ALISIOS: Algorithms and Linearization for the Integration of Intelligent Sensors in Offshore Wind Farm Operation

The ALISIOS project seeks to promote floating wind energy, considered the most promising solution to the space and social constraints affecting onshore wind power. Faced with the challenge of reducing costs and facilitating the mass scaling of this technology, 2BE has developed an internationally pioneering two-bladed downwind wind turbine, which reduces costs by reducing the number of blades, lightening the structure, and simplifying rotor assembly.

One of the most pressing problems in floating wind energy is its monitoring and control, which lead to an increase in cost due to the necessary additional sensors. To solve this, ALISIOS seeks to replace them with virtual sensors: algorithms capable of accurately estimating the critical loads and dynamics of the system from a few physical sensors. These algorithms will be validated using advanced simulations and reduced mathematical models, which will enable the development of optimized control strategies, improve wind turbine efficiency, reduce maintenance costs, and increase the economic viability of floating projects. Thanks to these innovations, 2BE is consolidating its position as a business leader and CENER as a benchmark in research, positioning itself at the forefront of the international floating wind power market and in a highly differentiated niche: two-bladed downwind wind turbines.

In the ALISIOS project, CENER contributes its technical expertise to the development and validation of virtual sensors for floating wind turbines. Their work focuses on designing both linear and nonlinear sensors, using mathematical models and advanced algorithms such as the Kalman filter, combined with linearizations obtained from a reduced physical model, ensuring proper parameterization and computational efficiency. Additionally, CENER carries out the validation of the virtual sensors against reference simulations, establishes key performance indicators (KPIs), and works closely with 2BE to iteratively improve sensor configuration, ensuring reliable and accurate estimations necessary to optimize control and monitoring of floating wind turbines.