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Optimizing the replacement of overhead lines in rural distribution systems with respect to reliability and customer value
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.ORCID iD: 0000-0002-2964-7233
Karlstads Universitet.
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.ORCID iD: 0000-0003-4763-9429
2005 (English)In: Eighteenth International Conference and Exhibition on Electricity Distribution, CIRED 2005, 2005, 127-131 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we present a method for establishing the value of a network's components from a reliability worth perspective. The method can be applied to a general distribution system i.e. both for radial and meshed network systems. Moreover, this paper shows results from an application study for a rural network system that is dominated by overhead lines. The purpose of the study was to establish the value of a secondary feeding point. Further, the method is used to establish the best replacement strategy for the concerned overhead lines.

Place, publisher, year, edition, pages
2005. 127-131 p.
Series
IEE Conference Publication, 2005-11034
Keyword [en]
Electric power distribution; Reliability; Rural areas; Rural distribution systems; Rural network systems
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-8164Scopus ID: 2-s2.0-28644436819OAI: oai:DiVA.org:kth-8164DiVA: diva2:13415
Note
QC 20100810Available from: 2008-04-03 Created: 2008-04-03 Last updated: 2010-11-30Bibliographically 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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