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.

High throughput analysis of endogenous glutamate release using a fluorescence plate reader

Recent discoveries of different modes of exocytosis and a plethora of molecules involved in neurotransmitter release has resulted in demand for more rapid and efficient methods for monitoring endogenous glutamate release from various tissue sources. In this article, we describe a high throughput microplate version of the enzyme-linked fluorescence detection method for the measurement of released glutamate, which utilises glutamate dehydrogenase, and the reduction of NADP to NADPH. Previous versions of this method rely upon cuvette-based fluorimeters for detection that are limited by large sample volumes and small numbers of samples that can be measured simultaneously. Comparison between the two methods shows that the microplate assay has comparable performance to the cuvette-based assay but has the capacity to analyse many times more samples in a given run. This increased capacity provides improved experimental design opportunities, higher experimental throughput and better comparison between experimental conditions. (c) 2005 Elsevier B.V. All rights reserved.

Causality detection on US mutual fund movements using evolutionary subset time-series

In this paper we develop an evolutionary kernel-based time update algorithm to recursively estimate subset discrete lag models (including fullorder models) with a forgetting factor and a constant term, using the exactwindowed case. The algorithm applies to causality detection when the true relationship occurs with a continuous or a random delay. We then demonstrate the use of the proposed evolutionary algorithm to study the monthly mutual fund data, which come from the 'CRSP Survivor-bias free US Mutual Fund Database'. The results show that the NAV is an influential player on the international stage of global bond and stock markets.

Is there a case for low inflation-induced productivity growth in selected Asian economies?

The authors examine the evidence on the relationship between inflation and productivity growth for nine Asian economies using causality analysis in a multivariate model with money supply as a possible effective monetary policy tool. The inflation-productivity growth relationship is found to be non-uniform, as the evidence of uni-directional, bi-directional, and no causality between the two variables is varied and significant for some countries and insignificant for others. An attempt is made to explain the inflation-productivity nexus for these countries and to discuss implications for anti-inflationary policies such as inflation targeting.

Knowledge about a Species' Conservation Status and Funding for its Preservation: Analysis

Using a species' population to measure its conservation status, this paper explores how increased knowledge about a species' status changes the public's willingness to donate funds for its conservation. This is based on the behavioral relationship between the level of donations and a species' conservation status satisfying general mathematical properties. This level of donation increases, on average, with greater knowledge of a species' conservation status if it is endangered, but falls if it is secure. Modelling enables individuals' demand for extra information about the conservation status of species to be specified. While this model may suggest that conservation bodies could boost funds for conservation of species by exaggerating species' endangerment, such a strategy is shown to be potentially counterproductive. (c) 2006 Elsevier B.V. All rights reserved.

The status and relevance of Vietnamese journalism education: An empirical analysis

Based primarily on data from indepth interviews with senior journalists and journalism educators as well as a content analysis of journalism curricula, this paper sets out to provide an overview of the demand, overall provision structure, teaching materials and methods of Vietnamese journalism education. It first shows that with a fast expansion in both size and substance, the Vietnamese media system is beginning to feel the urgent need for formal journalism education. However, the country's major journalism programs have been criticised for producing hundreds of unqualified journalism graduates a year. In general, the most deplorable aspects of Vietnamese journalism education include its body of outdated and awkward teaching material, its undue focus on theories and politics at the expense of practical training, its lack of qualified teaching staff and its inadequate teaching resources.

An automated failure mode and effect analysis based on high-level design specificication with behavior trees

Formal methods have significant benefits for developing safety critical systems, in that they allow for correctness proofs, model checking safety and liveness properties, deadlock checking, etc. However, formal methods do not scale very well and demand specialist skills, when developing real-world systems. For these reasons, development and analysis of large-scale safety critical systems will require effective integration of formal and informal methods. In this paper, we use such an integrative approach to automate Failure Modes and Effects Analysis (FMEA), a widely used system safety analysis technique, using a high-level graphical modelling notation (Behavior Trees) and model checking. We inject component failure modes into the Behavior Trees and translate the resulting Behavior Trees to SAL code. This enables us to model check if the system in the presence of these faults satisfies its safety properties, specified by temporal logic formulas. The benefit of this process is tool support that automates the tedious and error-prone aspects of FMEA.

A new methodology for generation investment in the national electricity market of Australia

Market administrators hold the vital role of maintaining sufficient generation capacity in their respective electricity market. However without the jurisdiction to dictate the generator types, locations and timing of new generation, the reliability of the system may be compromised by delayed entry of new generation. This paper illustrates a new generation investment methodology that can effectively present expected returns from the pool market; while concurrently searching for the type and placement of a new generator to fulfil system reliability requirements.

A genetic algorithm based method for deregulated electricity market dispatch

In a deregulated electricity market, optimizing dispatch capacity and transmission capacity are among the core concerns of market operators. Many market operators have capitalized on linear programming (LP) based methods to perform market dispatch operation in order to explore the computational efficiency of LP. In this paper, the search capability of genetic algorithms (GAs) is utilized to solve the market dispatch problem. The GA model is able to solve pool based capacity dispatch, while optimizing the interconnector transmission capacity. Case studies and corresponding analyses are performed to demonstrate the efficiency of the GA model.