A Computational Tool for the Pro-Active Management of Offshore Farms
Operation and Maintenance (O&M) of offshore farms have been highlighted as one of the major contributors to the final cost of energy. Therefore, lower the costs related to such aspect is vital in order to speed up their access into the market. Several decision-making tools have been developed in different areas in the last decades. Unfortunately, many of these suffer a degree of approximation due to the lack of either reliable input data or capability to assess specific offshore tasks. In this work the authors address this problem developing a tool for the assessment of the optimal O&M procedures for offshore renewable energy farms. This uses Monte Carlo simulation, which permits to establish probability of exceedance and confidence intervals on the results obtained, to characterize and optimize the management of the farm. The model is expressly orientated towards offshore devices, and aims to reduce the assumptions generally needed in RAM (Reliability, Availability, Maintainability) analysis. Modelling possibilities offered by the implemented tool, as well as suggested practices for the optimisation of the management of offshore farms, are illustrated and discussed through the paper.
The work in this paper has been conducted within the multinational Initial Training Network (ITN) OceaNET, funded under the PEOPLE Programme (Marie Curie Actions) of European Union’s FP7. Mojo Maritime have provided access to Mermaid to support, and for integration with, this research.
CORE 2016, 2016-09-12, 2016-09-14, Glasgow