Probabilistic access forecasting for improved offshore operations

Ciaran Gilbert, Jethro Browell and David McMillan

International Journal of Forecasting, 2021, vol. 37, issue 1, 134-150

Abstract: Improving access is a priority in the offshore wind sector, driven by the opportunity to increase revenues, reduce costs, and improve safety at operational wind farms. This paper describes a novel method for producing probabilistic forecasts of safety-critical access conditions during crew transfers. Methods of generating density forecasts of significant wave height and peak wave period are developed and evaluated. It is found that boosted semi-parametric models outperform those estimated via maximum likelihood, as well as a non-parametric approach. Scenario forecasts of sea-state variables are generated and used as inputs to a data-driven vessel motion model, based on telemetry recorded during 700 crew transfers. This enables the production of probabilistic access forecasts of vessel motion during crew transfer up to 5 days ahead. The above methodology is implemented on a case study at a wind farm off the east coast of the UK.

Keywords: Wind energy; Offshore access; Probabilistic forecasting; Multivariate forecasting; Forecast visualisation; Generalised additive models (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:37:y:2021:i:1:p:134-150

DOI: 10.1016/j.ijforecast.2020.03.007

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