TCSC control design for transient stability improvement of a multi-machine power system using trajectory sensitivity

This paper discusses the effects of thyristor controlled series compensator (TCSC), a series FACTS controller, on the transient stability of a power system. Trajectory sensitivity analysis (TSA) has been used to measure the transient stability condition of the system. The TCSC is modeled by a variable capacitor, the value of which changes with the firing angle. It is shown that TSA can be used in the design of the controller. The optimal locations of the TCSC-controller for different fault conditions can also be identified with the help of TSA. The paper depicts the advantage of the use of TCSC with a suitable controller over fixed capacitor operation.

Governance in the Australian superannuation industry

In the Superannuation/Pension industry ordinary investors entrust their retirement savings to the trustees of the superannuation plan. Investors rely on the trustees to ensure ethical business and risk management practices are implemented to protect their retirement savings. Governance practices ensure the monitoring of ethical risk management (Drennan, 2004). The Australian superannuation industry presents a unique scenario. Legislation requires employers to contribute a minimum of 9% of the employees wage to retirement savings. However, there are no legislated governance standards, although there are standards of recommended governance practices. In this paper, we examine the level of voluntary adoption of governance practices by the trustees of Australian public sector and industry superannuation funds. We also assess whether superannuation governance practices are associated with performance and volatility/riskiness of returns. Survey results show that the majority of superannuation plans adopt recommended governance practices supporting the concept of ethical management of the member’s retirement savings. The examination of governance principles that impact returns and risk show that board size and regular review of conflicts are positively associated with return. Superannuation plans with higher volatility in returns meet more frequently.

The application of neural networks to induction machine control

Neural networks (NNs) are discussed in connection with their possible use in induction machine drives. The mathematical model of the NN as well as a commonly used learning algorithm is presented. Possible applications of NNs to induction machine control are discussed. A simulation of an NN successfully identifying the nonlinear multivariable model of an induction-machine stator transfer function is presented. Previously published applications are discussed, and some possible future applications are proposed.

Identification and control of induction machines using artificial neural networks

The use of artificial neural networks (ANNs) to identify and control induction machines is proposed. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics, and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Both systems are inherently adaptive as well as self-commissioning. The current controller is a completely general nonlinear controller which can be used together with any drive algorithm. Various advantages of these control schemes over conventional schemes are cited, and the combined speed and current control scheme is compared with the standard vector control scheme

Identification and control of induction machines using artificial neural networks

This paper proposes the use of artificial neural networks (ANNs) to identify and control an induction machine. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics; and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Various advantages of these control schemes over other conventional schemes are cited and the performance of the combined speed and current control scheme is compared with that of the standard vector control scheme

Vector control of a high power induction machine

The design and implementation of a high-power (2 MW peak) vector control drive is described. The inverter switching frequency is low, resulting in high-harmonic-content current waveforms. A block diagram of the physical system is given, and each component is described in some detail. The problem of commanded slip noise sensitivity, inherent in high-power vector control drives, is discussed, and a solution is proposed. Results are given which demonstrate the successful functioning of the system

Invention and business performance in the tissue-engineering industry

Tissue engineering is a young and interdisciplinary scientific discipline but it offers exciting opportunities to improve the quality of health care for hundreds of thousands of patients. Lured by its potential, several start-up companies, pharmaceutical corporations, and medical device enterprises alike are investing heavily in this sector. Invention is a key driver of competition in this sector. In this study, we aim to explain the variation in inventive output across the different firms in the sector. Our major premise is that firms that forge alliances will be able to tap into the expertise of their partners and thus improve their chances of inventive output. We further argue that alliances that enable technology acquisition or learning will enhance the inventive output of firms more than other kinds of alliances. We measure the inventive output of a company by the number of patents filed. On the basis of a preliminary analysis of seven companies, we find support for the hypotheses. We also argue that, to achieve commercial success, firms need to manage time to market (through alliances or otherwise), have a global outlook, nurture their financial resources, and attain critical mass through mergers.