Impact of Data Quality on Power System AssetManagement - A Monte-Carlo Based Approach

• In power system asset management, component datais crucial for decision making. Consequently, the quality level ofdata has a great impact on the optimality of asset managementdecisions. The goal of the paper is to quantify the impact ofdata errors from a maintenance optimization perspective usingrandom population studies. In quantitative terms, the impact ofdata quality can be evaluated financially and technically. In thispaper, the financial impact is the total maintenance cost per yearof a specific scenario in a population of components, whereasthe technical impact is the loss of a component’s useful technicallifetime due to sub-optimal replacement time. Using Monte-Carlosimulation techniques, those impacts are analyzed in a case studyof a simplified random population of independent and nonrepairablecomponents. The results show that missing data hasa larger impact on cost and replacement year estimation thanthat of under- or over-estimated data. Additionally, dependingon problem parameters, after a certain threshold of missingdata probability, the estimation of cost and replacement yearbecomes unreliable. Thus, effective decision making for a certainpopulation of components requires ensuring a minimum level ofdata quality.

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

power distribution

Electrical Engineering

Elektro- och systemteknik

Publikations- och innehållstyp

vet (ämneskategori)

ovr (ämneskategori)