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Meteo Dashboard for cost effective operation of offshore wind farms

Project description

Feasibility study improving the cost effective operation of offshore wind farms by collecting real-time meteorological data.


Project summary

The cost effectiveness of offshore wind farms is strongly influenced by the weather conditions at the site of the wind farm. Income from energy production can be increased with more efficient wind farm layouts based on improved wake models, with better control strategies and with enhanced wind speed forecasting. On the other hand, costs can be reduced with improved maintenance strategies based on a better understanding of the loads due to the wind, wave and current climate, as well as the limits to access due to harsh conditions. The current practice of using operational and site condition data can be expanded and improved. To further this aim, a feasibility study has been carried out about a MeteoDashboard: an integrated hardware and software system, which is able to collect, store, process, and present a wide variety of operational and site data of an offshore wind farm, which can provide the operator with relevant information to monitor the performance of the wind farm and to support his decisions to optimise operation and maintenance. Besides presenting collected data, the Meteo Dashboard will process this data to enable forecasting of meteo conditions, energy production and accessibility.


Content of the study

The feasibility study was carried out by execution of four work packages:

WP 1.1 Technical Specifications for Meteo Dashboard: In this study carried out by ECN, the functional and requirements for information collection and processing of the Meteo Dashboard have been specified. To come to these requirements, joint workshops were setup which included participants from the operational team of Prinses Amaliawindpark, ECN, and TU Delft. Besides technical and functional requirements, this WP specifies which knowledge rules need to be developed to enable support in maintenance decisions and forecasting.

WP 1.2 Measurement Plan for Prinses Amaliawindpark: The development of the Meteo Dashboard will be done in close cooperation with the Prinses Amaliawindpark, and as a pilot the system will be implemented at this wind farm to prove viability. To enable this, a study was carried out to setup a measurement plan. The objective of this plan is to specify in detail the signals that will be measured, the hardware that will be used in the meteorological measurements, and the work that will be carried out during the preparation, the installation and the commissioning of the measuring system. It was concluded that measurements should be carried out on wind, waves, current, visibility, precipitation, lightning and others. Furthermore, a list the total set of signals required for implementation of the Meteo Dashboard is specified, as well as required equipment.

WP 1.3 Measurement Plan for Scaled Wind Farms: In order to improve wake modelling, it is foreseen that data from the Meteo Dashboard can be used in conjunction with data from scaled wind farms. The rationale of this is that implementation of extensive instrumentation on a full scale wind farm is very costly. Combining full scale measurements with scaled measurements enables to capture the benefits of both measurement types. In this study, a measurement plan for the ECN Scaled Wind Farm is setup, which enables improvement of wake modelling and the study of wake effect reducing concepts. The results detail how measurements on a scaled wind farm could be complementary to the Meteo Dashboard in improving knowledge on wake effects. It includes the type of measurements possible in the scaled wind farm, and the contribution of each of these measurements to knowledge improvement.

WP 1.4 Business Plan: The fourth and final work package of the feasibility study consists of the business plan for realisation of the Meteo Dashboard. The business plan includes the costs and benefits of realising the Meteo Dashboard, and investigates the possibilities for financing and partnering in the project. The results of this WP show that the estimated cost of development, Far and Large Offshore Wind innovation program P201101-003-ENE CONFIDENTIAL 3/11 implementation and 2 years of operation of the Meteo Dashboard are in the order of 1 million €. The benefits will be highlighted in the next section: conclusion and contribution to FLOW targets.


Conclusion and contribution to the FLOW targets

The final conclusion of the feasibility study is that the development of a (prototype) Meteo Dashboard is feasible.

The benefits of the Meteo Dashboard are:

  • Improved O&M strategies with better data on the weather limits for vessels and maintenance actions;
  • Increased 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;
  • Improved HSSE processes for offshore work;
  • Verification of the energy production that was estimated in the planning phase of the wind farm;
  • Verification of the performance of the wind turbines and wind farm (power curve analysis);
  • Verification of design lifetime of the wind farm, compare the actual offshore conditions to the design assumptions;
  • Tune and optimise the energy production forecasting method and adjust the wind farm controller to better meet the forecasted output; and
  • Set up a database with meteorological data that can be used for R&D, including more accurate planning of new wind farms (both energy production estimation and the estimation of O&M aspects and availability), wake model validation and other FLOW research.

Finally, a quantitative assessment of the potential contribution of the Meteo Dashboard to cost reduction of offshore wind energy was made.

A multitude of potential areas for cost reductions were identified. The most promising are:

  1. Improved knowledge of site conditions in the operational phase, and limits of access vessels for planning and access strategy: Potentially increased effective work time which leads to: 12% reduction in staff + 5% reduction in trips1 = €210k/year (100 MW)
  2. Validation and Improvement of Wake Models and Improvement of Energy Production Estimates: Reduction in uncertainty - improved P90 Improved IRR Potentially 1.6% less uncertainty = 1.6% reduction in P90/P50 = IRR + 0.16%
  3. Improvement to Wind Farm Design: Better design, reduced wake losses, Improved energy yield Potentially 1% improved yield = €165k yearly increase (grey price, 100 MW) = €1.65M yearly increase (grey price, 1 GW)
  4. Improved support structure design: Reduction in overall steel weight of 1-5 % = 25.8k -130k€/WTG

The positive outcome of this feasibility study was the reason to start the next phase which has been approved by FLOW: ‘Meteo Dashboard execution phase’ (P201203-009-ENE).

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