A framework for component ranking based on a data quality importance index : applications in power system asset management

•  Data-driven decision making is essential for efficient power system asset management. Faulty data causes distortions in component failure model estimations. This leads to inaccurate maintenance cost minimization and sub-optimal component replacements. In this paper, we review existing standards and frameworks related to data quality and asset management. We then study the sensitivity of a maintenance optimization model to the Weibull distribution shaping parameter and observe a non-linear relation. Based on this study, we propose using the Weibull shaping parameter as a data quality importance index to rank power system components in terms of data requirements. 

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Annan elektroteknik och elektronik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Other Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)

Nyckelord

asset management

data quality

maintenance

framework

failure model

Electrical Engineering

Elektro- och systemteknik

Publikations- och innehållstyp

vet (ämneskategori)

ovr (ämneskategori)