Influence of statistical uncertainty of component reliability estimations on offshore wind farm availability

Offshore wind turbine reliability, one of the industry's biggest sources of uncertainty, is the focus of the present paper. Specifically the impact of uncertain component failure distributions at constant failure rates has been investigated with respect to its implications for wind farm availability. A fully probabilistic offshore wind simulation model has been applied to quantify results; effects shown in this paper underline the significant impact that failure probability distributions have on asset performance evaluation. It was found that wind farm availability numbers may vary in the range up to 20 % just by changing the distributions of failure to a different pattern; in particular those scenarios in which extensive failure accumulation occurred led to significant losses in production. Results are interpreted and discussed mainly from the viewpoint of an offshore wind farm developer, owner and operator, with implications underlined for application in state-of-the-art offshore wind O&M (Operations and Maintenance) models and simulation tools

Influence of statistical uncertainty of component reliability estimations on offshore wind farm availability

Offshore wind turbine reliability, one of the industry's biggest sources of uncertainty, is the focus of the present paper. Specifically the impact of uncertain component failure distributions at constant failure rates has been investigated with respect to its implications for wind farm availability. A fully probabilistic offshore wind simulation model has been applied to quantify results; effects shown in this paper underline the significant impact that failure probability distributions have on asset performance evaluation. It was found that wind farm availability numbers may vary in the range up to 20 % just by changing the distributions of failure to a different pattern; in particular those scenarios in which extensive failure accumulation occurred led to significant losses in production. Results are interpreted and discussed mainly from the viewpoint of an offshore wind farm developer, owner and operator, with implications underlined for application in state-of-the-art offshore wind O&M (Operations and Maintenance) models and simulation tools

Whole body vibration on offshore structures: an evaluation of existing guidelines for assessing low-frequency motions

An extensive literature research has been conducted to create an insight into the existing norms and standards regulating the assessment of human exposure to motions in offshore environments. A summary of current threshold values and their specific fields of application is included. The presented literature is analysed with respect to their applicability for assessing low frequency oscillatory motions of floating offshore wind turbines to which technicians are exposed during maintenance tasks. The review identifies the need for a consistent assessment method in combination with threshold values for floating structures

A systematic failure mode effects and criticality analysis for offshore wind turbine systems towards integrated condition based maintenance strategies

Condition-based maintenance is applied in various industries to monitor and control critical assets and to optimize maintenance efforts. Its applicability to the offshore wind energy industry has been considered for almost 20 years and has resulted in the development and implementation of solutions that have contributed to lower cost of maintenance and increased asset availability. However, there is currently no public domain guidance available that provides the information required to (i) prioritize systems for which condition monitoring would generate highest value and to (ii) understand the parameters that need to be monitored by a specific system from failure cause to failure mode. Both items are addressed in this paper, providing a clearly structured, risk-based assessment methodology and corresponding results for state-of-the-art offshore wind turbines. A total of 337 failure modes have been identified and analysed by experts representing approximately 70% of the European offshore wind market to assess potential benefits of condition monitoring systems. Results may be used to target the development of condition monitoring systems focusing on critical systems and to find optimal O&M strategies by understanding failure paths of main offshore wind turbine systems resulting in a lower cost of energy and a more optimal risk-return balance

Influence of extended potential-to-functional failure intervals through condition monitoring systems on offshore wind turbine availability

Condition monitoring systems are deployed in various industries for decades contributing to optimizing operational performance and maintenance efforts. Several publications address this potential for application in the offshore wind energy industry; however, none attempts to quantify the impact that longer warning times ahead of a failure would have on asset availability. The aim of this paper is to bridge this gap by considering particularly the access restrictions for offshore operations through a probabilistic model which simulates existence of different condition monitoring systems on offshore wind turbines in the time domain. Results of this study quantify the positive impact that a longer warning time of potential-to-functional failure (P-F interval) has on availability, highlighting that variation of maintenance strategy through transformation of unplanned activities into planned interventions that can be conducted during a suitable weather window ahead of a component failure can lead to reduced operation and maintenance (O&M) costs

Maintenance Strategies for Large Offshore Wind Farms

Up to one third of the total cost of energy from offshore wind generation is contributed by operation and maintenance (O&M). Compared to its onshore counterpart, this fraction is significantly higher. Costs are not only caused by spare-parts and repair actions, but also by production losses due to downtime. The accessibility of a turbine in case of a failure is one main aspect affecting downtime. Therefore, a tool has been developed and implemented in MATLAB to simulate the operating phase of a wind farm with special emphasis toward the modeling of failures and repair. As an example application, a site at the UK east coast was chosen, and a few distinct scenarios were considered. Results include how sensitive availability changes with respect to changes in maintenance fleet and maintenance scheduling strategy. A quantification of potential cost savings due to an increase in availability is also stated

Effect of Load Sequence and Weather Seasonality on Fatigue Crack Growth for Monopile-based Offshore Wind Turbines

Offshore wind turbines are subjected to variable amplitude loading, but the impact of load sequence is commonly neglected in fatigue analysis. This paper presents an initial investigation if load sequence and weather seasonality influence fatigue crack growth for monopile-based offshore wind turbines. Focus is on the load sequence effect introduced by the non-linearity of crack propagation. Fatigue crack growth at two structural hot spots was analyzed with a fracture mechanics model applying Paris’ law. The model was calibrated to yield an identical lifetime as a SN-curve analysis. Input into the fracture mechanics model are structural stresses due to environmental and operational loading. Weather seasonality was simulated with a Markov model. Results show that loading sequence has only a negligible effect on crack sizes under the assumption made in this study. This makes fatigue lifetime predictions independent of weather seasonality. However, it becomes relevant for the prediction of future propagation of detected fatigue cracks throughout the year