The university of tokyo master thesis

THE UNIVERSITY OF TOKYO


MASTER THESIS




ASSESSMENT OF CAPITAL EXPENDITURE COST FOR OFFSHORE WIND FARM BY USING DISCRETE EVENT SIMULATION


BY

SHUKURJONOV KUHINUR DONIYOR UGLI

A thesis is submitted for the degree of
Master of Engineering
in the field of Civil Engineering

Summer 2021.


Abstract.
In 2020, the Government of Japan set its offshore wind energy targets to have 10 GW by 2030 and 30-45 GW by 2040. Reducing the levelized cost of energy (LCOE) for offshore wind energy is critical to achieve these targets. The offshore wind farm installation cost is affected by the workability which is the ratio of workable days to the whole installation days. Here, the workable day is when the environmental conditions are less than the criteria of each installation vessels and methods. Conventionally, the workability for each installation phase was evaluated by the cumulative occurrence probability of environmental conditions, which does not consider the sequential nature of offshore operations. The uncertainty of the workability due to the long-term variations of the environmental conditions is important to be assessed quantitatively. The evaluation of CAPEX uncertainty is important to make the cost reduction scenario. The previous CAPEX model only evaluates the mean value and there was no model for evaluating the uncertainty.
In this study, a discrete event simulation tool for the assessment of workability for offshore wind farm is developed considering the sequential nature of installation. Then, the evaluation of workability uncertainty is performed by using the proposed discrete event simulation tool and the long term simulated environmental data of different offshore sites in Japan. Finally, an uncertainty model of CAPEX for offshore wind farms with considering the evaluated workability uncertainty is proposed.
Firstly, the discrete even simulation tool for the assessment of workability with considering the sequential nature of offshore wind farm installation process is developed. The developed tool considers three weather conditions of wind speed, significant wave height and wave period. Predicted workability for bottom preparation, installation of substructure and wind turbine showed a good agreement with the actual record at Choshi offshore demonstration project.
Then, the uncertainty of workability due to the yearly variated weather conditions was assessed by using the proposed discrete event simulation at Akita, Kitakyushu and Fukushima. The simulated nine-year weather condition data are used, which were predicted by mesoscale models from 2006 to 2014. Fukushima site showed higher coefficient of variation (CoV) of workability with comparing to Akita and Kitakyushu when the installation criteria is low, but the difference of CoV becomes less when the installation criteria is high, which suggests that the larger vessels reduces the risk. The uncertainty of workability was decreased by increasing of installation period from 1 year to 3 years, which suggests that the larger wind farm installation has less risk.
Finally, the uncertainty model of CAPEX is proposed assuming the normal distribution for each variable. The coefficient of variation for each variable are assessed from the collected experienced data and assumed to be constant. The uncertainty of workability is evaluated by the proposed discrete event simulation tool. The simulated CoV of CAPEX without considering workability’s uncertainty underestimates the recorded CoV, but those with considering the uncertainty of matches better with the actual CoV for 30 wind farms in UK, which indicates the importance of considering workability’s uncertainty effect. The proposed uncertainty method will be able to use for proposing Japan LCOE reduction scenarios.