Application of Monte Carlo simulation for the assessment of the availability of an offshore substation
Author
Seresina, Luca Emanuele
Term
4. term
Education
Publication year
2020
Submitted on
2020-01-10
Pages
99
Abstract
This thesis examines how often an offshore substation is operational (availability) while accounting for uncertainty. We use Monte Carlo simulation in the general-purpose programming language R. Monte Carlo means running many randomized trials so the model captures natural variability and uncertainty in the inputs. We first build a generic model of an offshore substation and then create a case study from it. Availability is calculated based on how frequently components fail, how quickly operations and maintenance (O&M) resources can be mobilized, and how long repairs take. Data and assumptions were gathered with support from industry experts. We also conduct a sensitivity analysis to see how results change when key assumptions are varied. This helps discuss the model’s robustness and identify the main drivers of the outcomes. In addition to availability, the case study computes relevant economic measures. The results indicate that Monte Carlo modeling in R—even at an early stage—can support the development of tools for availability assessment and help increase expert confidence in evaluations used for project development.
Denne afhandling undersøger, hvor ofte en offshore transformerstation er i drift (tilgængelighed), når der tages højde for usikkerhed. Vi bruger Monte Carlo-simulering i det generelle programmeringssprog R. Monte Carlo betyder, at modellen kører mange tilfældige gentagelser for at afspejle naturlig variation og usikkerhed i inputdata. Vi opbygger først en generisk model af en offshore transformerstation og laver derfra et konkret casestudie. Tilgængeligheden beregnes ud fra, hvor ofte komponenter fejler, hvor hurtigt ressourcer til drift og vedligeholdelse (O&M) kan mobiliseres, og hvor lang tid reparationer tager. Data og antagelser er indsamlet med støtte fra brancheeksperter. Vi gennemfører også en sensitivitetsanalyse, som undersøger, hvordan resultaterne ændrer sig, når centrale antagelser varieres. På den måde kan vi diskutere modellens robusthed og de vigtigste drivere bag resultaterne. Ud over tilgængelighed beregner casestudiet også relevante økonomiske mål. Resultaterne viser, at Monte Carlo-modellering i R – selv på et tidligt udviklingsstadie – har potentiale til at understøtte værktøjer til tilgængelighedsvurdering og øge eksperters tillid til beslutningsgrundlaget i projektudvikling.
[This apstract has been rewritten with the help of AI based on the project's original abstract]
Keywords
availability ; RAM ; substation ; offshore ; wind energy ; risk ; uncertainty ; risk management