Application of statistical methods for making maintenance decisions within power utilities

Jongen, Rogier; Morshuis, P.H.F.; Gulski, Ε.; Smit, J.J.; Maksymiuk, J.; Janssen, Anton

doi:10.1109/mei.2006.253418

Cited by 18 publications

(7 citation statements)

References 6 publications

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“…1. It can be seen [3,6] that the calculated number of failures based on the analysis are comparable with the actual number of failures in the period 2000-2002. The expected increase in failures after 2002 is typical for the aging stage of the cable joints.…”

Section: Introductionmentioning

confidence: 61%

“…by the concept of condition indexing [2]. is often the practical situation that failure statistics on insulation and accessories aren't sufficiently available, making a good prediction of expected life time of these cable systems difficult [3,4]. On the other hand about on-site diagnostics for power cables a lot of experience is available [5].…”

Section: Introductionmentioning

confidence: 99%

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Diagnostic decision support system with condition indexing for asset managers of electrical infrastructures

Smit

Piepers

Gulski³

2007

2007 IEEE International Conference on Systems, Man and Cybernetics

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Maintenance decisions for high voltage assets are usually based on experience and failure statistics, however often too low sample sizes are available. On the one hand failure data do show that aging processes proceed inevitably in network components during a certain period of time before failure. Therefore diagnostic tools to assess the condition of high voltage components are very useful when the overall age of the electrical infrastructure increases. Depending on the diagnostic tool used, the results of the measurements involve different diagnostic parameters, e.g. partial discharge (PD) inception voltage, PD magnitudes at different voltages, tangent delta and return voltages. It is also known that aging and degradation, as failure mechanisms, are statistical in nature. On the other hand the amount of diagnostic data can be large, enabling an additional source of statistical information to estimate the time to failure more at specific components level. Due to stochastic behavior of the underlying degradation mechanisms the diagnostic data can be statistically interpreted. As a result boundaries for condition indexes for good, moderate and bad technical performance are derived, which are more adequately for implementation in an diagnostic decision support system of a utility, in particular to direct maintenance and replacement policy of components.

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Section: Introductionmentioning

confidence: 61%

Section: Introductionmentioning

confidence: 99%

Diagnostic decision support system with condition indexing for asset managers of electrical infrastructures

Smit

Piepers

Gulski³

2007

2007 IEEE International Conference on Systems, Man and Cybernetics

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“…Than among others, maintenance policy is one of the major goals of on-site testing of service aged MV power cables. For this reason it is important to get more knowledge about cable aging processes related to diagnostic parameters values [1][2][3][4][5][6][7][8][9]. On the other hand the most difficult part is always the interpretation of diagnostic parameters especially related to aging and degradation phenomena like PD occurrence.…”

Section: Generalmentioning

confidence: 99%

“…On the other hand the most difficult part is always the interpretation of diagnostic parameters especially related to aging and degradation phenomena like PD occurrence. It is known that Piotr Cicheckil, 1 II. STATISTICAL DATA INPUT In this contribution statistical analysis were employed to judge total 243 single MV (20kV) power distribution cable phases equipped with different amount of joints and 6 termination per circuit (all circuit are 3-phases).…”

Section: Generalmentioning

confidence: 99%

“…In particular the condition indexing based on calculated 40% and 80% reflecting service status can be in this way proposed to evaluate and follow the PD trend in function of service life time [1][2][3]. For Asset Management (AM) decision support, proposed condition indexing scheme (table V) has to concern most "probable" service situation and assumption that power cable reliability and failure rate is described by the 'bathtub curve' ( fig.…”

Section: Generalmentioning

confidence: 99%

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Interpretation of MV power cables PD diagnostic data using statistical analysis

Cichecki

Gulski

Smit

et al. 2008

Conference Record of the 2008 IEEE International Symposium on Electrical Insulation

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This document describes application of statistical analysis to several diagnostic parameters obtained during on-site measurements on MV power cables. The goal of this analysis is to estimate statistical borders values for different diagnostic parameters related to PD phenomena for cable insulation as well as different cable accessories like joint and termination. Data input introduced to analysis consist of mass, XLPE and mixed (XLPE +PILC) insulated power cables. Investigated parameters were obtained with application of damped AC (DAC) diagnostic system during on-site non-destructive tests. For the purpose of clear distinction between cable components (joints, termination, insulation parts) categories, of different cable accessories were created). For proper interpretation of collected data related to cable insulation condition as well as different accessories condition, categorization based on such diagnostic parameters e.g. PDIV (Partial Discharge Inception Voltage), PD occurrence, and PD mappings was done. Additionally crated in this way measuring criteria based on calculated statistical norms by fitting data to several statistic distributions were employed for overall condition indexing. Later on condition indexing was used to indicate percentage ration how big population of insulation and components are in very good, good and moderate condition.Index Terms-Condition index, cable insulation, damped AC, diagnostic data analysis, statistical analysis, partial discharges. condition of MV/HV power cables depends on several aging factors. The ageing mechanism developing in function of service time and evaluation of PD processes in cable insulation is a complex process. Each part of a cable system is exposed to ageing under influence of thermal, mechanical, chemical and electrical loads during service life. Especially old serviced cable systems with during service on-going PD activity in the insulation and the accessories are extremely sensitive to overstressing. PD "weak spots" presence accelerated by external stresses like: mechanical damages and environmental changes [4] can have direct impact on cable circuit reliability and failures rate ( fig. 1). In the other hand it is well known that degradation and failure mechanisms have statistical nature and for estimation relatively actual condition of the cable circuit, knowledge based on large number of examined cable sets is necessary. With application of statistically estimated diagnostic parameters so called norm values can be used to set e.g. "typical" PD level for particular insulation type with certain age and condition. During service life this value can increase or stay on stable level and the trending of changes may be useful in analyzing the degradation progress. For this reason is important to look for data characteristic in as long service period as it as possible to observe "typical" PD behavior. I. GENERALIN relation to reliability and availability of distribution cable connections, the MV power cables up to 20 kV play important role. A medium voltage...

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Statistical life data analysis for electricity distribution cable assets - an Asset Management approach

Mehairjan¹,

Djairam²,

Zhuang³

et al. 2011

IET and IAM Asset Management Conference 2011

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Nowadays, power utilities are adopting Asset Management as their framework in order to cope with the challenges introduced by the privatization and market competition in this sector. Stedin, a Dutch Distribution System Operator recognized the vital role that an Asset Management system has for its organization. Therefore, Stedin, has adopted the publicly available specification, BSI:PAS55, as a standard to perform the Asset Management responsibilities and tasks of their electricity and gas networks. Equipment life cycle and technical performance activities form an integral part of the implementation of an Asset Management system. In this context, Stedin felt the strong need to have access to systematic techniques and guidelines on how to deal with information of equipment lifetimes. In this paper a systematic method, based on Statistical Life Data Analysis, which deals with limited or incomplete life time data of large populations of assets with the aim of obtaining an indicator of the future failure expectancy is discussed. The methods and analytical tools developed in this contribution share a basic framework for decision-making and specify the evolution of the failures of asset population over time.

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Application of statistical methods for making maintenance decisions within power utilities

Cited by 18 publications

References 6 publications

Diagnostic decision support system with condition indexing for asset managers of electrical infrastructures

Diagnostic decision support system with condition indexing for asset managers of electrical infrastructures

Interpretation of MV power cables PD diagnostic data using statistical analysis

Statistical life data analysis for electricity distribution cable assets - an Asset Management approach

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