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TOWARDS HEALTH ASSESSMENT: FAILURE ANALYSIS AND RECOMMENDATION OF CONDITION MONITORING TECHNIQUES FOR LARGE DISCONNECTOR POPULATIONS
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering. (Reliability Centred Asset Management (RCAM) Group)ORCID iD: 0000-0002-3543-9326
(Vattenfall Eldistribution AB)
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering. (Reliability Centred Asset Management (RCAM) Group)
2016 (English)In: CIRED Workshop - Helsinki 14-15 June 2016, Helsinki, 2016, 4- p.Conference paper (Refereed)
Abstract [en]

Condition monitoring of power system equipment is an important part of asset management. Hence, health indices were developed to describe the equipment condition in a linguistic form with the obtained data. The development of health indices requires knowledge about the equipment population under investigation to consider all important factors. Therefore, this paper investigates the failure data of a large disconnector population to identify population characteristics such as failure modes and failure locations. The analysis showed that the functions maneuverability and current carrying are essential to monitor. Moreover, this paper discusses condition monitoring techniques for disconnector and their applicability in large populations. The paper concludes that even without cost intensive investments in condition measurements or higher preventive maintenance costs, a condition evaluation can be performed.

Place, publisher, year, edition, pages
Helsinki, 2016. 4- p.
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering; Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-187703OAI: oai:DiVA.org:kth-187703DiVA: diva2:931195
Conference
CIRED Workshop 2016
Note

QC 20160526

Available from: 2016-05-26 Created: 2016-05-26 Last updated: 2016-05-26Bibliographically 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. 33 p.
Series
TRITA-EE, ISSN 1653-5146 ; 2016:079
Keyword
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)
External cooperation:
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: 2016-09-12Bibliographically approved

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