Elso Torralba, Jorge
Loading...
Email Address
person.page.identifierURI
Birth Date
Job Title
Last Name
Elso Torralba
First Name
Jorge
person.page.departamento
Ingeniería
person.page.instituteName
ISC. Institute of Smart Cities
ORCID
person.page.observainves
person.page.upna
Name
- Publications
- item.page.relationships.isAdvisorOfPublication
- item.page.relationships.isAdvisorTFEOfPublication
- item.page.relationships.isAuthorMDOfPublication
2 results
Search Results
Now showing 1 - 2 of 2
Publication Open Access Lidar-based feedforward control design methodology for tower load alleviation in wind turbines(John Wiley & Sons, 2022) Miquélez Madariaga, Irene; Lizarraga Zubeldia, Idoia; Díaz de Corcuera Martínez, Asier; Elso Torralba, Jorge; Ingeniería; IngeniaritzaMinimising tower loads is a key issue for the optimal operation and cost-effective design of wind turbines. Light detection and ranging (LIDAR) technologies enable the measurement of free wind ahead of the rotor and the addition of new feedforward controllers to the traditional control loops, improving the performance in terms of generator speed regulation and load reduction. This paper presents a design procedure based on plant inversion at a set of key frequencies. Tower base longitudinal bending moment is considered the main output of the system. Although the minimisation of tower base loads is the main objective of the design, good results are obtained in terms of generator speed regulation and pitch actuation as well. The methodology has been tested in the well-known NREL 5MW wind turbine. Results have been obtained for different LIDAR configurations in order to quantify the loss of performance due to measurement errors. In all cases, the feedforward control behaves better than the baseline case.Publication Open Access Linear uncertain modelling of LIDAR systems for robust wind turbine control design(Elsevier, 2023) Miquélez Madariaga, Irene; Lizarraga Zubeldia, Idoia; Díaz de Corcuera Martínez, Asier; Elso Torralba, Jorge; Ingeniería; Ingeniaritza; Universidad Pública de Navarra / Nafarroako Unibertsitate PublikoaLight detection and ranging (LIDAR) sensors measure the free wind ahead of the rotor, enabling the use of new feedforward control strategies. However, there exist some sources of error inherent to the measuring process that should be considered during the design of LIDAR-based controllers. Typically, the coherence function is used for that purpose, but it is not compatible with some robust design methodologies. This paper presents an analytic relation between the coherence function and a non-parametric uncertainty model of LIDAR sensors, suitable for the design of controllers via 𝜇-synthesis or Quantitative Feedback Theory. Such a relation is applied to a realistic LIDAR simulator. First, the linear non-parametric uncertainty model is identified using simulation data obtained from the well-known NREL 5 MW wind turbine. Then, it is validated against the coherence model by comparing linear predictions of the simulation outputs.