Impacts of automatic control systems of loop restoration scheme on the distribution system reliability

Loop restoration scheme (LRS) is a special feeder automation (FA) scheme, which is used by utilities to improve distribution system reliability. The LRS is controlled and managed by its automatic control system (ACS). The impacts on distribution system reliability indices of implementing LRS mainly depend on the type of its ACS. Two common types of ACS of LRS are presented and used in this study. Successful operation of ACS is dependent on the protection and automatic control functions of switching devices of LRS. Different failure modes of these switching devices can therefore affect the procedure of ACS in fault detecting, isolating and service restoration. The impacts of failure of protection and automatic control functions of switching devices and fuse of lateral distributors on reliability indices are illustrated. The worth of implementing LRS and its ACS type is represented by the reduction in expected customer interruption cost. A distribution test system is utilised to examine the impacts of two common types of ACS of LRS on the distribution system reliability. Selecting the type of ACS of LRS by utilities relies on the desired level of load-point and system reliability improvement. This study aims to quantitatively assess the impacts of two common types of ACS of LRS on the distribution system reliability.     

Reliability assessment of restructured power systems using optimal load shedding technique

Power systemrestructuring and deregulation has changed the strategy of reliabilitymanagement of a power system. Load shedding, and generation and reserve re-dispatch methods used in the existing reliability evaluation techniques have to be improved to incorporate these changes. An optimisation technique, incorporating those changes, is proposed in this study to determine load curtailment and generation re-dispatch for each contingency state in the reliability evaluation of restructured power systems with the Poolco market structure. The problem is formulated using the optimal power flow (OPF) technique. The objective of the problem is to minimise the total system cost, which includes generation, reserve and interruption costs, subject to market and network constraints. A model for the contingency management of a Poolco power market is presented to include generation and reserve biddings, reliability considerations and transmission network constraints in reliability evaluation. Both supply side reliability for a generation company (Genco) and demand-side reliability for a customer can be calculated using the technique. The proposed technique can be used to evaluate both conventional and restructured power systems, and can provide both economic and reliability information for the independent system operator to manage system reliability, for Gencos to enhance their reliability, and for customer to select suppliers. The modified IEEE-RTS with the Poolco market has been analysed to illustrate the techniques. The results obtained using the proposed technique have been compared with those from the existing load shedding techniques.     

Three-phase balancing of distribution feeders using immune algorithm

The immune algorithm (IA) is proposed to derive the rephasing strategy arrangement of laterals and distribution transformers to enhance three-phase balancing of distribution systems. The multi-objective function is formulated by considering the unbalance of phasing currents, the customer service interruption cost (CIC) and labour cost to perform the optimal rephasing strategy. For each feasible rephasing strategy, the number of customers affected with total interruption load demand and outage duration time are used to calculate the impact of system reliability because of rephasing engineering works. To demonstrate the effectiveness of the proposed methodology, a practical distribution feeder in Taipower with 271 customers is selected for computer simulation. By minimising the objective function subjected to the operation constraints, the rephasing strategy has been derived by selecting the laterals and distribution transformers for phasing adjustment. It is found that the neutral current of test feeder has been reduced to be less than the neutral overcurrent limit by executing the rephasing of laterals and distribution transformers.     

Reliability assessment of an automated distribution system

Automation can greatly enhance distribution-network reliability by speeding up service restoration and thus significantly reduce customer-outage time. The paper presents an approach to assess quantitatively the adequacy of a particular automated distribution scheme designated as the `low interruption system' (LIS). Owing to the use of a high-speed communication system and line sensors, this automated scheme can reduce drastically the number of interruptions, the service interruption time and also the area affected by the fault. This scheme provides a simple and cost-effective way to automate distribution systems in which the remotely controlled switches speed up isolation of faulted sections and the restoration of healthy sections through alternative routes. The step-by-step calculation procedure is presented using a typical small automated distribution system. The proposed technique is then applied to a larger distribution system to examine the effectiveness of the technique and also to examine the level of reliability improvement achieved by automation     

Evaluation of reliability worth in an electric power system

This paper illustrates the application of basic power system reliability evaluation techniques to the quantification of reliability worth. The approach presented links customer interruption cost estimates with predictable indices of power system reliability. The technique is illustrated by application in the areas of generation, composite generation and transmission, and distribution system assessment using a hypothetical test system.     

Stochastic search techniques for post-fault restoration of electrical distribution systems

Three stochastic search techniques have been used to find the optimal sequence of operations required to restore supply in an electrical distribution system on the occurrence of a fault. The three techniques are the genetic algorithm, simulated annealing and the tabu search. The performance of these techniques has been compared. A large distribution system of over 29 substations, 2500 nodes and 120 feeders has been used.     

Image restoration through regularization based on error energy minimization

Image restoration has been an important field of image processing for decades. Various methods of restoration have been studied. Meanwhile, regularization presents a very general methodology for image restoration. However, more regularization will remove more noise but will also lose more image detail, and vice versa. In this article, a novel image restoration algorithm is presented, which is derived from regularization by minimizing error energy of noise and ring artifact. Thus, this proposed algorithm is not only immune to noise but also ringing artifact, where a designed high‐pass filter is used in the algorithm proposed here such as the difference of a delta function and a blurring function or an edge operator like a Laplacian operator. This proposed algorithm can achieve high‐resolution images by being implemented with a 1D noiseless signal to reveal its ability of generating high frequencies beyond the diffraction limit and with a 2D computer‐generated noisy image to show the ability of being immune to noise as well as with a 94‐GHz millimeter‐wave image to validate its reliability. © 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 308–315, 2010     

Semi-parametric PWP model robustness for log-linear increasing rates of occurrence of failures

Repairable systems have reliability (failure) and maintainability (restoration) processes that tend to improve or deteriorate over time depending on life-cycle phase. External variables (covariates) can explain differences in event rates and thus provide valuable information for engineering analysis and design. In some cases, the processes may be modeled by a parametric non-homogeneous Poisson process (NHPP) with proportional intensity function, incorporating the covariates. However, the true underlying process may not be known, in which case a distribution-free or semi-parametric model may be very useful. The Prentice, Williams and Peterson (PWP) family of proportional intensity models has been proposed for application to repairable systems. This paper reports results of a study on the robustness of one PWP reliability model over early failure history. The assessment of robustness was based on the semi-parametric PWP model's ability to predict the successive times of occurrence of events when the underlying process actually is parametric (specifically a NHPP having log-linear proportional intensity function with one covariate). A parametric method was also used to obtain maximum likelihood estimates of the log-linear parameters, for purposes of validation and as a reference for comparison. The PWP method provided accurate estimates of the time to next event for NHPP log-linear processes with moderately increasing rates of occurrence of events. Potential engineering applications to repairable systems, with increasing rates of event occurrence, include reliability (failure) processes in the wear-out phase and maintainability (restoration) processes in the learning phase. A real example of a maintainability (restoration) process (log-linear NHPP with two explanatory covariates) for US Army M1A2 Abrams Main Battle Tank serves to demonstrate the engineering relevance of the methods evaluated in this research.     

Noise classification and automatic restoration system using non-local regularization frameworks

ABSTRACT

Medical, satellite or microscopic images differ in the imaging techniques used, hence their underlying noise distribution also are different. Most of the restoration methods including regularization models make prior assumptions about the noise to perform an efficient restoration. Here we propose a system that estimates and classifies the noise into different distributions by extracting the relevant features. The system provides information about the noise distribution and then it gets directed into the restoration module where an appropriate regularization method (based on the non-local framework) has been employed to provide an efficient restoration of the data. We have effectively addressed the distortion due to data-dependent noise distributions such as Poisson and Gamma along with data uncorrelated Gaussian noise. The studies have shown a 97.7% accuracy in classifying noise in the test data. Moreover, the system also shows the capability to cater to other popular noise distributions such as Rayleigh, Chi, etc.     

Reliability Target Assessment Based on Integrated Factors Method (IFM): A Real Case Study of a Sintering Plant

The success of a company depends on customer’s satisfaction: quality, price, and service. These three goals depend in particular on R.A.M.S. characteristics: reliability, availability, maintainability, and safety. In the last few years, in order to guarantee high standards of reliability and maintainability, new methodologies and techniques have been developed to estimate the R.A.M.S. targets. In particular, the reliability target represents both the starting and the ending point of R.A.M.S. analysis. The design of the reliability target of a system is a crucial aspect of reliability analysis, as it affects the performance of the system and components. This paper aims to develop a new approach called “IFM Target,” to define the reliability target for complex systems through the integrated factors method, to combine the advantages of usually used approaches, and to overcome some criticalities highlighted in a careful literature analysis. The proposed method has been applied on a sintering system. The results show the effectiveness of the proposed approach.     

Electric power system customer interruption cost assessment

A common approach used in quantifying the worth or benefit of electric service reliability is to estimate the customer costs (monetary losses) associated with power interruptions. Customer surveys are often used to determine interruption costs. The Power Systems Research Group has recently conducted surveys of Canadian electric utility customers in the residential, commercial, industrial, and agricultural sectors. These surveys were sponsored by the Natural Sciences and Engineering Research Council and eight participating utilities. This paper presents summary results of these surveys with emphasis on the costs of interruption.     

Analysis of repairable systems with severe left censoring or truncation

Left censoring or left truncation occurs when specific failure information on machines is not available before a certain age. If only the number of failures but not the actual failure times before a certain age is known, we have left censoring. If neither the number of failures nor the times of failure are known, we have left truncation. A datacenter will typically include servers and storage equipment installed on different dates. However, data collection on failures and repairs may not begin on the installation date. Often, the capture of reliability data starts only after the initiation of a service contract on a particular date. Thus, such data may exhibit severe left censoring or truncation, since machines may have operated for considerable time periods without any reliability history being recorded. This situation is quite different from the notion of left censoring in non-repairable systems, which has been dealt with extensively in the literature. Parametric modeling methods are less intuitive when the data has severe left censoring. In contrast, non-parametric methods based on the Mean Cumulative Function (MCF), recurrence rate plots, and calendar time analysis are simple to use and can provide valuable insights into the reliability of repairable systems, even under severe left censoring or truncation. The techniques shown have been successfully applied at a large server manufacturer to quantify the reliability of computer servers at customer sites. In this discussion, the techniques will be illustrated with actual field examples.     

Reliability analysis of the dynamic system for the Chen model through sequential order statistics

Recently, the two-parameter Chen distribution has widely been used for reliability studies in various engineering fields. In this article, we have developed various statistical inferences on the composite dynamic system, assuming Chen distribution as a baseline model. In this dynamic system, failure of a component induces a higher load on the surviving components and thus increases component hazard rate through a power-trend process. The classical and Bayesian point estimates of the unknown parameters of the composite system are obtained by the method of maximum likelihood and Markov chain Monte Carlo techniques, respectively. In the Bayesian framework, we have used gamma priors to obtain Bayes estimates of unknown parameters under the squared error and generalized entropy loss functions. The interval estimates of the baseline reliability function are obtained by using the Fisher information matrix and Bayesian method. A parametric hypothesis test is presented to test whether the failed components change the hazard rate function. A compact simulation study is carried out to examine the behavior of the proposed estimation methods. Finally, one real data analysis is performed for illustrative purposes.     

Production reliability in flexible manufacturing systems

A typical flexible manufacturing system, Westland Helicopters' sheet metal detail manufacturing complex, has been analysed for reliability. The techniques of fault tree analysis and event tree analysis are presented and their applicability to this study investigated. Event tree analysis has been found to be a more effective method for analysing manufacturing systems. The failure states of the system have been identified from the construction of an event tree which considers random hardware faults that influence production. Failure rate data have been used to quantify the critical production failure states in terms of machine failures. Estimates are made of the system's MTTF and percentage availability using typical MTTR figures. The probability that a selected production route fails to complete the manufacture of a set of parts is also evaluated. A dependency of systems reliability on the production demand has been discovered, and a possible method for modelling and assessing the reliability of systems capable of producing several products is proposed.     

Operational reliability assessment of power systems considering condition-dependent failure rate

Failure rate of a system component is usually assumed to be constant in conventional reliability evaluation of power systems. It has been realised from the real-time operation that a component will experience more failures during heavy loading condition than those during light loading condition, which means that the failure rate of a component in real-time operation is not constant and varies with loading condition. In order to evaluate system operational reliability related to load condition, the factors affected condition-dependent failure rate (CDFR) are investigated and a basic CDFR model is proposed in this study. In predictive operational reliability study, equipment loading condition for a given load period is determined using AC power flow based on the corresponding load level with considering load uncertainty. A four-state model has been proposed to represent a system component. The equations for determining the probability of each state for the four-state model have been derived. A technique based on these equations and models has been developed to evaluate operational and annual reliability indices of components, load points and system. The IEEE-RTS has been analysed to illustrate the proposed models and technique.     

A Bayesian framework for accelerated reliability growth testing with multiple sources of uncertainty

Reliability growth tests are often used for achieving a target reliability for complex systems via multiple test‐fix stages with limited testing resources. Such tests can be sped up via accelerated life testing (ALT) where test units are exposed to harsher‐than‐normal conditions. In this paper, a Bayesian framework is proposed to analyze ALT data in reliability growth. In particular, a complex system with components that have multiple competing failure modes is considered, and the time to failure of each failure mode is assumed to follow a Weibull distribution. We also assume that the accelerated condition has a fixed time scaling effect on each of the failure modes. In addition, a corrective action with fixed ineffectiveness can be performed at the end of each stage to reduce the occurrence of each failure mode. Under the Bayesian framework, a general model is developed to handle uncertainty on all model parameters, and several special cases with some parameters being known are also studied. A simulation study is conducted to assess the performance of the proposed models in estimating the final reliability of the system and to study the effects of unbiased and biased prior knowledge on the system‐level reliability estimates.     

Reliability Assessment of Cogeneration Power Plant in Textile Mill Using Fault Tree Analysis

The Combined Heat and Power (CHP) Systems are systems that simultaneously generate both electricity and useful heat. It is important to analyze the reliability of these systems to ensure the lowest level of life cycle cost. A CHP system installed in a textile mill is considered as a case study to assess the reliability through fault tree analysis (FTA). The common cause failures (CCFs) are evaluated using the β-factor model with the available data on the failure of the plant. On a detailed analysis, it is found that the unavailability of the plant is 8.50E−03, which is predominantly caused by the problems related to mechanical system, subsystems of boiler, and turbine. The repair and the restoration times for these components used in the fault tree analysis (FTA) are 48 and 8 h, respectively. Hence, faster restoration of these components affected by shutdown/failure and implementation of reliability-centered maintenance (RCM) features will significantly improve the reliability of the system, thereby reducing the time with respect to return on the investment.     

A reliability analysis for electronic devices under an extension of exponentiated perks distribution

This paper presents a reliability analysis for electronic devices (ED) with bathtub curve-shaped failure times. An extension of the exponentiated perks distribution (EPD) is proposed for the analysis. The extension of this new distribution is based on the Alpha Power Transformation, so the Alpha Exponentiated Perks Distribution (AEXP) is introduced. The AEXP has three shape parameters and one scale parameter, allowing greater flexibility to represent failure rates in an increasing, decreasing, or bathtub curve form. Some useful properties in the reliability engineering context are presented. AEXP parameters were estimated via the Maximum Likelihood Method. Finally, two case studies focused on ED are used to compare the proposed distribution and other distributions with similar failure rate representation properties. The obtained results show that the AEXP better describes the behavior of ED than the distributions considered in the analysis.     

Power spectrum equalization for ultrasonic image restoration

A method of image restoration for ultrasonic B-scan images has been proposed that need no a priori knowledge on the PSF (point spread function) of the imaging system and is feasible for in vivo applications. The entire system's response, including the interposed medium and possible transducer defects, is estimated from the degraded image itself with a few simple operations. The ultrasonic image is restored based only on a knowledge of the estimated PSF and on the spectral characteristics of the resultant echo signal. The proposed method does not modify the phase relations between echoes from multiple scatterers since the restoration filter is phaseless and the display operation does not involve nonlinear detection. The effectiveness of the restoration filter was tested on simulated ultrasonic images in the absence and in the presence of interposed tissue. Then the filter was tested on a phantom made of scatterers randomly distributed in nonattenuating gel with and without an interposed medium whose attenuation linearly increases with frequency. A good correspondence between simulations and experimental results was found: both tests show an exceptional improvement of image resolution.     

Sequence alteration and restoration related to sequenced parts delivery on an automobile mixed-model assembly line with multiple departments

A mixed-model assembly line is commonly used in the automobile industry. When there are multiple departments on an assembly line, there are usually different sequencing considerations from various departments. Intentional sequence alteration to accommodate a different sequencing consideration can be needed for a downstream department. Unintentional sequence alteration may also take place due to rework or equipment breakdowns. There is also an increasingly common practice in automobile assembly to have parts sequenced before delivering to the final assembly line. To achieve sequenced parts delivery, the sequence needs to be known in advance. Thus, addressing sequence alteration and restoration becomes more relevant for an automobile mixed-model assembly line. A number of sequence alteration methods to accommodate a downstream department's sequencing considerations are presented. One method easily supports sequence restoration of the sequence altered by the method. Two sequence restoration methods for restoring the sequence altered by unintentional reasons are discussed; the proper sizing of the two restoration methods are also addressed. These sequence alteration and restoration approaches mainly address the design and control aspects of the mixed-model assembly line. A case study based on an automobile assembly plant is presented to demonstrate the use of these methods.