|dc.description.abstract||This PhD work has been carried out when early experience is obtained from the first offshore wind energy projects and new projects with large capacity are in preparation. The importance and challenges of operation and maintenance (O&M) in offshore wind farms are realized both in industry and academia. Onshore wind turbines achieve an availability of 95 – 99 % and generate electricity with competitive price in the market. However, the availability of offshore wind turbines (OWTs) is much less favourable and the cost of offshore wind energy is 1.5 times or more than onshore wind energy. O&M, which contributes to about 30 % of the total cost of offshore wind energy, has a large potential for cost reduction, but is a challenging task due to the harsh weather impacts and limitations of support resources.
The focus of this PhD thesis is to investigate and develop methods for improving safety and efficiency of O&M in offshore wind farms. Safety concerns the subassemblies and components in the wind farm, but also the technicians who travel to individual turbines for maintenance services. Efficiency is mainly related to the optimization of the maintenance support organization in offshore wind farms. The reduction of O&M costs is not directly addressed in the PhD project, but the research results are expected to be a contribution.
The work presented in this thesis reviews current methods and approaches used for maintenance planning, access design and operation, and life cycle engineering in offshore wind farms. Several research objectives are specifically defined, and the main contributions of this thesis are:
Maintenance planning is a complicated decision–making process that involves the major stakeholders and the main life cycle phases of an engineering system. Considering availability as an important indicator of the system performance and the significant impact from logistics support on availability, an availability centred maintenance (ACM) approach is proposed. The application of the approach has the potential to provide a competitive advantage in the long–term maintenance operations of offshore wind farms. An offshore wind farm normally comprises a large number of turbines which demand frequent maintenance visits. In addition to making maintenance plans that avoid downtime and production losses, it is important to utilize the expensive resources, such as service vessels, in an efficient way. This thesis introduces the routing and scheduling problem of a maintenance fleet for offshore wind farms, which is to determine the optimal assignments of turbines and routes to the vessels in terms of cost. The mathematical formulations of this problem is presented and verified with a computational case study. Collisions between service vessels and offshore wind turbines (OWTs) are paid little attention to in the offshore wind energy industry. To fill the research gap, this thesis proposes a risk assessment framework for such collisions and investigates the magnitude of the collision risk and important risk-influencing factors. The fast growth of the current wind energy industry has stimulated rapid solutions and low costs. Hardware systems gain emphasis, while “soft” aspects and system synthesis get less focus. In this thesis, a framework is proposed for integrating task analysis into the general system development process as a supplement to the development of hardware systems and operation procedures. Among the various subsystems of an OWT, the protection systems are of utmost importance, since any failure of these systems may lead to serious accidents. As a contribution to improving the reliability of the protection system and ensuring the safety of OWTs, this thesis discusses how an OWT can be designed to fulfill the requirements of IEC 61508; the most important standard for protection systems. In addition, this PhD work develops a framework based on a life cycle model for integrating reliability, availability, maintainability and safety (RAMS) in the development of offshore wind farms, and an alternative method for modeling the operation of service vessels for offshore wind farms by using stochastic activity networks (SANs).
The thesis summarises the work performed and results obtained in the end. There are several areas of further research. One major area is to improve the new approaches and frameworks in this PhD project with updated information and industry data, and through the implementation of these approaches and frameworks in industrial applications.||nb_NO