Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A Review and Discussion of Failure Rate Heterogeneity in Power System Reliability Assessment
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering. (Reliability Centred Asset Management (RCAM) Group)ORCID iD: 0000-0002-3543-9326
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering. (Power system operation and control)ORCID iD: 0000-0003-3014-5609
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering. (Reliability Centred Asset Management (RCAM) Group)ORCID iD: 0000-0002-2964-7233
2016 (English)Manuscript (preprint) (Other academic)
Abstract [en]

The failure rate is a reliability measure which isused for planning and operation of the power system. Thus far, average or experience based failure rates were applied to power system equipment due to their straightforward implementation. However, this approach limits the accuracy of the gained resultsand neglects the important differentiation between populationand individual failure rates. Hence, this paper discusses and demonstrates the necessity to distinguish between populationand individual failure rates and reviews the existing literature offailure rate estimation within the power system domain. The literature is categorized into statistical data driven approaches and failure rate modelling with focus on different criteria whichcan be used to describe the heterogeneity within populations. The review reveals that the environmental impact was modelled predominantly.

Place, publisher, year, edition, pages
2016. p. 1-8
Keywords [en]
failure rate modelling; heterogeneity; individual failure rate; relative risk model
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-194408ISBN: 978-1-5090-1970-0 (print)OAI: oai:DiVA.org:kth-194408DiVA, id: diva2:1040230
Conference
Probabilistic Methods Applied to Power Systems (PMAPS), 2016 International Conference on, Beijing
Note

QC 20161026

Available from: 2016-10-26 Created: 2016-10-26 Last updated: 2018-09-28Bibliographically approved
In thesis
1. Condition-based Failure Rate Modelling for Individual Components in the Power System
Open this publication in new window or tab >>Condition-based Failure Rate Modelling for Individual Components in the Power System
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The electrical power grid is one of the most important infrastructures in the modernsociety. It supplies industrial and private customers with electricity and supportsother critical infrastructures such as the water supply. Thus, it is significant that the power grid is a reliable system. However, the power system experiences a hugetransition from classical production methods such as coal and nuclear power plantsto distributed renewable energy forms such as wind energy and photovoltaic. This change to a more distributed system challenges the existing power grid as well as the traditional business models of electric utilities. Thus, cost minimization to increase profitability and improvement of the power grid to increase customer satisfactionare in the focus. One approach to increase the reliability of the grid and decrease maintenance costs is a condition-based maintenance approach which requirescondition monitoring techniques.

This thesis introduces into failure rate modelling for individual power system components and develops a method to calculate individual failure rates based onthe average failure rate, failure statistics, and condition monitoring data. This approach includes the analysis of failure statistics to identify failure causes and failure locations which are population characteristics but can be utilized to describe the heterogeneity within the population. Thus, the thesis first introduces into the topic of failure analysis and heterogeneity in populations. Different factors are identified and categorized which describe the condition development of a component overtime. Then, the literature within failure rate estimation is reviewed to present the factors which are used within failure rate modelling and to outline the existingmethods which consider the individual. However, limitations are discussed which emphasize the demand for a new approach. Consequently, this thesis introduce intoa new approach for estimating the failure rate for individual components.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2016. p. 33
Series
TRITA-EE, ISSN 1653-5146 ; 2016:079
Keywords
Asset management, condition monitoring, diagnostic measures, failure rate, failure rate modeling, transformer diagnostics
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-187701 (URN)978-91-7729-031-5 (ISBN)
Presentation
2016-06-08, KTH Main Campus, Q22, Osquldas väg 6B, Stockholm, 16:08 (English)
Opponent
Supervisors
Projects
Energiforsk AB risk analysis program
Note

QC 20160526

Available from: 2016-05-26 Created: 2016-05-26 Last updated: 2016-10-26Bibliographically approved
2. Individual Failure Rate Modelling and Exploratory Failure Data Analysis for Power System Components
Open this publication in new window or tab >>Individual Failure Rate Modelling and Exploratory Failure Data Analysis for Power System Components
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

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.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2018. p. 79
Series
TRITA-EECS-AVL ; 2018:67
Keywords
Asset management, condition monitoring, failure rate, failure rate modeling
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-235519 (URN)978-91-7729-950-9 (ISBN)
Public defence
2018-10-19, E3, Osquars backe 14, Kungl. Tekniska högskolan, Stockholm, 10:00 (English)
Opponent
Supervisors
Projects
SweGRIDS, the Swedish Centre for Smart Grids and Energy Storage
Funder
SweGRIDS - Swedish Centre for Smart Grids and Energy Storage
Note

QC 20180928

Available from: 2018-09-28 Created: 2018-09-27 Last updated: 2018-09-28Bibliographically approved

Open Access in DiVA

No full text in DiVA

Search in DiVA

By author/editor
Jürgensen, Jan HenningNordström, LarsHilber, Patrik
By organisation
Electromagnetic Engineering
Other Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 291 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf