Multi-area reliability assessment of interconnected generating systems using hybrid approach

This paper present an efficient method using system state sampling technique in Monte Carlo simulation for reliability evaluation of multi-area power systems, at Hierarchical Level One (HLI). System state sampling is one of the common methods used in Monte Carlo simulation. The cpu time and memory requirement can be a problem, using this method. Combination of analytical and Monte Carlo method known as Hybrid method, as presented in this paper, can enhance the efficiency of the solution. Incorporation of load model in this study can be utilised either by sampling or enumeration. Both cases are examined in this paper, by application of the methods on Roy Billinton Test System(RBTS).

An assessment for cost effective maintenance and operation of the Callide Power Station electrical system, using reliability evaluation

The reliable operation of the electrical system at Callide Power Station is of extreme importance to the normal everyday running of the Station. This study applied the principles of reliability to do an analysis on the electrical system at Callide Power Station. It was found that the level of expected outage cost increased exponentially with a declining level of maintenance. Concluding that even in a harsh economic electricity market where CS Energy tries and push their plants to the limit, maintenance must not be neglected. A number of system configurations were found to increase the reliability of the system and reduce the expected outage costs. A number of other advantages were identified as a result of using reliability principles to do this study on the Callide electrical system configuration.

Maintenance considerations in applied substation reliability assessment

This paper presents a reliability assessment of a substation, part of the Queensland transmission network in Australia. As part of a maintenance considerations, this study utilises the substation reliability assessment package STAREL to quantitatively compare the reliability improvement achieved by two circuit breaker reinforcement alternatives for Swanbank circuit breaker replacement or refurbishment. Substation reliability is interpreted on the basis of outage frequency and outage duration indices for each individual transmission line terminated in Swanbank 'B' substation. By considering the reliability indices in this paper with the cost associated conducted by POWERLINK Queensland, a Swanbank 'B' reinforcement alternative can be selected that optimises both transmission line security and the costs incurred in achieving it.

Applied Reliability of Transmission Substations

Reliability is an integral component of modern power system design, planning and management. This paper uses the Markov approach to substation reliability evaluation using dedicated reliability software. This technique was applied to yield reliability indices for an existing and important substation in the POWERLINK QUEENSLAND 275 kV transmission network. Reliability indices were also determined for several reinforcement alternatives for this substation with the aim of improving substation reliability. The economic feasibility of achieving higher levels of reliability was also taken into account.

Optimal distribution network reinforcement considering load growth, line loss, and reliability

In this paper, a new comprehensive planning methodology is proposed for implementing distribution network reinforcement. The load growth, voltage profile, distribution line loss, and reliability are considered in this procedure. A time-segmentation technique is employed to reduce the computational load. Options considered range from supporting the load growth using the traditional approach of upgrading the conventional equipment in the distribution network, through to the use of dispatchable distributed generators (DDG). The objective function is composed of the construction cost, loss cost and reliability cost. As constraints, the bus voltages and the feeder currents should be maintained within the standard level. The DDG output power should not be less than a ratio of its rated power because of efficiency. A hybrid optimization method, called modified discrete particle swarm optimization, is employed to solve this nonlinear and discrete optimization problem. A comparison is performed between the optimized solution based on planning of capacitors along with tap-changing transformer and line upgrading and when DDGs are included in the optimization.

Using mobile technology and augmented reality to increase data reliability for environmental assessment

Climate change and land use pressures are making environmental monitoring increasingly important. As environmental health is degrading at an alarming rate, ecologists have tried to tackle the problem by monitoring the composition and condition of environment. However, traditional monitoring methods using experts are manual and expensive; to address this issue government organisations designed a simpler and faster surrogate-based assessment technique for consultants, landholders and ordinary citizens. However, it remains complex, subjective and error prone. This makes collected data difficult to interpret and compare. In this paper we describe a work-in-progress mobile application designed to address these shortcomings through the use of augmented reality and multimedia smartphone technology.

On the reliability of classifying programming tasks using a Neo-Piagetian theory of cognitive development

Recent research has proposed Neo-Piagetian theory as a useful way of describing the cognitive development of novice programmers. Neo-Piagetian theory may also be a useful way to classify materials used in learning and assessment. If Neo-Piagetian coding of learning resources is to be useful then it is important that practitioners can learn it and apply it reliably. We describe the design of an interactive web-based tutorial for Neo-Piagetian categorization of assessment tasks. We also report an evaluation of the tutorial's effectiveness, in which twenty computer science educators participated. The average classification accuracy of the participants on each of the three Neo-Piagetian stages were 85%, 71% and 78%. Participants also rated their agreement with the expert classifications, and indicated high agreement (91%, 83% and 91% across the three Neo-Piagetian stages). Self-rated confidence in applying Neo-Piagetian theory to classifying programming questions before and after the tutorial were 29% and 75% respectively. Our key contribution is the demonstration of the feasibility of the Neo-Piagetian approach to classifying assessment materials, by demonstrating that it is learnable and can be applied reliably by a group of educators. Our tutorial is freely available as a community resource.

Timed Up and Go Tests in cardiac rehabilitation : reliability and comparison with the 6-minute walk test

PURPOSE: To test the reliability of Timed Up and Go Tests (TUGTs) in cardiac rehabilitation (CR) and compare TUGTs to the 6-Minute Walk Test (6MWT) for outcome measurement. METHODS: Sixty-one of 154 consecutive community-based CR patients were prospectively recruited. Subjects undertook repeated TUGTs and 6MWTs at the start of CR (start-CR), postdischarge from CR (post-CR), and 6 months postdischarge from CR (6 months post-CR). The main outcome measurements were TUGT time (TUGTT) and 6MWT distance (6MWD). RESULTS: Mean (SD) TUGTT1 and TUGTT2 at the 3 assessments were 6.29 (1.30) and 5.94 (1.20); 5.81 (1.22) and 5.53 (1.09); and 5.39 (1.60) and 5.01 (1.28) seconds, respectively. A reduction in TUGTT occurred between each outcome point (P ≤ .002). Repeated TUGTTs were strongly correlated at each assessment, intraclass correlation (95% CI) = 0.85 (0.76–0.91), 0.84 (0.73–0.91), and 0.90 (0.83–0.94), despite a reduction between TUGTT1 and TUGTT2 of 5%, 5%, and 7%, respectively (P ≤ .006). Relative decreases in TUGTT1 (TUGTT2) occurred from start-CR to post-CR and from start-CR to 6 months post-CR of −7.5% (−6.9%) and −14.2% (−15.5%), respectively, while relative increases in 6MWD1 (6MWD2) occurred, 5.1% (7.2%) and 8.4% (10.2%), respectively (P < .001 in all cases). Pearson correlation coefficients for 6MWD1 to TUGTT1 and TUGTT2 across all times were −0.60 and −0.68 (P < .001) and the intraclass correlations (95% CI) for the speeds derived from averaged 6MWDs and TUGTTs were 0.65 (0.54, 0.73) (P < .001). CONCLUSIONS: Similar relative changes occurred for the TUGT and the 6MWT in CR. A significant correlation between the TUGTT and 6MWD was demonstrated, and we suggest that the TUGT may provide a related or a supplementary measurement of functional capacity in CR.

Achieving high reliability for ambiguity resolutions with multiple GNSS constellations

Global Navigation Satellite Systems (GNSS)-based observation systems can provide high precision positioning and navigation solutions in real time, in the order of subcentimetre if we make use of carrier phase measurements in the differential mode and deal with all the bias and noise terms well. However, these carrier phase measurements are ambiguous due to unknown, integer numbers of cycles. One key challenge in the differential carrier phase mode is to fix the integer ambiguities correctly. On the other hand, in the safety of life or liability-critical applications, such as for vehicle safety positioning and aviation, not only is high accuracy required, but also the reliability requirement is important. This PhD research studies to achieve high reliability for ambiguity resolution (AR) in a multi-GNSS environment. GNSS ambiguity estimation and validation problems are the focus of the research effort. Particularly, we study the case of multiple constellations that include initial to full operations of foreseeable Galileo, GLONASS and Compass and QZSS navigation systems from next few years to the end of the decade. Since real observation data is only available from GPS and GLONASS systems, the simulation method named Virtual Galileo Constellation (VGC) is applied to generate observational data from another constellation in the data analysis. In addition, both full ambiguity resolution (FAR) and partial ambiguity resolution (PAR) algorithms are used in processing single and dual constellation data. Firstly, a brief overview of related work on AR methods and reliability theory is given. Next, a modified inverse integer Cholesky decorrelation method and its performance on AR are presented. Subsequently, a new measure of decorrelation performance called orthogonality defect is introduced and compared with other measures. Furthermore, a new AR scheme considering the ambiguity validation requirement in the control of the search space size is proposed to improve the search efficiency. With respect to the reliability of AR, we also discuss the computation of the ambiguity success rate (ASR) and confirm that the success rate computed with the integer bootstrapping method is quite a sharp approximation to the actual integer least-squares (ILS) method success rate. The advantages of multi-GNSS constellations are examined in terms of the PAR technique involving the predefined ASR. Finally, a novel satellite selection algorithm for reliable ambiguity resolution called SARA is developed. In summary, the study demonstrats that when the ASR is close to one, the reliability of AR can be guaranteed and the ambiguity validation is effective. The work then focuses on new strategies to improve the ASR, including a partial ambiguity resolution procedure with a predefined success rate and a novel satellite selection strategy with a high success rate. The proposed strategies bring significant benefits of multi-GNSS signals to real-time high precision and high reliability positioning services.

Intelligent reliability analysis with incomplete covariates

The reliability analysis is crucial to reducing unexpected down time, severe failures and ever tightened maintenance budget of engineering assets. Hazard based reliability methods are of particular interest as hazard reflects the current health status of engineering assets and their imminent failure risks. Most existing hazard models were constructed using the statistical methods. However, these methods were established largely based on two assumptions: one is the assumption of baseline failure distributions being accurate to the population concerned and the other is the assumption of effects of covariates on hazards. These two assumptions may be difficult to achieve and therefore compromise the effectiveness of hazard models in the application. To address this issue, a non-linear hazard modelling approach is developed in this research using neural networks (NNs), resulting in neural network hazard models (NNHMs), to deal with limitations due to the two assumptions for statistical models. With the success of failure prevention effort, less failure history becomes available for reliability analysis. Involving condition data or covariates is a natural solution to this challenge. A critical issue for involving covariates in reliability analysis is that complete and consistent covariate data are often unavailable in reality due to inconsistent measuring frequencies of multiple covariates, sensor failure, and sparse intrusive measurements. This problem has not been studied adequately in current reliability applications. This research thus investigates such incomplete covariates problem in reliability analysis. Typical approaches to handling incomplete covariates have been studied to investigate their performance and effects on the reliability analysis results. Since these existing approaches could underestimate the variance in regressions and introduce extra uncertainties to reliability analysis, the developed NNHMs are extended to include handling incomplete covariates as an integral part. The extended versions of NNHMs have been validated using simulated bearing data and real data from a liquefied natural gas pump. The results demonstrate the new approach outperforms the typical incomplete covariates handling approaches. Another problem in reliability analysis is that future covariates of engineering assets are generally unavailable. In existing practices for multi-step reliability analysis, historical covariates were used to estimate the future covariates. Covariates of engineering assets, however, are often subject to substantial fluctuation due to the influence of both engineering degradation and changes in environmental settings. The commonly used covariate extrapolation methods thus would not be suitable because of the error accumulation and uncertainty propagation. To overcome this difficulty, instead of directly extrapolating covariate values, projection of covariate states is conducted in this research. The estimated covariate states and unknown covariate values in future running steps of assets constitute an incomplete covariate set which is then analysed by the extended NNHMs. A new assessment function is also proposed to evaluate risks of underestimated and overestimated reliability analysis results. A case study using field data from a paper and pulp mill has been conducted and it demonstrates that this new multi-step reliability analysis procedure is able to generate more accurate analysis results.

Exploring dependencies of 5.9 GHz DSRC throughput and reliability on safety applications

Dedicated Short Range Communication (DSRC) is the emerging key technology supporting cooperative road safety systems within Intelligent Transportation Systems (ITS). The DSRC protocol stack includes a variety of standards such as IEEE 802.11p and SAE J2735. The effectiveness of the DSRC technology depends on not only the interoperable cooperation of these standards, but also on the interoperability of DSRC devices manufactured by various manufacturers. To address the second constraint, the SAE defines a message set dictionary under the J2735 standard for construction of device independent messages. This paper focuses on the deficiencies of the SAE J2735 standard being developed for deployment in Vehicular Ad-hoc Networks (VANET). In this regard, the paper discusses the way how a Basic Safety Message (BSM) as the fundamental message type defined in SAE J2735 is constructed, sent and received by safety communication platforms to provide a comprehensive device independent solution for Cooperative ITS (C-ITS). This provides some insight into the technical knowledge behind the construction and exchange of BSMs within VANET. A series of real-world DSRC data collection experiments was conducted. The results demonstrate that the reliability and throughput of DSRC highly depend on the applications utilizing the medium. Therefore, an active application-dependent medium control measure, using a novel message-dissemination frequency controller, is introduced. This application level message handler improves the reliability of both BSM transmissions/receptions and the Application layer error handling which is extremely vital to decentralized congestion control (DCC) mechanisms.

Reliability and validity of conjunctival ultraviolet autofluorescence measurement

BACKGROUND: Conjunctival ultraviolet autofluorescence (UVAF) photography was developed to detect and characterise pre-clinical sunlight-induced UV damage. The reliability of this measurement and its relationship to outdoor activity are currently unknown. METHODS: 599 people aged 16-85 years in the cross-sectional Norfolk Island Eye Study were included in the validation study. 196 UVAF individual photographs (49 people) and 60 UVAF photographs (15 people) of Norfolk Island Eye Study participants were used for intra- and inter-observer reliability assessment, respectively. Conjunctival UVAF was measured using UV photography. UVAF area was calculated using computerised methods by one grader on two occasions (intra-observer analysis) or two graders (inter-observer analysis). Outdoor activity category, during summer and winter separately, was determined with a UV questionnaire. Total UVAF equalled the area measured in four conjunctival areas (nasal/temporal conjunctiva of right and left eyes). RESULTS: Intra-observer (ρ_c=0.988, 95% CI 0.967 to 0.996, p<0.001), and inter-observer concordance correlation coefficients (ρ_c=0.924, 95% CI 0.870 to 0.956, p<0.001) of total UVAF exceeded 0.900. When grouped according to 10 mm(2) total UVAF increments, intra- and inter-observer reliability was very good (κ=0.81) and good (κ=0.71), respectively. Increasing time outdoors was strongly with increasing total UVAF in summer and winter (p(trend) <0.001). CONCLUSION: Intra- and inter-observer reliability of conjunctival UVAF is high. In this population, UVAF correlates strongly with the authors' survey-based assessment of time spent outdoors.

Homeostatic epistemology : reliability, coherence and coordination in a Bayesian virtue epistemology

How do agents with limited cognitive capacities flourish in informationally impoverished or unexpected circumstances? Aristotle argued that human flourishing emerged from knowing about the world and our place within it. If he is right, then the virtuous processes that produce knowledge, best explain flourishing. Influenced by Aristotle, virtue epistemology defends an analysis of knowledge where beliefs are evaluated for their truth and the intellectual virtue or competences relied on in their creation. However, human flourishing may emerge from how degrees of ignorance are managed in an uncertain world. Perhaps decision-making in the shadow of knowledge best explains human wellbeing—a Bayesian approach? In this dissertation I argue that a hybrid of virtue and Bayesian epistemologies explains human flourishing—what I term homeostatic epistemology. Homeostatic epistemology supposes that an agent has a rational credence p when p is the product of reliable processes aligned with the norms of probability theory; whereas an agent knows that p when a rational credence p is the product of reliable processes such that: 1) p meets some relevant threshold for belief (such that the agent acts as though p were true and indeed p is true), 2) p coheres with a satisficing set of relevant beliefs and, 3) the relevant set of beliefs is coordinated appropriately to meet the integrated aims of the agent. Homeostatic epistemology recognizes that justificatory relationships between beliefs are constantly changing to combat uncertainties and to take advantage of predictable circumstances. Contrary to holism, justification is built up and broken down across limited sets like the anabolic and catabolic processes that maintain homeostasis in the cells, organs and systems of the body. It is the coordination of choristic sets of reliably produced beliefs that create the greatest flourishing given the limitations inherent in the situated agent.

Validity and reliability of nutrition screening administered by nurses

Background: Nutrition screening is usually administered by nurses. However, most studies on nutrition screening tools have not used nurses to validate the tools. The 3-Minute Nutrition Screening (3-MinNS) assesses weight loss, dietary intake and muscle wastage, with the composite score of each used to determine risk of malnutrition. The aim of the study was to determine the validity and reliability of 3-MinNS administered by nurses, who are the intended assessors. Methods: In this cross sectional study, three ward-based nurses screened 121 patients aged 21 years and over using 3-MinNS in three wards within 24 hours of admission. A dietitian then assessed the patients’ nutritional status using Subjective Global Assessment within 48 hours of admission, whilst blinded to the results of the screening. To assess the reliability of 3-MinNS, 37 patients screened by the first nurse were re-screened by a second nurse within 24 hours, who was blinded to the results of the first nurse. The sensitivity, specificity and best cutoff score for 3-MinNS were determined using the Receiver Operator Characteristics Curve. Results: The best cutoff score to identify all patients at risk of malnutrition using 3-MinNS was three, with sensitivity of 89% and specificity of 88%. This cutoff point also identified all (100%) severely malnourished patients. There was strong correlation between 3-MinNS and SGA (r=0.78, p<0.001). The agreement between two nurses conducting the 3-MinNS tool was 78.3%. Conclusion: 3-Minute Nutrition Screening is a valid and reliable tool for nurses to identify patients at risk of malnutrition.