to address the small signal instability in the case of MVAC architecture and methods for enhancement were also presented.

No description available.

The development of microwave Gallium Arsenide Metal Semiconductor Field Effect Transistor (MESFET) devices has enabled the miniaturization of pagers, cellular phones, and other electronic devices. With these MESFET devices comes the need to model them. This thesis extracts a small signal equivalent circuit model from a Gallium Arsenide MESFET device. The approach taken in this thesis is to use measured S- parameters to extract a small signal equivalent circuit model by optimization. Small signal models and S-parameters are explained. The Simplex Method is used to optimize the small signal equivalent circuit model. A thorough analysis of the strengths and weaknesses of the Simplex method is performed. / Master of Science

Power systems are extremely non-linear systems which require substantial modeling and control efforts to run continuously. The movement of the power system in parameter and state space is often not well understood, thus making it difficult or impossible to determine whether the system is nearing instability. This dissertation demonstrates several ways in which the power system stability boundary can be calculated. The power system movements evaluated here address the effects of inter-area oscillations on the system which occur in the seconds to minutes time period. The first uses gain scheduling techniques through creation of a set of linear parameter varying (LPV) systems for many operating points of the non-linear system. In the case presented, load and line reactance are used as parameters. The scheduling variables are the power flows in tie lines of the system due to the useful information they provide about the power system state in addition to being available for measurement. A linear controller is developed for the LPV model using H₂/H∞ with pole placement objectives. When the control is applied to the non-linear system, the proposed algorithm predicts the response of the non-linear system to the control by determining if the current system state is located within the domain of attraction of the equilibrium. If the stability domain contains a convex combination of the two points, the control will aid the system in moving towards the equilibrium. The second contribution of this thesis is through the development and implementation of a pseudo non-linear evaluation of a power system as it moves through state space. A system linearization occurs first to compute a multi-objective state space controller. For each contingency definition, many variations of the power system example are created and assigned to the particular contingency class. The powerflow variations and contingency controls are combined to run sets of time series analysis in which the Lyapunov function is tracked over three time steps. This data is utilized for a classification analysis which identifies and classifies the data by the contingency type. The goal is that whenever a new event occurs on the system, real time data can be fed into the trained tree to provide a control for application to increase system damping. / Ph. D.