Assessing the competitiveness of loss allocation methods in a deregulated electricity market

This paper critically assesses several loss allocation methods based on the type of competition each method promotes. This understanding assists in determining which method will promote more efficient network operations when implemented in deregulated electricity industries. The methods addressed in this paper include the pro rata [1], proportional sharing [2], loss formula [3], incremental [4], and a new method proposed by the authors of this paper, which is loop-based [5]. These methods are tested on a modified Nordic 32-bus network, where different case studies of different operating points are investigated. The varying results obtained for each allocation method at different operating points make it possible to distinguish methods that promote unhealthy competition from those that encourage better system operation.

Calculation of line integrals in boundary integral methods

We propose quadrature rules for the approximation of line integrals possessing logarithmic singularities and show their convergence. In some instances a superconvergence rate is demonstrated.

Turbulence in Small Sub-Tropical Estuary with Semi-Diurnal Tides

In natural estuaries, contaminant transport is driven by the turbulent momentum mixing. The predictions of scalar dispersion can rarely be predicted accurately because of a lack of fundamental understanding of the turbulence structure in estuaries. Herein detailed turbulence field measurements were conducted at high frequency and continuously for up to 50 hours per investigation in a small subtropical estuary with semi-diurnal tides. Acoustic Doppler velocimetry was deemed the most appropriate measurement technique for such small estuarine systems with shallow water depths (less than 0.5 m at low tides), and a thorough post-processing technique was applied. The estuarine flow is always a fluctuating process. The bulk flow parameters fluctuated with periods comparable to tidal cycles and other large-scale processes. But turbulence properties depended upon the instantaneous local flow properties. They were little affected by the flow history, but their structure and temporal variability were influenced by a variety of mechanisms. This resulted in behaviour which deviated from that for equilibrium turbulent boundary layer induced by velocity shear only. A striking feature of the data sets is the large fluctuations in all turbulence characteristics during the tidal cycle. This feature was rarely documented, but an important difference between the data sets used in this study from earlier reported measurements is that the present data were collected continuously at high frequency during relatively long periods. The findings bring new lights in the fluctuating nature of momentum exchange coefficients and integral time and length scales. These turbulent properties should not be assumed constant.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

A framework for electricity price spike analysis with advanced data mining methods

There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.

A demonstration of artificial dissipation effects in some finite volume solution methods for the Navier-Stokes equations

The artificial dissipation effects in some solutions obtained with a Navier-Stokes flow solver are demonstrated. The solvers were used to calculate the flow of an artificially dissipative fluid, which is a fluid having dissipative properties which arise entirely from the solution method itself. This was done by setting the viscosity and heat conduction coefficients in the Navier-Stokes solvers to zero everywhere inside the flow, while at the same time applying the usual no-slip and thermal conducting boundary conditions at solid boundaries. An artificially dissipative flow solution is found where the dissipation depends entirely on the solver itself. If the difference between the solutions obtained with the viscosity and thermal conductivity set to zero and their correct values is small, it is clear that the artificial dissipation is dominating and the solutions are unreliable.

A shift from passive teaching at medical conferences to more interactive methods improves physician learning

Conferences that deliver interactive sessions designed to enhance physician participation, such as role play, small discussion groups, workshops, hands-on training, problem- or case-based learning and individualised training sessions, are effective for physician education.

Appropriate surveying methods in the Philippines: Can modern GPS units help?

An investigation was undertaken to test the effectiveness of two procedures for recording boundaries and plot positions for scientific studies on farms on Leyte Island, the Philippines. The accuracy of a Garmin 76 Global Positioning System (GPS) unit and a compass and chain was checked under the same conditions. Tree canopies interfered with the ability of the satellite signal to reach the GPS and therefore the GPS survey was less accurate than the compass and chain survey. Where a high degree of accuracy is required, a compass and chain survey remains the most effective method of surveying land underneath tree canopies, providing operator error is minimised. For a large number of surveys and thus large amounts of data, a GPS is more appropriate than a compass and chain survey because data are easily up-loaded into a Geographic Information System (GIS). However, under dense canopies where satellite signals cannot reach the GPS, it may be necessary to revert to a compass survey or a combination of both methods.

Improved methods for predicting individual leaf area and leaf senescence in maize (Zea mays)

The ability to predict leaf area and leaf area index is crucial in crop simulation models that predict crop growth and yield. Previous studies have shown existing methods of predicting leaf area to be inadequate when applied to a broad range of cultivars with different numbers of leaves. The objectives of the study were to (i) develop generalised methods of modelling individual and total plant leaf area, and leaf senescence, that do not require constants that are specific to environments and/or genotypes, (ii) re-examine the base, optimum, and maximum temperatures for calculation of thermal time for leaf senescence, and (iii) assess the method of calculation of individual leaf area from leaf length and leaf width in experimental work. Five cultivars of maize differing widely in maturity and adaptation were planted in October 1994 in south-eastern Queensland, and grown under non-limiting conditions of water and plant nutrient supplies. Additional data for maize plants with low total leaf number (12-17) grown at Katumani Research Centre, Kenya, were included to extend the range in the total leaf number per plant. The equation for the modified (slightly skewed) bell curve could be generalised for modelling individual leaf area, as all coefficients in it were related to total leaf number. Use of coefficients for individual genotypes can be avoided, and individual and total plant leaf area can be calculated from total leaf number. A single, logistic equation, relying on maximum plant leaf area and thermal time from emergence, was developed to predict leaf senescence. The base, optimum, and maximum temperatures for calculation of thermal time for leaf senescence were 8, 34, and 40 degrees C, and apply for the whole crop-cycle when used in modelling of leaf senescence. Thus, the modelling of leaf production and senescence is simplified, improved, and generalised. Consequently, the modelling of leaf area index (LAI) and variables that rely on LAI will be improved. For experimental purposes, we found that the calculation of leaf area from leaf length and leaf width remains appropriate, though the relationship differed slightly from previously published equations.

Synthesis, NMR studies and conformational analysis of oxazolidine derivatives of the beta-adrenoreceptor antagonists metoprolol, atenolol and timolol

Formaldehyde-derived oxazolidine derivatives 4-7 of the beta-adrenoreceptor antagonists metoprolol 1, atenolol 2 and timolol 3 have been synthesised. Conformational analysis of 1-3 and the oxazolidine derivatives 4-7 has been performed using H-1 NMR spectroscopy and computational methods. The H-1 NMR studies show that for the aryloxypropanolamine beta-adrenoreceptor antagonists there is a predominance of the conformer in which the amine group is approximately antiperiplanar or trans to the aryloxymethylene group. Both H-1 NMR data and theoretical studies indicate that the oxazolidine derivatives 4-7 and the aryloxypropanolamine beta-adrenoreceptor antagonists 1-3 adopt similar conformations around the beta-amino alcohol moiety. Thus, oxazolidine ring formation does not dramatically alter the preferred conformation adopted by the beta-amino alcohol moiety of 1-3. Oxazolidine derivatives of aryloxypropanolamine beta-adrenoreceptor antagonists may therefore be appropriate as prodrugs, or semi-rigid analogues, when greater lipophilicity is required for drug delivery.

Ester prodrugs of a potent analgesic, morphine-6-sulfate: syntheses, spectroscopic and physicochemical properties

The aim of this work is to develop 3-acyl prodrugs of the potent analgesic morphine-6-sulfate (M6S). These are expected to have higher potency and/or exhibit longer duration of analgesic action than the parent compound. M6S and the prodrugs were synthesized, then purified either by recrystallization or by semi-preparative HPLC and the structures confirmed by mass spectrometry, IR spectrophotometry and by detailed 1- and 2-D NMR studies. The lipophilicities of the compounds were assessed by a combination of shake-flask, group contribution and HPLC retention methods. The octanol-buffer partition coefficient could only be obtained directly for 3-heptanoylmorphine-6-sulfate, using the shake-flask method. The partition coefficients (P) for the remaining prodrugs were estimated from known methylene group contributions. A good linear relationship between log P and the HPLC log capacity factors was demonstrated. Hydrolysis of the 3-acetyl prodrug, as a representative of the group, was found to occur relatively slowly in buffers (pH range 6.15-8.01), with a small buffer catalysis contribution. The rates of enzymatic hydrolysis of the 3-acyl group in 10% rat blood and in 10% rat brain homogenate were investigated. The prodrugs followed apparent first order hydrolysis kinetics, with a significantly faster hydrolysis rate found in 10% rat brain homogenate than in 10% rat blood for all compounds. (C) 1998 Elsevier Science B.V. All rights reserved.