Differential evolution based total transfer capability assessment with optimal dispatch

In this paper, a new differential evolution (DE) based power system optimal available transfer capability (ATC) assessment is presented. Power system total transfer capability (TTC) is traditionally solved by the repeated power flow (RPF) method and the continuation power flow (CPF) method. These methods are based on the assumption that the productions of the source area generators are increased in identical proportion to balance the load increment in the sink area. A new approach based on DE algorithm to generate optimal dispatch both in source area generators and sink area loads is proposed in this paper. This new method can compute ATC between two areas with significant improvement in accuracy compared with the traditional RPF and CPF based methods. A case study using a 30 bus system is given to verify the efficiency and effectiveness of this new DE based ATC optimization approach.

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.

Optimal dispatch of spinning reserve in a competitive electricity market using genetic algorithms

Ancillary service plays a key role in maintaining operation security of the power system in a competitive electricity market. The spinning reserve is one of the most important ancillary services that should be provided effectively. This paper presents the design of an integrated market for energy and spinning reserve service with particular emphasis on coordinated dispatch of bulk power and spinning reserve services. A new market dispatching mechanism has been developed to minimize the cost of service while maintaining system security. Genetic algorithms (GA) are used for finding the global optimal solutions for this dispatch problem. Case studies and corresponding analyses have been carried out to demonstrate and discuss the efficiency and usefulness of the proposed method.

Integrated power scheme simulator for human-system integration studies

We present a simulator of a hydropower company’s view of its scheme, and its broader market and network context, which has been developed to evaluate advanced displays for control room operations. Although simplified, the simulator captures all the main aspects of scheme operations. The simulator allows controlled studies to be performed that test the effectiveness of current vs advanced display concepts under normal vs unexpected operating conditions that can be scripted into the simulator.

Experimental evidence of frequency entrainment between coupled chaotic oscillations

The nonlinear response of a chaotic system to a chaotic variation in a system parameter is investigated experimentally. Clear experimental evidence of frequency entrainment of the chaotic oscillations is observed. We show that analogous to the frequency locking between coupled periodic oscillations, this effect is generic for coupled chaotic systems.

The critical power function is dependent on the duration of the predictive exercise tests chosen

The linear relationship between work accomplished (W-lim) and time to exhaustion (t(lim)) can be described by the equation: W-lim = a + CP.t(lim). Critical power (CP) is the slope of this line and is thought to represent a maximum rate of ATP synthesis without exhaustion, presumably an inherent characteristic of the aerobic energy system. The present investigation determined whether the choice of predictive tests would elicit significant differences in the estimated CP. Ten female physical education students completed, in random order and on consecutive days, five art-out predictive tests at preselected constant-power outputs. Predictive tests were performed on an electrically-braked cycle ergometer and power loadings were individually chosen so as to induce fatigue within approximately 1-10 mins. CP was derived by fitting the linear W-lim-t(lim) regression and calculated three ways: 1) using the first, third and fifth W-lim-t(lim) coordinates (I-135), 2) using coordinates from the three highest power outputs (I-123; mean t(lim) = 68-193 s) and 3) using coordinates from the lowest power outputs (I-345; mean t(lim) = 193-485 s). Repeated measures ANOVA revealed that CPI123 (201.0 +/- 37.9W) > CPI135 (176.1 +/- 27.6W) > CPI345 (164.0 +/- 22.8W) (P < 0.05). When the three sets of data were used to fit the hyperbolic Power-t(lim) regression, statistically significant differences between each CP were also found (P < 0.05). The shorter the predictive trials, the greater the slope of the W-lim-t(lim) regression; possibly because of the greater influence of 'aerobic inertia' on these trials. This may explain why CP has failed to represent a maximal, sustainable work rate. The present findings suggest that if CP is to represent the highest power output that an individual can maintain for a very long time without fatigue then CP should be calculated over a range of predictive tests in which the influence of aerobic inertia is minimised.

Identification of "pathologs" (disease-related genes) from the RIKEN mouse cDNA dataset using human curation plus FACTS, a new biological information extraction system

Background: A major goal in the post-genomic era is to identify and characterise disease susceptibility genes and to apply this knowledge to disease prevention and treatment. Rodents and humans have remarkably similar genomes and share closely related biochemical, physiological and pathological pathways. In this work we utilised the latest information on the mouse transcriptome as revealed by the RIKEN FANTOM2 project to identify novel human disease-related candidate genes. We define a new term patholog to mean a homolog of a human disease-related gene encoding a product ( transcript, anti-sense or protein) potentially relevant to disease. Rather than just focus on Mendelian inheritance, we applied the analysis to all potential pathologs regardless of their inheritance pattern. Results: Bioinformatic analysis and human curation of 60,770 RIKEN full-length mouse cDNA clones produced 2,578 sequences that showed similarity ( 70 - 85% identity) to known human-disease genes. Using a newly developed biological information extraction and annotation tool ( FACTS) in parallel with human expert analysis of 17,051 MEDLINE scientific abstracts we identified 182 novel potential pathologs. Of these, 36 were identified by computational tools only, 49 by human expert analysis only and 97 by both methods. These pathologs were related to neoplastic ( 53%), hereditary ( 24%), immunological ( 5%), cardio-vascular (4%), or other (14%), disorders. Conclusions: Large scale genome projects continue to produce a vast amount of data with potential application to the study of human disease. For this potential to be realised we need intelligent strategies for data categorisation and the ability to link sequence data with relevant literature. This paper demonstrates the power of combining human expert annotation with FACTS, a newly developed bioinformatics tool, to identify novel pathologs from within large-scale mouse transcript datasets.

Effect of power Doppler and digital subtraction techniques on the comparison of myocardial contrast echocardiography with SPECT

Objective-To compare the accuracy and feasibility of harmonic power Doppler and digitally subtracted colour coded grey scale imaging for the assessment of perfusion defect severity by single photon emission computed tomography (SPECT) in an unselected group of patients. Design-Cohort study. Setting-Regional cardiothoracic unit. Patients-49 patients (mean (SD) age 61 (11) years; 27 women, 22 men) with known or suspected coronary artery disease were studied with simultaneous myocardial contrast echo (MCE) and SPECT after standard dipyridamole stress. Main outcome measures-Regional myocardial perfusion by SPECT, performed with Tc-99m tetrafosmin, scored qualitatively and also quantitated as per cent maximum activity. Results-Normal perfusion was identified by SPECT in 225 of 270 segments (83%). Contrast echo images were interpretable in 92% of patients. The proportion of normal MCE by grey scale, subtracted, and power Doppler techniques were respectively 76%, 74%, and 88% (p < 0.05) at > 80% of maximum counts, compared with 65%, 69%, and 61% at < 60% of maximum counts. For each technique, specificity was lowest in the lateral wail, although power Doppler was the least affected. Grey scale and subtraction techniques were least accurate in the septal wall, but power Doppler showed particular problems in the apex. On a per patient analysis, the sensitivity was 67%, 75%, and 83% for detection of coronary artery disease using grey scale, colour coded, and power Doppler, respectively, with a significant difference between power Doppler and grey scale only (p < 0.05). Specificity was also the highest for power Doppler, at 55%, but not significantly different from subtracted colour coded images. Conclusions-Myocardial contrast echo using harmonic power Doppler has greater accuracy than with grey scale imaging and digital subtraction. However, power Doppler appears to be less sensitive for mild perfusion defects.