Optimization of the operation and maintenance planning of offshore wind farms
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Report (1,847Mb) (Accés restringit)
Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/169723
Tutor / directorPinson, Pierre
Realitzat a/ambDanmarks tekniske universitet
Tipus de documentProjecte Final de Màster Oficial
Data2018
Condicions d'accésAccés restringit per decisió de l'autor
Tots els drets reservats. Aquesta obra està protegida pels drets de propietat intel·lectual i
industrial corresponents. Sense perjudici de les exempcions legals existents, queda prohibida la seva
reproducció, distribució, comunicació pública o transformació sense l'autorització del titular dels drets
Abstract
Offshore wind energy is rapidly advancing as one of the cutting-edge renewable energy
sources towards the global decarbonization goal. However, offshore wind energy is still
twice as expensive as onshore wind. The Operational Expenses (OPEX) are responsible
for a substantial portion. They constitute 25 to 30% of the total costs. Therefore, it is
essential that market-leading operators like Ørsted redefine their maintenance strategies to
make the sustainable technology more competitive. Digitalization has opened the doors to
monitor the health state of the wind turbines and apply maintenance based on the risk
to failure, but little investigation has been conducted to understand what is the actual
impact of shifting to a condition-based maintenance strategy.
This thesis develops a decision support tool for identifying the most cost-effective solutions
for the medium to long-term maintenance planning of offshore wind farms. The model is
based on time domain Monte Carlo simulations that analyze weather conditions, i.e., wind
speed and wave height, models wind turbine failures and transportation systems such as
Crew Transfer or Jack-up vessels, and schedules corrective, preventive and condition-based
tasks. The model is tested on a hypothetical 80 wind turbine wind farm in the North Sea
for a 10 years operation. The results show that Time-based Availability and Energy-based
Availability increase more than 2% with a condition-based strategy. Production losses are
reduced 10.72%
TitulacióMÀSTER UNIVERSITARI EN ENGINYERIA INDUSTRIAL (Pla 2014)
Col·leccions
Fitxers | Descripció | Mida | Format | Visualitza |
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Master_thesis_Guillem_Blanco_Sagues.pdf | Report | 1,847Mb | Accés restringit |