Willow Concept
WILLOW integrated system will provide an open-source, data-driven smart curtailment solution to the Wind Farm Operators with the basis of an integrated Wind Farm Control system looking for a trade-off between the power production and the lifetime consumption.
Objetives
1
2
3
- Global Structural Health Monitoring (SHM) system for the tower/transition piece and foundations based on loads, accelerations, images, thickness losses considering fatigue, pitting corrosion and coating degradation by using physical and virtual sensors combined with Machine Learning techniques.
- Prognosis tools to predict the consumed lifetime (CL) and remaining useful life (RUL) by combining SCADA and SHM data using physical models and ML methods. Anomaly detection methods based on historical data considering damages and prognosis data.
- Decision-making support tool for smart power dispatch in curtailed conditions and O&M scheduling. To determine how much power to be extracted from each turbine in present, near and far future to satisfy grid, market and lifetime constraints.
(WP2)
The objective of this Work Package is to design an integrated Structural Health Monitoring System. The goal is to be able to detect, identify and quantify structural damages (coating degradation, pitting corrosion) combined with precise estimation of different kind of loads and complemented with drone-based visual and thermographic inspections. WP2 will receive specific requirements from WP1 considering the defined use cases in task 1.1. Furthermore, WP2 will follow the cybersecurity strategies defined in task 1.4 for the design of the continuous monitoring system and for the drone operations. The data output of the developed structural health monitoring system is the crucial input to WP3, to reinforce and augment the capabilities of providing a more precise lifetime assessment of the status of the offshore towers including the transition piece and foundations.
(WP3)
The objective of this Work Package is to move from the component/individual turbine level to the level of the windfarm. The objective is to setup a methodology for farmwide lifetime assessment & novelty detection hereby combining SCADA data, Meteo data and enriched by additional data on the component /individual turbine level (WP2) allowing more accurate estimations. In a second step these data-driven farmwide load and corrosion estimates will be used as input for lifetime assessment exercises and novelty detection for improved O&M optimisation, load-driven control and lifetime extension strategies on a windfarm level (WP4).
(WP4)
The objective of this work package is (i) to characterise the cost- reduction potential of wind farm power dispatch control through its prolongation of remaining useful lifetime in curtailed conditions, and (ii) to exploit this potential through a smart curtailment solution for use by WFOs valid for up to 20 MW turbines. A third objective is to provide decision support for manned inspection planning (such as drone inspections in WP2).