PROOF OF CONCEPT FOR A COORDINATED WIND TURBINE CONTROL DEVICE ON HYBRID OFFSHORE PLATFORMS
(MatrixWT_PoC)
PCD2025-165016-C21
The primary objective of this project (UCM) is to improve the efficiency, reduce maintenance, and increase the reliability of hybrid FOWT-OWC platforms by implementing advanced and intelligent wind turbine control strategies on a physical device. During the project, the turbine control strategies will be integrated to dynamically adapt to the changing environment in which it operates. Expected outcomes include reduced fatigue, extended component life, and more efficient and stable power generation.
The specific objectives are as follows:
- Implement the Matrix Controller, a physical control device that executes the advanced multi-objective control strategies developed in the previous project, specifically for the floating offshore wind turbine. These control approaches will seek to reduce structural vibrations, mitigate platform oscillations, and improve the overall energy efficiency of the system. The controller will use real-world operating data to refine and adjust the algorithms for practical implementation. The necessary electromechanical adaptations will also be designed to integrate the control device into the FOWT structure.
- Build and test small-scale prototypes of floating offshore wind turbines, equipped with representative control architectures, including blade pitch control and turbine electrical load control.
- Conduct a rigorous experimental validation program in wave tank environments. This will include testing the prototype turbines in relevant scenarios to assess the stability and performance of the control systems, providing crucial data for future large-scale deployment.
MULTI-RESOURCE MARINE ENERGY PLATFORM WITH INTELLIGENT SELF-REGULATION AND PREDICTIVE MAINTENANCE TO EXTEND TURBINE LIFE (PORTEUS)
PID2024-155653-OB-C21
STABILIZATION, MAINTENANCE AND INTELLIGENT SELF-REGULATION OF A MULTI-RESOURCE MARINE ENERGY PLATFORM BY WIND TURBINE CONTROL (SEA-STAR1)
The coordinated project proposes to address the challenges of the energy transition by developing an intelligent self-regulating multi-resource energy platform that integrates a floating wind turbine (WT) with oscillating water columns (OWCs), which interact with each other to stabilize the device and reduce vibrations. By combining advanced intelligent control strategies and predictive maintenance, the project aims to provide a comprehensive solution that improves the performance, reliability and lifetime of offshore wind platforms, while minimizing the impact on marine biodiversity.
Subproject 1 will focus on the design and implementation of advanced control and load mitigation strategies to extend the operational life of wind turbine components and reduce maintenance. This wind turbine control will be synchronized with hydrodynamic control methods designed to dampen the platform motions by adjusting the opening surface of the OWCs developed in subproject 2. In addition, machine learning algorithms and other data-driven approaches will be applied to detect anomalies, predict failures and optimize maintenance planning, ensuring operational efficiency and cost reduction of the wind turbine.
These solutions will be integrated into a self-learning supervisory control system to enable cohesive operation of the wind turbine and OWC systems, balancing load reduction, power production and maintenance actions. The holistic control approach will consider different criteria to balance energy efficiency, remaining useful life (RUL) of the wind turbine and marine biodiversity conservation.
SUPERVISION AND CONTROL OF HYBRID MARINE PLATFORMS (MatrixWW)
PID2021-123543OB-C21
SUPERVISION AND CONTROL OF OFFSHORE WIND TURBINES (SuMariNeW)
The main objective of coordinated project MatrixWW is to develop methodologies that ensure the efficiency and safety of floating offshore turbine operation. To achieve this objective, it is proposed to combine floating turbines with wave energy converter devices, so that both systems benefit each other.
The subproject1, SuMariNeW, led by the UCM team, will develop a system for early fault detection and prevention in offshore wind turbines using artificial intelligence, data-driven and learning-based AI methodologies. The final goal is to maximize performance while minimizing vibrations applying multi-objective wind control systems to improve useful life and reduce maintenance.
The subproject 2, OWC4FWind, led by the Automatic Control Group at EHU, focuses on the development of advanced wave energy conversion systems based on Oscillating Water Column (OWC) technology. Using over a decade of experience at the Mutriku on-shore OWC plant, this subproject aims to adapt and integrate reliable, high-efficiency power take-off and control systems into the floating WindWave platform. The goal is to enhance energy capture and conversion from offshore wave conditions, improving performance and survivability while reducing maintenance needs. The research combines theoretical modeling, control development, and experimental validation to ensure robust operation in harsh marine environments and to significantly increase the commercial viability of hybrid wave and wind energy platforms.
ANALYSIS AND CONTROL OF A HYBRID FLOATING WIND AND MARINE ENERGY DEVICE
RTI2018-094902-B-C21
ANALYSIS AND VIBRATION CONTROL OF FLOATING WIND TURBINES (FloatWind)
This coordinated brings together two different marine renewable technologies into one ocean energy converter device named WindWave. The final objective of this project is to analyze the dynamics of a hybrid energy device that deploys wave converters on the platform of a floating wind turbine.
Subproject 1, led by UCM, is focused on the floating wind marine turbine (FWT) component of the WindWave device, both from the energy efficiency and vibration control point of views, in order to make it feasible and reduce costs.
Subproject 2, Wmatrix4W, led by the Automatic Control Group at EHU, focuses on the integration of a matrix of Oscillating Water Column (OWC) wave energy converters into the floating wind platform. The objective is to enhance energy harvesting capabilities by combining both renewable sources on a single structure. This subproject addresses the design, control, and implementation of the OWC array and its integration with the wind subsystem through
cooperative control strategies. It also includes the development of advanced predictive models to improve system reliability and reduce maintenance needs. The team builds on extensive experience in OWC systems and contributes to the coordinated effort with specialized knowledge in wave energy conversion,aiming to maximize overall system efficiency and survivability.