The influence of multiple working shifts for offshore wind farm O&M activities : StrathOW-OM Tool

Dalgic, Y and Lazakis, I and Dinwoodie, I and McMillan, D and Revie, M and Majumder, J; (2015) The influence of multiple working shifts for offshore wind farm O&M activities : StrathOW-OM Tool. In: Design and Operation of Offshore Wind Farm Support Vessels 2014. Royal Institution of Naval Architects, GBR.

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Offshore wind projects are moving towards deeper waters and more distinct locations in order to capture stronger winds and eventually increase power productivity. However, challenging climate conditions limit the operability and accessibility of the maintenance vessels significantly; therefore, the turbine downtimes due to vessel inaccessibility become dominant. Moreover, offshore wind farm operators in the UK only perform maintenance activities if there is enough daylight at the offshore wind farm in order to prevent potential accidents. These major difficulties influence the power production undesirably and increase the financial risks of the operating offshore wind farms. In this context, the focus of this research is the investigation of operational and financial benefits that multiple working shifts can bring to the operating offshore farms and the influence of the offshore wind farm location on the operational decisions. The operational simulations are performed by the offshore wind operational expenditure and logistics optimisation tool StrathOW-OM, which is developed by the University of Strathclyde and commercial partner organisations within Technology Innovation Centre (TIC) project. StrathOW-OM examines climate parameters (wind speed, wave height, and wave period) in the offshore wind farm location, size and operational characteristics of the maintenance fleet, failure rates of the turbine components. The operational simulations are performed through multiple scenarios in order to identify the most cost efficient solution. The developed methodology enables offshore wind farm operators to define the O&M fleet composition and highlights how the maintenance fleet is optimally scheduled on a daily basis.


Dalgic, Y, Lazakis, I ORCID logoORCID:, Dinwoodie, I ORCID logoORCID:, McMillan, D ORCID logoORCID:, Revie, M ORCID logoORCID: and Majumder, J;