Simplified small-signal stability analysis for optimized power system architecture

The optimization of power architectures is a complex problem due to the plethora of different ways to connect various system components. This issue has been addressed by developing a methodology to design and optimize power architectures in terms of the most fundamental system features: size, cost and efficiency. The process assumes various simplifications regarding the utilized DC/DC converter models in order to prevent the simulation time to become excessive and, therefore, stability is not considered. The objective of this paper is to present a simplified method to analyze small-signal stability of a system in order to integrate it into the optimization methodology. A black-box modeling approach, applicable to commercial converters with unknown topology and components, is based on frequency response measurements enabling the system small-signal stability assessment. The applicability of passivity-based stability criterion is assessed. The stability margins are stated utilizing a concept of maximum peak criteria derived from the behavior of the impedance-based sensitivity function that provides a single number to state the robustness of the stability of a well-defined minor-loop gain.

Systematic Method to Assess Small-Signal Stability of DC-Distributed Power-System-Architecture

The objective of this paper is to present a simplified method to analyze small-signal stability of a power system and provide performance metrics for stability assessment of a given power-system-architecture. The stability margins are stated utilizing a concept of maximum peak criteria (MPC), derived from the behavior of an impedance-based sensitivity function that provides a single number to state the robustness of the stability of a well-defined minor-loop gain. For each minor-loop gain, defined at every system interface, the robustness of the stability is provided as a maximum value of the corresponding sensitivity function. Typically power systems comprise of various interfaces and, therefore, in order to compare different architecture solutions in terms of stability, a single number providing an overall measure of the whole system stability is required. The selected figure of merit is geometric average of each maximum peak value within the system, combined with the worst case value of system interfaces.

Pile transfer functions.

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Characteristics of small-signal capacitances of silicon-on-sapphire MOSFETs

The measured inter-electrode capacitances of silicon-on-sapphire (SOS) MOSFETs are presented and compared with simulation results. It is shown that the variations of capacitances with DC bias differ from those of bulk MOSFETs due to change in body potential variation of the SOS device resulting from electron-hole pair generation through impact ionisation.

Power system sensitivity analysis for probabilistic small signal stability assessment in a deregulated environment

Deregulations and market practices in power industry have brought great challenges to the system planning area. In particular, they introduce a variety of uncertainties to system planning. New techniques are required to cope with such uncertainties. As a promising approach, probabilistic methods are attracting more and more attentions by system planners. In small signal stability analysis, generation control parameters play an important role in determining the stability margin. The objective of this paper is to investigate power system state matrix sensitivity characteristics with respect to system parameter uncertainties with analytical and numerical approaches and to identify those parameters have great impact on system eigenvalues, therefore, the system stability properties. Those identified parameter variations need to be investigated with priority. The results can be used to help Regional Transmission Organizations (RTOs) and Independent System Operators (ISOs) perform planning studies under the open access environment.

Eigenvalue sensitivity analysis for probabilistic small signal stability assessment

This paper presents a method to analyze the first order eigenvalue sensitivity with respect to the operating parameters of a power system. The method is based on explicitly expressing the system state matrix into sub-matrices. The eigenvalue sensitivity is calculated based on the explicitly formed system state matrix. The 4th order generator model and 4th order exciter system model are used to form the system state matrix. A case study using New England 10-machine 39-bus system is provided to demonstrate the effectiveness of the proposed method. This method can be applied into large scale power system eigenvalue sensitivity with respect to operating parameters.

A novel grid computing approach for probabilistic small signal analysis

Grid computing is an advanced technique for collaboratively solving complicated scientific problems using geographically and organisational dispersed computational, data storage and other recourses. Application of grid computing could provide significant benefits to all aspects of power system that involves using computers. Based on our previous research, this paper presents a novel grid computing approach for probabilistic small signal stability (PSSS) analysis in electric power systems with uncertainties. A prototype computing grid is successfully implemented in our research lab to carry out PSSS analysis on two benchmark systems. Comparing to traditional computing techniques, the gird computing has given better performances for PSSS analysis in terms of computing capacity, speed, accuracy and stability. In addition, a computing grid framework for power system analysis has been proposed based on the recent study.

Spatial contrast sensitivity and external noise: applications to optical and neural modulation transfer functions

The thesis will show how to equalise the effect of quantal noise across spatial frequencies by keeping the retinal flux (If-2) constant. In addition, quantal noise is used to study the effect of grating area and spatial frequency on contrast sensitivity resulting in the extension of the new contrast detection model describing the human contrast detection system as a simple image processor. According to the model the human contrast detection system comprises low-pass filtering due to ocular optics, addition of light dependent noise at the event of quantal absorption, high-pass filtering due to the neural visual pathways, addition of internal neural noise, after which detection takes place by a local matched filter, whose sampling efficiency decreases as grating area is increased. Furthermore, this work will demonstrate how to extract both the optical and neural modulation transfer functions of the human eye. The neural transfer function is found to be proportional to spatial frequency up to the local cut-off frequency at eccentricities of 0 - 37 deg across the visual field. The optical transfer function of the human eye is proposed to be more affected by the Stiles-Crawford -effect than generally assumed in the literature. Similarly, this work questions the prevailing ideas about the factors limiting peripheral vision by showing that peripheral optical acts as a low-pass filter in normal viewing conditions, and therefore the effect of peripheral optics is worse than generally assumed.

Small-signal input admittance characteristics of a brushless DC motor drive

To carry out stability studies on more electric systems in which there is a preponderance of motor drive equipment, input admittance expressions are required for the individual pieces of equipment. In this paper the techniques of averaging and small-signal linearisation will be used to derive a simple input admittance model for a low voltage, trapezoidal back EMF, brushless, DC motor drive system.

Rational Function Interpolation of Electromagnetic Transfer Functions of High-Speed Interconnect Systems from Discrete Time-Domain and Frequency-Domain Data

We present new methodologies to generate rational function approximations of broadband electromagnetic responses of linear and passive networks of high-speed interconnects, and to construct SPICE-compatible, equivalent circuit representations of the generated rational functions. These new methodologies are driven by the desire to improve the computational efficiency of the rational function fitting process, and to ensure enhanced accuracy of the generated rational function interpolation and its equivalent circuit representation. Toward this goal, we propose two new methodologies for rational function approximation of high-speed interconnect network responses. The first one relies on the use of both time-domain and frequency-domain data, obtained either through measurement or numerical simulation, to generate a rational function representation that extrapolates the input, early-time transient response data to late-time response while at the same time providing a means to both interpolate and extrapolate the used frequency-domain data. The aforementioned hybrid methodology can be considered as a generalization of the frequency-domain rational function fitting utilizing frequency-domain response data only, and the time-domain rational function fitting utilizing transient response data only. In this context, a guideline is proposed for estimating the order of the rational function approximation from transient data. The availability of such an estimate expedites the time-domain rational function fitting process. The second approach relies on the extraction of the delay associated with causal electromagnetic responses of interconnect systems to provide for a more stable rational function process utilizing a lower-order rational function interpolation. A distinctive feature of the proposed methodology is its utilization of scattering parameters. For both methodologies, the approach of fitting the electromagnetic network matrix one element at a time is applied. It is shown that, with regard to the computational cost of the rational function fitting process, such an element-by-element rational function fitting is more advantageous than full matrix fitting for systems with a large number of ports. Despite the disadvantage that different sets of poles are used in the rational function of different elements in the network matrix, such an approach provides for improved accuracy in the fitting of network matrices of systems characterized by both strongly coupled and weakly coupled ports. Finally, in order to provide a means for enforcing passivity in the adopted element-by-element rational function fitting approach, the methodology for passivity enforcement via quadratic programming is modified appropriately for this purpose and demonstrated in the context of element-by-element rational function fitting of the admittance matrix of an electromagnetic multiport.