A.L.J. Janssen

Application of statistical methods for making maintenance decisions within power utilities

In this article, the theoretical considerations that have to be taken into account when using statistical failure analyses of service-aged components are discussed. Furthermore, two case studies in which statistical failure analysis is used to predict future failures and to see in what way strategies can influence this prediction are included. Then, conclusions are drawn based on the analysis of the two case studies

Application of statistical analysis in the asset management decision process

One of the tools to answer some typical asset management (AM) questions is the use of statistical analysis of life time data of high voltage components. When life time data of components is available, statistical analysis can be performed. The analysis can give information about the failure rate of components, expected failures in the future, conditional remaining life estimation and influence of maintenance- and/or replacement strategies. In this contribution the general approach of the analysis is shown together with some examples of typical AM questions for typical high voltage components. Statistical analysis is used to find answers to these questions.

Failure analysis of in service failed resin cable joints by means of a statistical approach

Statistical failure analysis can be a powerful tool for asset replacement strategies. In parts of the Netherlands, a specific type of resin joint for 10 kV paper-oil insulated cables was applied substantially in the 1970s. These joints have now a considerable contribution in outage time because of breakdown of the resin insulation. The reported failures over the last six years, together with the population still in service are used as input for statistical analysis with Weibull and Normal distributions. It can be concluded that the joints are in their wear-out life period and that ageing is the main reason for failures. The total number of expected failures, obtained from the analysis, shows an increasing trend in coming years. A testing program, started a few years ago, influences the failure behavior. An active replacement strategy can also influence the number of expected failures. A comparison is made between the influence of testing and replacement strategy.

Statistical analysis of in service failed epoxy resin bushings in a 50 kV switchgear assembly

In the 1960s up to the 1980s a very compact oil-filled switchgear assembly was installed in the 50 kV networks of different utilities in the Netherlands. Per bay the switchgear consists of different oil-filled compartments where the high voltage parts are supported and connected from one compartment to the other by epoxy resin bushings. The population of this type of bushing is relative large. The number of failures however is low, and most of them occurred in the early nineties. This initiated a concern about the possibility of an oncoming re-investment wave due to replacement of this type of circuit breaker. In this contribution a statistical analysis of failure data was performed for failure prediction in the future. From the statistical analysis it can be concluded that the bushings are in the wear-out life period of the bathtub curve. However, the relative low value of the shape parameter indicates that the ageing process is in its early stage. If the failure rate function obtained from the analysis is compared with the population in service, than the total population can be stated as young. With the analysis an estimate is made of the expected number of failures in coming years, which can help the asset manager to determine if action has to be taken to meet the business policy

Influence of ambient temperature on the failure behavior of cable joints

The failure behavior of resin cable joints in the medium voltage underground network in the Netherlands shows a correlation with the ambient temperature of the air above the ground. This behavior is especially seen when the failures occurred during the summer months are considered. In the last years the months July or August were very hot and the number of failures increased significantly in these months. The ambient temperature has an influence on the soil temperature through the year even 0.5 -1 meter below surface level where most cables are installed. It can also be seen that the failures follow the rise and fall of the average air temperature during the different days of the month with increasing and decreasing number of failures with some time delay. The change of the soil temperature around the joint results in a higher temperature within the joint, thus contributing to the failure of a joint, which is already in its ageing stage. The presence of a hotspot in combination with a rise of the soil temperature can result into breakdown. In this paper the failure behavior of resin cable joints and the possible effect of ambient temperature are discussed.

Life-data analysis for condition assessment of high-voltage assets

Currently, network operators are facing a situation in which their high-voltage assets are reaching or even exceeding their design lifetimes [1]-[3]. The problem of future replacement of assets must thus be considered [4], [5]. Spare parts must be available to ensure replacement of components that fail during operation. In practice, utilities adopt two different approaches to assessing the condition of their assets [6], [7], namely bottom-up and top-down analysis. Bottom-up analysis uses aging characteristics of the materials within a given asset, and diagnostic measurements are performed to assess the physical degradation of the various parts of that asset. In contrast, top-down analysis uses mathematics to analyze the service-lifetime data of the whole population under consideration and to estimate the number of future failures within the population. In practice, both approaches have limitations due to differences in component design, operational conditions, environment, and maintenance programs [1]. An additional difficulty arises from ongoing technological improvements, e.g., in the properties of materials used in high-voltage components over a period of perhaps 40 years. In this paper, parametric statistical methods are used to analyze the time to failure of high-voltage components and to estimate the number of future failures. Attention is drawn to several problems that complicate the statistical analysis of service-lifetime data. Detailed information on the basic theory of statistical analysis of failure data can be found in [5], [6], [8]. Using service-lifetime data provided by a Dutch utility, and Monte Carlo simulations, three case studies of the failure of high-voltage components are presented.

Reliability estimation for populations with limited and heavily censored failure information

Statistical analysis of the life data, is a useful tool helping to assess the life-time of populations of high-voltage components. More specific, the results of such analysis give overview over the failure behavior of the population under investigation, i.e. number and trend of expected failures. For the analysis, the detailed information about ages and numbers and ages of installed units and failed units has to be collected. Subsequently, the distribution representing the behavior of the population is fitted to the data. The latter allows deriving the time-dependent failure rate function, which in turn, directly indicates the trends of the future failures. However, this method requires homogeneous and independent data of sufficient amount. The latter becomes a problem, particularly that for past periods the failure data is often unavailable. It is important to estimate the population reliability and number of expected failures, for the whole population of components being operated. This is also important in the case when the available failure data comes only from one part of the area where the components are installed. In this paper we will show how to deal with populations where the available failure data is heavily censored, and what will the influence of the data division according to the regions in which the transformers are operated, on the failure expectancy.

Application of statistical tools for assessing service availability of high voltage power cables

The practical interest of power utilities regarding the maintenance and replacement policy of insulating systems such as cables, switchgear and transformers is often based on experiences knowledge and data from the past. The ages of components in the network are increasing and this can result in an increase of the number of failures in coming years. To be able to monitor the components powerful tools are diagnostic measurements performed on the network components and analysis of life time data obtained from the exploitation of the components. In this contribution the analysis procedure is applied to life time data of 50 kV mass-insulated cables of a Dutch utility.To see what can be expected in the future the population in service together with the obtained failure rate curve is used. This gives statistical information regarding expected failures and critical connections. The analysis can help the asset manager to determine if immediate action has to be taken to meet the business policy e.g. condition assessment, maintenance or replacement, or if the current policy fulfils the conditions.

Service Availability Assessment of Mass-insulated Power Cables by Means of Statistical Analysis

Failure data together with the length and the ages of mass-insulated power cables the still in service of a Dutch utility are used as input for the statistical analysis. The choice of the appropriate distribution depends on the goodness of fit to the data. The fitted statistical distribution gives the relation of the number of expected failures per kilometer together with the age of the cable. To see what can be expected in the future the population in service together with the obtained failure rate curve is used. This gives statistical information regarding expected failures and critical connections. The analysis can help the asset manager to determine if immediate action has to be taken to meet the business policy e.g. condition assessment, maintenance or replacement, or if the current policy fulfils the conditions.