| 1. |
- Jürgensen, Jan Henning, 1987-, et al.
(författare)
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Assessment of Explanatory Variables on the Failure Rate of Circuit Breakers Using the Proportional Hazard Model
- 2018
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Ingår i: 2018 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC). - Dublin, Ireland : IEEE conference proceedings. - 9781910963104
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Konferensbidrag (refereegranskat)abstract
- This paper utilises the proportional hazard model to understand and quantify the impact of explanatory variables on the failure rate of circuit breakers (CB). Particularly, 4496 work orders with 2622 high voltage CBs are investigated with an occurrence of 281 major failures. Different explanatory variables such as CB type, manufacturer, preventive maintenance (PM), and others are gathered to quantify their significance and magnitude of their effect. The results present that PM has a positive impact, the number of operations within the last year a negative impact, and age has a small but negative impact on the failure rate. The CB type is not significant in all analyses which can be explained by examining the PM and age of these CB types. This paper contributes to the understanding of how explantatory variables impact the failure rate which is essential for power system asset management.
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| 2. |
- Jürgensen, Jan Henning, 1987-, et al.
(författare)
-
Estimation of Individual Failure Rates for Power System Components based on Risk Functions
- 2018
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The failure rate is essential in power system reliability assessment and thus far it has been commonly assumed as constant. This is a basic approach that delivers reasonable results. However, this approach neglects the heterogeneity in component populations which has a negative impact on the accuracy of the failure rate. This paper proposes a method based on risk functions, which describes the risk behaviour of condition measurements over time, to compute individual failure rates within populations. The method is applied to a population of 12 power transformers on transmission level. The computed individual failure rates depict the impact of maintenance and that power transformers with long operation times have a higher failure rate. Moreover, the paper presents a procedure based on the proposed approach to forecast failure rates. Finally, the individual failure rates are calculated over a specified prediction horizon and depicted with a 95\% confidence interval.
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| 3. |
- Jürgensen, Jan Henning, 1987-, et al.
(författare)
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Impact Assessment of Remote Control and Preventive Maintenance on the Failure Rate of a Disconnector Population
- 2018
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Ingår i: IEEE Transactions on Power Delivery. - : IEEE. - 0885-8977 .- 1937-4208. ; 33:4, s. 1501-1509
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents the impact of different explanatory variables such as remote control availability and conducted preventive maintenance, among others, on failure statistics of a disconnector population in Sweden using the proportional hazard model. To do so, 2191 work orders were analysed which included 1626 disconnectors and 278 major failures. Here, the results show that the remote control availability for disconnectors - an example of such Smart Grid technology - has a negative effect on the failure rate, whereas preventive maintenance has a positive impact. It is also shown that the disconnector age is not significant and that certain disconnector types have a significant and positive correlation towards failures when compared to other disconnector types. The results increase the understanding of disconnector failures to improve asset management.
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| 4. |
- Jürgensen, Jan Henning, 1987-
(författare)
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Individual Failure Rate Modelling and Exploratory Failure Data Analysis for Power System Components
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- A set of vital societal functions such as health and safety are necessary for today's society to function and to secure the life of its individuals. Infrastructure is required to provide and maintain these functions. This for society critical infrastructure includes electronic communication technology, transport systems, oil \& gas supply, water supply, and the supply of electric power. The electric power system plays a central role in the critical infrastructure since it is required to operate all others. Therefore, outages in the power system can have severe consequences not solely for the supply of electricity but also for the supply of water, gas, and food. To provide a reliable and safe power supply, power system operators are applying asset management strategies to investigate, plan, maintain, and utilize the system and its components while improving the performance under its own financial constraints.One approach to increase the reliability of the power grid while decreasing costs is maintenance planning, scheduling, and optimization. To optimize maintenance, a reliability measure for power system components is required. The failure rate, which is the probability of failure in a predefined interval, is utilized in maintenance optimization. Thus far, an average failure rate has been assigned to all components of the same type due to a shortage of component failure data. However, this limits the accuracy of maintenance techniques since the component heterogeneity is neglected. Moreover, the actual failure rate is being underrated or overrated and it is a challenge to identify the impact of conducted maintenance tasks.This thesis presents how the failure rate accuracy can be improved despite limited failure data available. Firstly, an introduction to failure rate modelling theory, concepts, and definitions is given to provide a common understanding for the later chapters and papers. Secondly, regression models are presented which can be used to model, predict, and characterise the failure rate and failure intensity for power system components. The Cox regression and regression models for count data are applied to two case studies of disconnector and circuit breaker failure data. The results contribute to an improved modelling of the failure rate on individual level but also improve the understanding of risk factor's impact on component failures. However, the aforementioned regression models have rarely been applied in the power system domain due to the limited failure data. Thirdly, the necessity to distinguish between population and individual failure rates is illustrated and risk factors and methods are presented, which are frequently used in failure rate modelling. Moreover, the thesis presents a method to calculate and predict individual failure rates despite the occurrence of actual failures which is of particular advantage for new components.
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| 5. |
- Jürgensen, Jan Henning, 1987-, et al.
(författare)
-
Modelling of Recurrent Circuit Breaker Failures with Regression Models for Count Data
- 2018
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Konferensbidrag (refereegranskat)abstract
- High voltage circuit breaker (CB) are of fundamental importance to protect and operate the power system. To improve their performance and to better predict failures, it is necessary to understand the effect of covariates such as preventive maintenance, age, voltage level, and the CB type. A straightforward approach is to investigate recurrent failures with regression models for count data. In this paper, several regression models are developed to estimate the impact of the aforementioned covariates to predict the recurrence of failures. The results show that age has a significant and negative impact, preventive maintenance before the first failure has a positive impact, and that the voltage level has a negative impact. Moreover, the Poisson, Negative Binomial, and zero-inflated models are compared. The comparison shows that the Negative Binomial model has the best fit to the studied recurrent failure data.
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