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.

Comparison of BR and QR Eigenvalue Algorithms for Power System Small Signal Stability Analysis

The BR algorithm is a novel and efficient method to find all eigenvalues of upper Hessenberg matrices and has never been applied to eigenanalysis for power system small signal stability. This paper analyzes differences between the BR and the QR algorithms with performance comparison in terms of CPU time based on stopping criteria and storage requirement. The BR algorithm utilizes accelerating strategies to improve its performance when computing eigenvalues of narrowly banded, nearly tridiagonal upper Hessenberg matrices. These strategies significantly reduce the computation time at a reasonable level of precision. Compared with the QR algorithm, the BR algorithm requires fewer iteration steps and less storage space without depriving of appropriate precision in solving eigenvalue problems of large-scale power systems. Numerical examples demonstrate the efficiency of the BR algorithm in pursuing eigenanalysis tasks of 39-, 68-, 115-, 300-, and 600-bus systems. Experiment results suggest that the BR algorithm is a more efficient algorithm for large-scale power system small signal stability eigenanalysis.

Thermal stability analysis of organo-silicates, using solid phase microextraction techniques

An analysis of thermal degradation products evolved during the melt processing of organo-layered silicates (OLS) was carried out via the use of a solid phase microextraction (SPME) technique. Two commerical OLSs and one produced in-house were prepared for comparision. The solid phase microextraction technique proved to be a very effective technique for investigating the degradation of the OLS at a specific processing temperature. The results showed that most available OLSs will degrade under typical conditions required for the melt processing of many polymers, including thermoplastic polyurethanes. It is suggested that these degradation products may lead to changes in the structure and properties of the final polymer, particularly in thermoplastic polyurethanes, which seem significantly succeptable to the presence of these products. It is also suggested that many commercially available OLSs are produced in such a way that results in an excess of unbound organic modifier, giving rise to a greater quantity of degradation products. All OLSs where compared and characterised by TGA and GC-MS. (c) 2004 Elsevier B.V. All rights reserved.

Hydrothermal Stability Analysis of Carbonised Template Molecular Sieve Silica Membranes

For fuel cell CO clean up application, the presence of water with silica membranes greatly reduces their selectivity to CO. We show results of a new functional carbonised template membrane of around 13nm thickness which offered hydrothermal stability with no compromise to the membrane’s H2/CO permselectivity of 16. Lost permeance was also regenerated.

Clustering Process Analysis in a Large-Size Dropshaft and in a Hydraulic Jump

Recent efforts in the characterization of air-water flows properties have included some clustering process analysis. A cluster of bubbles is defined as a group of two or more bubbles, with a distinct separation from other bubbles before and after the cluster. The present paper compares the results of clustering processes two hydraulic structures. That is, a large-size dropshaft and a hydraulic jump in a rectangular horizontal channel. The comparison highlighted some significant differences in clustering production and structures. Both dropshaft and hydraulic jump flows are complex turbulent shear flows, and some clustering index may provide some measure of the bubble-turbulence interactions and associated energy dissipation.

Data analysis in multiple-frequency bioelectrical impedance analysis

The performance of three analytical methods for multiple-frequency bioelectrical impedance analysis (MFBIA) data was assessed. The methods were the established method of Cole and Cole, the newly proposed method of Siconolfi and co-workers and a modification of this procedure. Method performance was assessed from the adequacy of the curve fitting techniques, as judged by the correlation coefficient and standard error of the estimate, and the accuracy of the different methods in determining the theoretical values of impedance parameters describing a set of model electrical circuits. The experimental data were well fitted by all curve-fitting procedures (r = 0.9 with SEE 0.3 to 3.5% or better for most circuit-procedure combinations). Cole-Cole modelling provided the most accurate estimates of circuit impedance values, generally within 1-2% of the theoretical values, followed by the Siconolfi procedure using a sixth-order polynomial regression (1-6% variation). None of the methods, however, accurately estimated circuit parameters when the measured impedances were low (<20 Omega) reflecting the electronic limits of the impedance meter used. These data suggest that Cole-Cole modelling remains the preferred method for the analysis of MFBIA data.

Parallel processing and image analysis in the eyes of mantis shrimps

The compound eyes of mantis shrimps, a group of tropical marine crustaceans, incorporate principles of serial and parallel processing of visual information that may be applicable to artificial imaging systems. Their eyes include numerous specializations for analysis of the spectral and polarizational properties of light, and include more photoreceptor classes for analysis of ultraviolet light, color, and polarization than occur in any other known visual system. This is possible because receptors in different regions of the eye are anatomically diverse and incorporate unusual structural features, such as spectral filters, not seen in other compound eyes. Unlike eyes of most other animals, eyes of mantis shrimps must move to acquire some types of visual information and to integrate color and polarization with spatial vision. Information leaving the retina appears to be processed into numerous parallel data streams leading into the central nervous system, greatly reducing the analytical requirements at higher levels. Many of these unusual features of mantis shrimp vision may inspire new sensor designs for machine vision

A comparison of low-storage strategies for spectral analysis in dissipative systems: filter diagonalisation in the Lanczos representation and harmonic inversion of the Chebychev-order-domain autocorrelation function

We compare the performance of two different low-storage filter diagonalisation (LSFD) strategies in the calculation of complex resonance energies of the HO2, radical. The first is carried out within a complex-symmetric Lanczos subspace representation [H. Zhang, S.C. Smith, Phys. Chem. Chem. Phys. 3 (2001) 2281]. The second involves harmonic inversion of a real autocorrelation function obtained via a damped Chebychev recursion [V.A. Mandelshtam, H.S. Taylor, J. Chem. Phys. 107 (1997) 6756]. We find that while the Chebychev approach has the advantage of utilizing real algebra in the time-consuming process of generating the vector recursion, the Lanczos, method (using complex vectors) requires fewer iterations, especially for low-energy part of the spectrum. The overall efficiency in calculating resonances for these two methods is comparable for this challenging system. (C) 2001 Elsevier Science B.V. All rights reserved.

Estimation of total body water from bioelectrical impedance analysis in patients with pancreatic cancer - agreement between three methods of prediction

Introduction Bioelectrical impedance analysis (BIA) is a useful field measure to estimate total body water (TBW). No prediction formulae have been developed or validated against a reference method in patients with pancreatic cancer. The aim of this study was to assess the agreement between three prediction equations for the estimation of TBW in cachectic patients with pancreatic cancer. Methods Resistance was measured at frequencies of 50 and 200 kHz in 18 outpatients (10 males and eight females, age 70.2 +/- 11.8 years) with pancreatic cancer from two tertiary Australian hospitals. Three published prediction formulae were used to calculate TBW - TBWs developed in surgical patients, TBWca-uw and TBWca-nw developed in underweight and normal weight patients with end-stage cancer. Results There was no significant difference in the TBW estimated by the three prediction equations - TBWs 32.9 +/- 8.3 L, TBWca-nw 36.3 +/- 7.4 L, TBWca-uw 34.6 +/- 7.6 L. At a population level, there is agreement between prediction of TBW in patients with pancreatic cancer estimated from the three equations. The best combination of low bias and narrow limits of agreement was observed when TBW was estimated from the equation developed in the underweight cancer patients relative to the normal weight cancer patients. When no established BIA prediction equation exists, practitioners should utilize an equation developed in a population with similar critical characteristics such as diagnosis, weight loss, body mass index and/or age. Conclusions Further research is required to determine the accuracy of the BIA prediction technique against a reference method in patients with pancreatic cancer.

Application of ICP-MS trace element analysis in study of ancient Chinese ceramics

Thirty-nine trace elements of the Song-Yuan period (960-1368 AD) porcelain bodies from Cizhou, Jizhou and Longquanwu kilns were analyzed with ICP-MS, a technique rarely used in Chinese archaeometry, to investigate its potential application in such studies. Trace element compositions clearly reflect the distinctive raw materials and their mineralogy at the three kilns and allow their products to be distinguished. Significant chemical variations are also observed between Yuan and Song-Jing dynasties samples from Cizhou as well as fine and coarse porcelain bodies from Longquanwu. In Cizhou, porcelains of better quality which imitate the famous Ding kiln have trace element features distinctive from ordinary Cizhou products, that indicates geochemically distinctive raw materials were used and which possibly also underwent extra refining prior to use. The distinct trace element features of different kilns and the various types of porcelains from an individual kiln can be interpreted from a geochemical perspective. ICP-MS can provide a large amount of valuable information about ancient Chinese ceramics as it is capable of analyzing >40 elements with a typical of precision < 2%.

Core stability exercise in chronic low back pain

Exercise is commonly used in the management of chronic musculoskeletal conditions, including chronic low back pain (CLBP). The focus of exercise is varied and may include parameters ranging from strength and endurance training, to specific training of muscle coordination and control. The assumption underpinning these approaches is that improved neuromuscular function will restore or augment the control and support of the spine and pelvis. In a biomechanical model of CLBP, which assumes that pain recurrence is caused by repeated mechanical irritation of pain sensitive structures [1], it is proposed that this improved control and stability would reduce mechanical irritation and lead to pain relief [1]. Although this model provides explanation for the chronicity of LBP, perpetuation of pain is more complex, and contemporary neuroscience holds the view that chronic pain is mediated by a range of changes including both peripheral (eg, peripheral sensitization) and central neuroplastic changes [2]. Although this does not exclude the role of improved control of the lumbar spine and pelvis in management of CLBP, particularly when there is peripheral sensitization, it highlights the need to look beyond outdated simplistic models. One factor that this information highlights is that the refinement of control and coordination may be more important than simple strength and endurance training for the trunk muscles. The objective of this article is to discuss the rationale for core stability exercise in the management of CLBP, to consider critical factors for its implementation, and to review evidence for efficacy of the approach.