The application of health- and risk indices as a decision-support tool for utilities

M.E. Vermeer, J.D. Schuddebeurs, J.M. Wetzer

Research output: Chapter in Book/Report/Conference proceedingConference contributionProfessional

2 Citations (Scopus)

Abstract

Modern society has become increasingly dependent on a reliable energy supply. As a result, asset managers at TSOs and DNOs have a strong focus on managing reliability and controlling risks, amongst others by complying with the ISO 55000 standard on asset management. Asset managers need to arrange the decision making such that the available OPEX (maintenance) and CAPEX (investments) budgets for the grid assets are used in an optimum way. In the decision making process, asset managers often use some form of asset health index in combination with a failure impact analysis to gain insight in the (impact of) asset condition and in order to identify the required interventions. This paper describes the complexity of this process, addresses the requirements that need to be fulfilled, and illustrates the solutions that are available. In particular, we address the possible bottlenecks, and ways to circumvent them, related to the impact of missing or low-quality data, dealing with uncertainties, handling multiple business values and KPIs, and taking into account costs and constraints. We have given an outline of the DNV GL asset management decision taking model (AHRM). Based on our experience with this model we have formulated a number of recommendations. One of the recommendations is a plea for asset data sharing between utilities.
Original languageEnglish
Title of host publicationAsset Management Conference (AM 2016)
PublisherInstitution of Engineering and Technology
Number of pages8
ISBN (Electronic)978-1-78561-367-8
ISBN (Print)978-1-78561-368-5
DOIs
Publication statusPublished - 17 May 2018
Externally publishedYes
EventAsset Management Conference (AM 2016) - London, United Kingdom
Duration: 23 Nov 201624 Nov 2016

Conference

ConferenceAsset Management Conference (AM 2016)
Abbreviated titleAM 2016
Country/TerritoryUnited Kingdom
CityLondon
Period23/11/1624/11/16

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