This folder contains all the data and code used in:
Papadopoulos, P., Coit, D.W. and Ezzat, A.A., 2022. Seizing Opportunity: Maintenance Optimization in Offshore Wind Farms Considering Accessibility, Production, and Crew Dispatch. IEEE Transactions on Sustainable Energy, 13(1), pp.111-121.
Please use the reference above if you use parts of the code or data
All the parts of the analysis performed in the paper have been concatenated into a single python notebook: Main_code.ipynb
To execute the cells in this notebook, all the data and code must be downloaded and saved in the same folder.
-
Main_code.ipynb: Contains all the code necessery for the analysis of the paper, from data importing, processing and result analysis. -
benchmarks.py: Contains the benchmark adaptations of HOST for the comparison of different strategies. Each benchmark is a function called within the Main_code. -
{HOST, BESN, PBOS, TBS, CMS}.xlsx: Excel files that contain precalculated metrics for 30 weather scenarios used in the analysis of Case Study I in the paper. -
{HOST, BESN, PBOS, TBS, CMS}2_10wt_var_price5.json: JSON files containing the optimal schedules and metrics obtained by solving for 30 weather scenarios, used in the analysis of Case Study II in the paper. -
method_of_bins.csv: A csv file containing data used for the binning method and the construction of the power curve. -
da_hrl_lmps_ZONE2014.csv: A csv file containing raw hourly electricity price data used in Case Study II, downloaded from PJM data miner 2. -
wind_wave_data.csv: A csv file containing pre-processed hourly wind speed and wave height data, downloaded from NYSERDA.