An overview of out-of-step protection in power systems

Power system is subjected to an extensive variety of little or bigger disturbance to the system during the operation. The power system that designed as one of the main requirement is to survive from the larger type of disturbances like faults. The power swing in certain system is the variation in three phase power flow in the power system. This paper mainly discussed the power swing and distance relay and the effect of the power swing on the distance relay and demonstrate about the basic power system stability and power swing phenomena. Moreover, out of step protection and detection applications are revised as well. At the end, the paper also demonstrated the past study of out of step application of TNB 275 KV network

Harmonic Reduction of a Single-Phase Multilevel Inverter Using Genetic Algorithm and Particle Swarm Optimization

Power inverter play an important role in power system especially with its capability on reducing system size and increase efficiently. The recent research trends of power electronic system are focusing on multilevel inverter topics in optimization on voltage output, reducing the total harmonics distortion, modulation technique, and switching configuration. The research emphasizes the optimization with a fundamental switching frequency method that is the optimized harmonic stepped waveform (OHSW) modulation method. The selective harmonic elimination (SHE) calculation has adapted with genetic algorithm (GA) and particle swarm optimization (PSO) in order to speed up the calculation. Both bioinspired algorithms are compared in terms of total harmonic distortion (THD) and selective harmonic elimination for both equal and unequal sources. The overall result showed that both algorithms have high accuracy in solving the nonlinear equation. However, the genetic algorithm showed better output quality in terms of selective harmonic elimination which overall no exceeding 0.4%. Particle swarm optimization shows strength in finding the best total harmonic distortion where in seven-level cascaded H-bridge multilevel inverter (m=0.8) shows 6.8% only as compared to genetic algorithm. Simulation for three-level, five-level, and seven-level for each multilevel inverter at different circumferences had been done in this research. The result draws out a conclusion where the possibility of having a filterless high-efficient inverter can be achieved

Fine-Scale Mapping of the 4q24 Locus Identifies Two Independent Loci Associated with Breast Cancer Risk

Background: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. Methods: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. Results: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10−4; OR, 1.04; 95% confidence interval (CI), 1.02–1.07] and rs77928427 (P = 1.86 × 10−4; OR, 1.04; 95% CI, 1.02–1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r2 ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor–binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. Conclusion: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. Impact: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk

Cardiovascular disease, chronic kidney disease, and diabetes mortality burden of cardiometabolic risk factors from 1980 to 2010: A comparative risk assessment

Background: High blood pressure, blood glucose, serum cholesterol, and BMI are risk factors for cardiovascular diseases and some of these factors also increase the risk of chronic kidney disease and diabetes. We estimated mortality from cardiovascular diseases, chronic kidney disease, and diabetes that was attributable to these four cardiometabolic risk factors for all countries and regions from 1980 to 2010. Methods: We used data for exposure to risk factors by country, age group, and sex from pooled analyses of population-based health surveys. We obtained relative risks for the effects of risk factors on cause-specific mortality from meta-analyses of large prospective studies. We calculated the population attributable fractions for each risk factor alone, and for the combination of all risk factors, accounting for multicausality and for mediation of the effects of BMI by the other three risks. We calculated attributable deaths by multiplying the cause-specific population attributable fractions by the number of disease-specific deaths. We obtained cause-specific mortality from the Global Burden of Diseases, Injuries, and Risk Factors 2010 Study. We propagated the uncertainties of all the inputs to the final estimates. Findings: In 2010, high blood pressure was the leading risk factor for deaths due to cardiovascular diseases, chronic kidney disease, and diabetes in every region, causing more than 40% of worldwide deaths from these diseases; high BMI and glucose were each responsible for about 15% of deaths, and high cholesterol for more than 10%. After accounting for multicausality, 63% (10·8 million deaths, 95% CI 10·1-11·5) of deaths from these diseases in 2010 were attributable to the combined effect of these four metabolic risk factors, compared with 67% (7·1 million deaths, 6·6-7·6) in 1980. The mortality burden of high BMI and glucose nearly doubled from 1980 to 2010. At the country level, age-standardised death rates from these diseases attributable to the combined effects of these four risk factors surpassed 925 deaths per 100 000 for men in Belarus, Kazakhstan, and Mongolia, but were less than 130 deaths per 100 000 for women and less than 200 for men in some high-income countries including Australia, Canada, France, Japan, the Netherlands, Singapore, South Korea, and Spain. Interpretation: The salient features of the cardiometabolic disease and risk factor epidemic at the beginning of the 21st century are high blood pressure and an increasing effect of obesity and diabetes. The mortality burden of cardiometabolic risk factors has shifted from high-income to low-income and middle-income countries. Lowering cardiometabolic risks through dietary, behavioural, and pharmacological interventions should be a part of the global response to non-communicable diseases. Funding: UK Medical Research Council, US National Institutes of Health. © 2014 Elsevier Ltd

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Genome-wide association meta-analysis of corneal curvature identifies novel loci and shared genetic influences across axial length and refractive error

Abstract: Corneal curvature, a highly heritable trait, is a key clinical endophenotype for myopia - a major cause of visual impairment and blindness in the world. Here we present a trans-ethnic meta-analysis of corneal curvature GWAS in 44,042 individuals of Caucasian and Asian with replication in 88,218 UK Biobank data. We identified 47 loci (of which 26 are novel), with population-specific signals as well as shared signals across ethnicities. Some identified variants showed precise scaling in corneal curvature and eye elongation (i.e. axial length) to maintain eyes in emmetropia (i.e. HDAC11/FBLN2 rs2630445, RBP3 rs11204213); others exhibited association with myopia with little pleiotropic effects on eye elongation. Implicated genes are involved in extracellular matrix organization, developmental process for body and eye, connective tissue cartilage and glycosylation protein activities. Our study provides insights into population-specific novel genes for corneal curvature, and their pleiotropic effect in regulating eye size or conferring susceptibility to myopia

Optimal voltage stability assessment based on voltage stability indices and artificial neural network

The evaluation of voltage stability assessment experiences sizeable anxiety in the safe operation of power systems, due to the complications of a strain power system. With the snowballing of power demand by the consumers and also the restricted amount of power sources, therefore, the system has to perform at its maximum proficiency. The noteworthy to discover the maximum ability boundary prior to voltage collapse should be undertaken. A preliminary warning can be perceived to evade the interruption of power system’s capacity. This research considered the implementation of static and time-step system monitoring methods that able to provide a timely warning in the power system. Numerous types of line voltage stability indices (LVSI) are differentiated in this research to resolve their effectuality to determine the weakest lines for the power systems. The main motivation of these indices is used to predict and forecast the proximity towards voltage instability in the power system control and security applications. The indices are also able to decide the weakest load buses which are close to voltage collapse in the power system. Therefore, the static and time-step simulation (TSS) results are used to calculate the line stability indices and to ratify with voltage stability indices theory. The line voltage stability indices are assessed using the IEEE 9-Bus system, IEEE 14-Bus System and IEEE 30-Bus system to validate their practicability. The results are used to calculate the line stability indices by using Matlab software. This research also introduced the implementation of voltage stability monitoring by using Artificial Neural Network (ANN). Results demonstrated that the calculated indices and the estimated indices by using ANN are practically relevant in predicting the manifestation of voltage collapse in the system. Overall, VCPI(Power) index is able to detect the voltage collapse point precisely due to its accuracy in forecasting. This index successfully showed the capability to forecast the voltage collapse point either in small or a larger power system network. Therefore, essential actions can be taken by the operators in order to dodge voltage collapse incident from arising

Feedforward Artificial Neural Network for Predicting Voltage Stability Indices in Power Systems

Several electricity failures associated with the voltage stability incident have appeared in a few countries. Nowadays, main concern towards voltage stability control and prediction is no longer crucial, however significant awareness is arising to sustain power system’s stability to conceal recurrence of major blackouts. Numerous types of line voltage stability indices (LVSI) being appointed to validate the weakest lines in IEEE 30-Bus test system. Besides that, LVSI is being forecasted by Feedforward Back Propagation Artificial Neural Network (FFBPNN) in order to recognize the voltage stability in IEEE 30-Bus test system. The calculated indices by using LVSI and forecasted indices by using FFBPNN are realistically applicable to discover the voltage collapse event in the system. The actual output for the VCPI(Power) in line 2-5 is 1.0459, while the predicted VCPI(Power) by using FFBPNN is 1.0459 with 3 seconds training time with 0% error percentage. Generally, the voltage collapse event has been successfully proven based on the capability of VCPI(Power). Therefore, necessary measures are capable to be performed by the power system operators to evade voltage collapse events occurred

Transmission Line Fault Detection: A Review

Transmission line is the most important part of the power system.  Transmission lines a principal amount of power. The requirement of power and its allegiance has grown up exponentially over the modern era, and the major role of a transmission line is to transmit electric power from the source area to the distribution network. The exploded between limited production, and a tremendous claim has grown the focus on minimizing power losses. Losses like transmission loss and also conjecture factors as like as physical losses to various technical losses, Another thing is the primary factor it has a reactive power and voltage deviation are momentous in the long-range transmission power line. In essentially, fault analysis is a very focusing issue in power system engineering to clear fault in short time and re-establish power system as quickly as possible on very minimum interruption. However,  the fault detection that interrupts the transmission line is itself challenging task to investigate fault as well as improving the reliability of the system. The transmission line is susceptible given all parameters that connect the whole power system. This paper presents a review of transmission line fault detection