Meteo dashboard execution phase

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Problem Statement
Weather conditions at offshore wind farm sites heavily determine the business case of offshore wind. Wind, waves and currents have a profound impact on i) project development and financing (wind resource and wake assessments), ii) project engineering (wind farm layout, foundation design, and wind turbine design) and iii) project construction, operation and maintenance (planning of offshore operations and forecasting, turbine accessibility). Reliable on‐site measurement and forecast data and intelligent processing of this data for decision making creates additional value (including higher yield and lower risks) and reduces the cost of offshore wind (improved maintenance strategies) for offshore project owners and operators. Improvements can be achieved in better planned offshore activities, better insight in aging processes of components of the wind farm leading to better planned maintenance and better designed structures and wind farm layouts due to better insight in loads and wake fields. Such aspects are increasingly important as offshore wind projects increase in size and in distance to shore.

Project Objective
The main objective of this project is to develop the Meteo Dashboard, which will be an integrated software system that collects, stores and presents measured and detailed (!) forecasted meteo‐ and detailed hydrodynamic data for decision making of maintenance activities in Proeftuin Leeghwater. At the start of the project it was expected that Proeftuin Leeghwater will be located at the RWE concession named Tromp Binnen. Once set up, the Meteo Dashboard can be made applicable to other offshore wind farms, with relatively small effort.

A second objective within the development of the Meteo Dashboard is to setup a forecasting system: a high‐resolution hydrodynamic modelling system that providesforecasts of waves, currents and water levels at each wind turbine location in the considered offshore wind farm. The forecasts will also be stored and presented by the Meteo Dashboard to support the decision making process.

Project Results
Based on the results of the preceding feasibility study for the Meteo Dashboard1 functional and technical requirements of the Meteo Dashboard were defined by Deltares. This was presented to the consulting partners RWE and Eneco and feedback was incorporated. The requirements formed the input for the development of the Meteo Dashboard software, which is based on Deltares’ operational software named Delft‐FEWS.

Furthermore, Deltares developed a hydrodynamic numerical model for the Tromp Binnen offshore wind farm for detailed wave and tidal forecasts. The resolution of the model enables distinction between individual wind turbines. The forecast is validated against available measurements, concluding that a relative strong correlation between the observations and the model results can be observed.

Together with weather forecasts, the measured data and wave forecastsis made presentable via a web‐ interface for operators to use for planning of operation and maintenance activities.

Project Conclusions
During the project RWE and Eneco were consulted for providing feedback on Meteo Dashboard. Following the feedback, it was concluded that for O&M, wave height is the most important parameter, followed by wave direction and, less important, current speed and current direction. But this will vary per sight. Therefore, the most relevant parameters are currently shown in the Meteo Dashboard. Also, it was brought forward that it is important to show and compare measurement and model data in one figure.

The general conclusion was that the system is applicable as such and is an added value for supporting the Operation and Maintenance phase of offshore wind farms.

The project result are described in a report that concludes with a list of recommendations for further optimising Meteo Dashboard. These recommendations will be considered in the next phase of the FLOW project (P201406_001) named Meteo Dashboard Validation Phase to further optimise the system. Both these projects will form a blueprint for future projects.

Project Contribution to cost and risk reduction of far‐offshore wind energy
The arguments for the Meteo Dashboard project resulting in cost and risk reduction of (far‐)offshore wind energy is as following:

The setup of a simple Operation and Maintenance decision making tool with more accurate forecast information will optimise O&M planning, resulting in less trips offshore;
Increase effective working time of O&M activities, with the development of knowledge rules for when (under which weather conditions) maintenance actions can be carried out;
Improve yield: due to more accurate forecast, early weather windows can be identified, subsequently WTG’s could be repaired faster;
Modelling the hydrodynamic and wave conditions at each wind turbine during the whole life time of the offshore wind farm will increase knowledge of the foundation and WTG loading;
Delivering data and thus knowledge of metocean conditions at all WTG locations is expected to result in increased certainty of loadings at specific WTGs, for better consideration of which turbine will require preventive maintenance;
Possibly the scour protection inspection regime could be adjusted according to conditions which have occurred at the site;
Possible extension of the life time of the offshore wind turbines, after structural integrity analyses based on the conditions which have actually occurred at the site;
Based on more accurate forecast, wind turbines can be switched to idle mode when unwanted combination of specific loadings is expected (for instance, extreme wind and wave conditions misaligned);
HSSE ‐ As additional benefit, the improved knowledge ofsite conditions and vessel accessibility will lead to safer working conditions for the O&M technicians. This is an important benefit, but cannot be quantified in terms of costs.

Although this is a feasibility study, the resulting outcome of the remaining work as described in the project proposal Meteo Dashboard, could lead to a cost reduction (LCoE) of approximately 0.5~1.0 %. Note that not all qualitative arguments as mentioned above could be quantified in the FLOW‐TKI Offshore Wind Cost model. Therefore, the cost reduction capacity of Meteo Dashboard could be even more significant in the end. Furthermore, the generated data by Meteo Dashboard will improve support R&D in offshore wind.