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Monetary Importance of Component Reliability in Electrical Networks for Maintenance Optimization
KTH, Superseded Departments, Electrical Systems.ORCID iD: 0000-0002-2964-7233
KTH, Superseded Departments, Electrical Systems.ORCID iD: 0000-0003-4763-9429
2004 (English)In: 8th International Conference on Probabilistic Methods Applied to Power Systems: Iowa State Univ, Ames, IA, SEP 12-16, 2004, 2004, 150-155 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes a method for defining the importance of individual components in a network with respect to total interruption cost. Since the method considers several customer nodes simultaneously, it is especially suitable for network structures that serve many purposes/customers e.g. transmission and distribution networks with more than one load point. The major result is an importance index, I-H, for every component. This index can be used for the evaluation of maintenance actions. Furthermore, the importance index is used to calculate the component contribution to the total system interruption cost. Finally, the goal to reach an optimal maintenance plan is outlined. The methodology is presented together with an application study for an electrical distribution system in-the Stockholm area.

Place, publisher, year, edition, pages
2004. 150-155 p.
Keyword [en]
maintenance; optimization; reliability; interruption cost; importance index; reliability-centered maintenance (RCM); reliability-centered asset management (RCAM)
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-8163ISI: 000225735200026Scopus ID: 2-s2.0-14544273157ISBN: 0-9761319-1-9 (print)OAI: oai:DiVA.org:kth-8163DiVA: diva2:13414
Note

QC 20100810

Available from: 2008-04-03 Created: 2008-04-03 Last updated: 2017-06-14Bibliographically approved
In thesis
1. Maintenance optimization for power distribution systems
Open this publication in new window or tab >>Maintenance optimization for power distribution systems
2008 (English)Doctoral thesis, comprehensive summary (Other scientific)
Abstract [en]

Maximum asset performance is one of the major goals for electric power distribution system operators (DSOs). To reach this goal minimal life cycle cost and maintenance optimization become crucial while meeting demands from customers and regulators. One of the fundamental objectives is therefore to relate maintenance and reliability in an efficient and effective way. Furthermore, this necessitates the determination of the optimal balance between pre¬ventive and corrective maintenance, which is the main problem addressed in the thesis.

The balance between preventive and corrective maintenance is approached as a multiobjective optimization problem, with the customer interruption costs on one hand and the maintenance budget of the DSO on the other. Solutions are obtained with meta-heuristics, developed for the specific problem, as well as with an Evolutionary Particle Swarm Optimization algorithm. The methods deliver a Pareto border, a set of several solutions, which the operator can choose between, depending on preferences. The optimization is built on component reliability importance indices, developed specifically for power systems. One vital aspect of the indices is that they work with several supply and load points simultaneously, addressing the multistate-reliability of power systems. For the computation of the indices both analytical and simulation based techniques are used. The indices constitute the connection between component reliability performance and system performance and so enable the maintenance optimization.

The developed methods have been tested and improved in two case studies, based on real systems and data, proving the methods’ usefulness and showing that they are ready to be applied to power distribution systems. It is in addition noted that the methods could, with some modifications, be applied to other types of infrastructures. However, in order to perform the optimization, a reliability model of the studied power system is required, as well as estimates on effects of maintenance actions (changes in failure rate) and their related costs. Given this, a generally decreased level of total maintenance cost and a better system reliability performance can be given to the DSO and customers respectively. This is achieved by focusing the preventive maintenance to components with a high potential for improvement from system perspective.

Place, publisher, year, edition, pages
Stockholm: KTH, 2008. vii, 56 p.
Series
Trita-EE, ISSN 1653-5146 ; 2008:012
Keyword
Reliability Importance Index, Multiobjective Optimization, Maintenance Optimization, Asset Management, Customer Interruption Cost, Reliability Centred Maintenance (RCM), Reliability Centered Asset Management (RCAM), Monte Carlo Simulation, Evolutionary Particle Swarm Optimization.
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-4686 (URN)978-91-628-7464-3 (ISBN)
Public defence
2008-04-18, D3, D, Lindstedsv. 5, Stockholm, 13:15
Opponent
Supervisors
Note
QC 20100810Available from: 2008-04-03 Created: 2008-04-03 Last updated: 2010-08-10Bibliographically approved
2. Component reliability importance indices for maintenance optimization of electrical networks
Open this publication in new window or tab >>Component reliability importance indices for maintenance optimization of electrical networks
2005 (English)Licentiate thesis, comprehensive summary (Other scientific)
Abstract [en]

Maximum asset performance is one of the major goals for electric power system managers. To reach this goal minimal life cycle cost and maintenance optimization become crucial while meeting demands from customers and regulators. One of the fundamental objectives is therefore to relate maintenance and reliability in an efficiently and effectively way, which is the aim of several maintenance methods such as the Reliability Centered Maintenance method (RCM). Furthermore, this necessitates the determination of the optimal balance between preventive and corrective maintenance to obtain the lowest total cost.

This thesis proposes methods for defining the importance of individual components in a network with respect to total interruption cost. This is a first step in obtaining an optimal maintenance solution. Since the methods consider several customer nodes simultaneously, they are especially suitable for network structures that serve many purposes/customers e.g. transmission and distribution networks with more than one load point. The major results are three component reliability importance indices, which are applied in two case studies. The first case study is based on a network in the Stockholm area. The second case study is performed for one overhead line system in the rural parts of Kristinehamn. The application studies demonstrate that the indices are possible to implement for existing electrical networks and that they can be used for maintenance prioritization. Consequently these indices constitute a first step in the overall objective of a maintenance optimization method.

The computations of the indices are performed both with analytical and simulation based techniques. Furthermore, the indices can be used to calculate the component contribution to the total system interruption cost. The approach developed for the importance indices can be utilized in any multi-state network that can be measured with one performance indicator.

Place, publisher, year, edition, pages
Stockholm: KTH, 2005. viii, 64 p.
Series
Trita-ETS, ISSN 1650-674X ; 2005:09
Keyword
Electrical power technology, Reliability Importance Index, Maintenance Optimization, Asset Management, Customer Interruption Cost, Reliability Centred Maintenance (RCM), Reliability Centered Asset Management (RCAM), Monte Carlo Simulation, Elkraftteknik
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-274 (URN)91-7178-055-6 (ISBN)
Presentation
2005-05-25, H1, Teknikringen 33, Stockholm, 11:30
Opponent
Supervisors
Note
QC 20101130Available from: 2005-06-07 Created: 2005-06-07 Last updated: 2010-11-30Bibliographically approved

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