Decision Support Tool for Offshore Wind Farm Vessel Routing under Uncertainty

Abstract

This paper for the first time captures the impact of uncertain maintenance action times on vessel routing for realistic offshore wind farm problems. A novel methodology is presented to incorporate uncertainties, e.g., on the expected maintenance duration, into the decision-making process. Users specify the extent to which these unknown elements impact the suggested vessel routing strategy. If uncertainties are present, the tool outputs multiple vessel routing policies with varying likelihoods of success. To demonstrate the tool's capabilities, two case studies were presented. Firstly, simulations based on synthetic data illustrate that in a scenario with uncertainties, the cost-optimal solution is not necessarily the best choice for operators. Including uncertainties when calculating the vessel routing policy led to a 14% increase in the number of wind turbines maintained at the end of the day. Secondly, the tool was applied to a real-life scenario based on an offshore wind farm in collaboration with a United Kingdom (UK) operator. The results showed that the assignment of vessels to turbines generated by the tool matched the policy chosen by wind farm operators. By producing a range of policies for consideration, this tool provided operators with a structured and transparent method to assess trade-offs and justify decisions.

Analysis of the Use of Electric Drive Systems for Crew Transfer Vessels Servicing Offshore Wind Farms

“…Then after service work, the crews are again transported from the wind tower to the port or the residential ship. To minimize service costs [28], this process is subject to optimization regarding both its management [22,29,30], and the safe steering of the ship along a given route [31][32][33][34][35][36]. CTVs are intensively used during the operation of offshore wind farms and require frequent refueling, which is both expensive and time consuming.…”

A Comprehensive Review of Artificial Intelligence and Wind Energy

“…Decision making is oriented in two directions: planning (both short and long term) and variable assessment. Among planning tasks are to decide the best suited components [217,218], short or long term planning [159, 187], power prediction [219,220], route optimization [221,222], state definition [223,224], WT manufacturing [225], and risk assessment [226][227][228] and mitigation [229,230]. Variable assessment is aimed at defining the best suited variables to perform O&M tasks [231][232][233] and to reduce computational costs [211,234], as well as to predict fault apparition considering signal uncertainties [235][236][237] or failure probability [238,239].…”

A Bayesian hierarchical assessment of night shift working for offshore wind farms

“…This effort has been helped along by the development of O&M simulation tools of varying complexity, relating to both long‐term strategy 7,8 and day‐to‐day decision making 9–13 . On top of this, the advent of increasingly sophisticated tools for on‐site data collection, management and analysis is becoming steadily more influential.…”

“…This effort has been helped along by the development of O&M simulation tools of varying complexity, relating to both long-term strategy 7,8 and day-to-day decision making. [9][10][11][12][13] On top of this, the advent of increasingly sophisticated tools for on-site data collection, management and analysis is becoming steadily more influential. The majority of these, however, are in the area of conditional monitoring-so much so that it now predominates in the wider O&M research space.…”