ALISIOS PROJECT
ALISIOS is a collaborative R&D project led by 2-B Energy together with CENER. Its main goal is to boost the competitiveness of 2-B Energy’s multi-MW floating two-blade downwind turbine by replacing costly offshore instrumentation with smart virtual sensors and advanced control strategies.
- Dynamic modelling of the floating downwind turbine:
ALISIOS develops parametric dynamic models that capture the fundamental behaviour of a floating, downwind, two-blade turbine. These models describe key frequencies and damping ratios of the system and are benchmarked against detailed hydrodynamic models to ensure consistency.
2. Validation in industry-grade simulation tools:
The dynamic models are validated using the Bladed simulation environment, comparing power curves and responses in multiple operating conditions. This step guarantees that the simplified models remain faithful to the full non-linear behaviour of the turbine.
3. Passive yaw integration:
One key innovation of ALISIOS is the implementation of a dedicated passive yaw formulation in Bladed. By introducing a specific sub-model for the yaw dynamics driven by aerodynamic and gravitational effects, the project ensures that the particular behaviour of the downwind configuration is accurately represented in both linear and non-linear models.
4. Virtual sensors: Model-based estimation of critical loads and states
Using reduced-order models and linearizations, ALISIOS develops virtual sensors based on Kalman-filter techniques. These algorithms estimate critical variables and loads of the turbine in real time, combining information from a limited set of physical sensors with advanced dynamic models.
5. Validation of virtual sensing solutions: Robustness across operating conditions
The virtual sensors are extensively validated against Bladed simulations over a wide range of operating conditions. Their accuracy is assessed in both time and frequency domains, ensuring that the estimated quantities remain reliable for control and monitoring purposes.
6. Control strategies powered by virtual sensors: Reducing loads and improving performance
Finally, ALISIOS integrates virtual sensor estimates into advanced control strategies, such as model-based and predictive controllers. These strategies aim to reduce structural loads and rotor speed oscillations while maximising energy capture, paving the way for a lower LCOE in floating offshore wind.
