Data accompanying Chapter 5 of the PhD Dissertation: Energy System Design and Operation of Hydrogen Fuelled Ships

<strong>Introduction: </strong>This dataset contains the results and inputs files collected as part of the Chapter 5 in the doctoral thesis of Mr. Foivos Mylonopoulos, Dipl.-Ing in Delft University of Technology, 2022-2026.The present dataset is made public to act both as supplementary data for the publications of F. Mylonopoulos and to offer other researchers the ability to use this data in their own work.This data is part of the SH2IPDRIVE project (Sustainable Hydrogen Integrated Propulsion Drives).The project is funded by the Netherlands Enterprise Agency (RVO: Rijksdienst voor Ondernemend Nederland) under the grant number MOB21013.<br><strong>Purpose of the dataset:</strong>This dataset was created to support the assessment of weather-driven operational variability and navigation safety impacts on ship power demand, energy system sizing, and lifetime cost, as presented in Chapter 5 of the PhD dissertation. It enables the reproduction of the weather-adjusted power profiles, capacity distributions and lifetime cost analyses under different metocean conditions and hydrogen fuel price scenarios. <br><strong>Description of the dataset:</strong>This dataset is provided as a single ZIP archive containing the Python-based simulation, post-processing, and plotting workflows used in Chapter 5. The archive includes two main simulation scripts: Weather_Laden_Ch5.py for laden condition and Weather_Ballast_Ch5.py for the ballast condition. These scripts use vessel speed and course over ground inputs from Speed_COG_power.xlsx and Speed_COG_power_Ballast.xlsx, respectively, and incorporate wind and wave parameters derived on a daily basis from ERA5 meteorological datasets (.nc files) to generate weather-adjusted power profiles.The remaining files in the archive support result visualization. All simulation outputs are summarized in Results_Ch5.xlsx. The script Capacity_Histograms_Plots.py generates fuel cell and capacity histograms for different power profiles. Vessel_profile_plots.py produces plots of power profiles under different weather conditions using input from the corresponding Excel file. Finally, NPV_TOTAL.py generates lifetime cost distributions for different hydrogen fuel price scenarios (3,6, and 9$/kg) using input from the corresponding Excel files. <br><strong>Dependencies:</strong>Python with PySCIPOpt (SCIP solver), ERA5 weather data are provided in NETCDF (.nc) format and read in Python. Microsoft Excel for .xlsx files