Projects per year
Uncertainty in operation and maintenance costs of offshore renewable installations can be incurred through failure to properly account for marine conditions. One such area, vessel utilisation scheduling, requires accurate forecasts of wind and wave conditions to minimise charter costs as well as plant downtime. Additionally, fuel usage and auxiliary costs will increase with longer transfer times. Exploiting auxiliary offshore measurement data and its relation to accessibility constraints could reduce idle charter periods by allowing operatives to better anticipate prevailing site conditions. Existing models omit the effect of direction on operations and fail to account for the complex relations between dependent environmental variables which can impact on operations such as crew transfers, lifting and jacking operations. In this paper, a methodology for improving the forecasting of offshore conditions through incorporating distributed meteorological and marine observations at multiple timescales is presented. Advancing towards a demonstration of a strategic maintenance approach of this kind will assist in both reducing direct costs and associated initial project finance. The developed model will be beneficial to developers and operators as better forecasting of when conditions are suitable for maintenance could reduce costs, lost earnings and improve mobilisation of vessels and technicians.
|Title of host publication||5th IET International Conference on Renewable Power Generation|
|Place of Publication||London|
|Number of pages||6|
|Publication status||Published - 23 Sep 2016|
|Event||International Conference on Renewable Power Generation 2016 - London, United Kingdom|
Duration: 21 Sep 2016 → 23 Sep 2016
|Conference||International Conference on Renewable Power Generation 2016|
|Abbreviated title||RPG 2016|
|Period||21/09/16 → 23/09/16|
FingerprintDive into the research topics of 'Wind and wave directional transit time model for offshore wind operation and maintenance'. Together they form a unique fingerprint.
- 1 Finished
1/10/09 → 31/03/18
Project: Research - Studentship