Iain Dinwoodie

Reference cases for verification of operation and maintenance simulation models for offshore wind farms

Due to lack of operating experience in the field of offshore wind energy and large costs associated with maintaining offshore wind farms, there is a need to develop accurate operation and maintenance models for strategic planning purposes. This paper provides an approach for verifying such simulation models and demonstrates it by describing the verification process for four models. A reference offshore wind farm is defined and simulated using these models to provide test cases and benchmark results for verification for wind farm availability and O&M costs. This paper also identifies key modelling assumptions that impact the results. The calculated availabilities for the four models show good agreement apart from cases where maintenance resources are heavily constrained. There are also larger discrepancies between the cost results. All the differences in the results can be explained by different modelling assumptions. Therefore, the models can be regarded as verified based on the presented approach.

Analysis of Offshore Wind Turbine Operation and Maintenance Using a Novel Time Domain Meteo-Ocean Modeling Approach

This paper presents a novel approach to repair modeling using a time domain Auto-Regressive model to represent meteo-ocean site conditions. The short term hourly correlations, medium term access windows of periods up to days and the annual distibution of site data are captured. In addition, seasonality is included. Correlation observed between wind and wave site can be incorporated if simultaneous data exists. Using this approach a time series for both significant wave height and mean wind speed is described. This allows MTTR to be implemented within the reliability simulation as a variable process, dependent on significant wave height. This approach automatically captures site characteristics including seasonality and allows for complex analysis using time dependent constaints such as working patterns to be implemented. A simple cost model for lost revenues determined by the concurrent simulated wind speed is also presented. A preliminary investigation of the influence of component reliability and access thresholds at various existing sites on availability is presented demonstrating the abiltiy of the modeling approach to offer new insights into offshore wind turbine operation and maintenance.

Wave height forecasting to improve off-shore access and maintenance scheduling

This paper presents research into modelling and predicting wave heights based on historical data. Wave height is one of the key criteria for allowing access to off-shore wind turbines for maintenance. Better tools for predicting wave height will allow more accurate identification of suitable “weather windows” in which access vessels can be dispatched to site. This in turn improves the ability to schedule maintenance, reducing costs related to vessel dispatch and recall due to unexpected wave patterns. The paper outlines the data available for wave height modelling. Through data mining, different modelling approaches are identified and compared. The advantages and disadvantages of each approach, and their accuracies for a given site implementation, are discussed.

Statistical forecasting for offshore wind helicopter operations

The influence of the wind and wave climate on offshore wind operations and maintenance is well known. These environmental factors dictate to a large extent whether turbine crew transfer (carried out by small vessels) or major lifting actions (carried out by large vessels) can be executed at sea. However the role of helicopter operations has received much less attention. In this paper the authors explore the helicopter access problem via statistical forecasting and implement a model innovation, by including cloud base as a key access metric. By understanding the practical limits of helicopter operation, offshore wind access calculations will be much improved and reflect more closely the reality of operations at sea.