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Probabilistic Life Cycle Costing: A Monte Carlo Approach for Distribution System Operators in Sweden
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Investments in power systems are characterized by large investment costs and uncertainties doto extended time frame. New consumption patterns in the electricity grid, as well as an aginggrid calls for modernization, new solutions and new investments. Components in the electricalsystem is characterized by most of their costs that are caused after their acquisition. One stateof the art method in analyzing investments over long time frames and provide long-term costestimation is life cycle costing (LCC). In LCC a "cradle to grave"-approach is performed whichenables comparative cost assessment to be made. This thesis reviews the existing literature inprobabilistic life cycle costing and gives a step by step methodology for DSOs to systematicallyaddress uncertainty in cost and technical parameters.This thesis proposes a Monte Carlo sampling method in combination with a Markov Chainfailure model to model failures is providing a comprehensive method of reaching nancial benetwhen comparing dierent investment decisions. The model evaluates nancial implications andtechnical properties to demonstrate the total cost of components. This thesis analyses a casefor Swedish distribution system operators and their investment in transformers. The proposedmodel includes an all-covering model of costs and incentives. The main conclusion is that probabilisticlife cycle costing benets investment decisions and the applied method shows promisingresults in addressing uncertainty and investment risks. The developed PLCC model is used onan investment decision where two transformers are compared. Results shows that PLCC is apowerful tool and could be used in power system applications.

Abstract [sv]

Investeringar i kraftsystem kännetecknas av höga investeringskostnader och osäkerheter på grundav komponenternas långa livslängd. Nya konsumtionsönster och ett föråldrat elsystem efterfrågar mordenisering, nya lösningar och nya investeringar. Komponenter i elnätet karakteriserasav att den största delen av kostnader orsakas efter de förvärvats. En framstående metod för attanalysera investeringar som löper över långa tidsspann och som kan ge en kostnadsestimeringär livscykelkostnadsanalys. Inom livscykelkostnadsanalys tillämpas ett från vaggan till graventillvägagångssätt vilket möjliggör jämförelser av kostnader. Denna uppsats granskar existerandeforskning inom probabilistisk livscykelanalys och ger en steg-för-steg-metodik för att en distributionsnätsoperatör systematiskt skall kunna adressera osäkerheter relaterade till kostnader samttekniska parametrar.Denna uppsatsen föreslår en Monte Carlo-metod i kombination av en Markovkedja, för attmed en heltäckande metod nå finansiell jämförbarhet mellan olika investeringsbeslut. Denna uppsatsenanalyserar ett fall för en svensk distributionsnätsoperatör och dess investering i transformatorer.Den föreslagna modellen inkluderar en heltäckande modell för kostnader och incitamet.Huvudresultatet från den föreslagna metoden är att probabilistisk livscykelkostnadsanalys samtde använda metoderna visar lovande resultat för att adressera osäkerheter och risker vid investeringsbeslut.

Place, publisher, year, edition, pages
2017. , p. 62
Series
TRITA-EE, ISSN 1653-5146 ; 2017:152
Keywords [en]
Probabilistic life cycle cost, investment decision, Monte Carlo simulation, Markov Chain
Keywords [sv]
Probabilistisk livscykelkostnad, investeringsbeslut, Monte Carlo-simulering, Markovkedja
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-218293OAI: oai:DiVA.org:kth-218293DiVA, id: diva2:1160364
Available from: 2017-11-27 Created: 2017-11-27 Last updated: 2017-11-27Bibliographically approved

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