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H2020 LCE 7 -2016/2017: Control de parques eólicos completos para reducir los efectos de estela y aumentar la productividad

Resumen

Tipo:
Búsqueda de socios
Referencia:
RDUK20160112001
Publicado:
21/01/2016
Caducidad:
21/01/2017
Resumen:
Una universidad escocesa busca socios con el fin de desarrollar una propuesta para la convocatoria LCE 7 (Control avanzado de turbinas y parques eólicos a gran escala) del programa H2020. El objetivo es desarrollar un sistema para controlar parques eólicos completos y reducir los efectos de estela en el rendimiento de las turbinas. La universidad busca experiencia en pruebas en túnel de viento, dinámica de fluidos computacional, implementación de software y hardware de sistemas de control para turbinas y parques eólicos, y funcionamiento de grandes parques eólicos. La fecha límite de la convocatoria es el 16 de febrero de 2016 y el plazo para presentar expresiones de interés finaliza el 25 de enero.

Details

Tittle:
H2020 LCE 7 -2016/2017 - Control of whole wind farms to mitigate wake effects and maximise productivity
Summary:
A Scottish university is looking for partners to develop a proposal for the H2020 call LCE 7 ´Advanced control of large scale wind turbines and farms´. The project will develop a system for controlling whole wind farms to minimise the effects of wake on turbine performance. Desired expertise includes: i) wind tunnel testing, ii) computational fluid dynamics, iii) software and hardware implementation of control systems for wind turbines and farms, and iii) operation of large wind farms.
Description:
A Scottish university is looking for partners to develop a proposal for the Horizon 2020 LCE 7 call ´Advanced control of large scale wind turbines and farms.´

The intended project will develop, test and validate advanced algorithms and their software and hardware implementations for controlling whole wind farms to minimise the effect of wake on turbine and farm performance. The expected Technology Readiness Level (TRL) at the end of this 3-4 year project is TRL 4, hence laboratory scale validation must form an important part of the research alongside theoretical developments and numerical simulations, the latter additionally underpinned by full-scale, in-situ data.

Wind turbine operating parameters, such as blade pitch, tip speed ratio and yaw, are typically optimised for maximising energy production and/or minimizing loads for individual turbines. Such strategies are suboptimal for wind farms where the downwind turbines may find themselves in the wake of the upwind turbines that can reduce their power output. Increasing distances between the turbines is not always practical. However, the downwind power loses may be minimized by controlling collectively the whole farm. Sacrificing the upwind turbine optimal blade pitch, tip speed ratio and yaw will reduce their power output but will also decrease the harmful wake effects allowing the downward turbines to increase their efficiency. This will result in an overall increase in the farm´s productivity. The cost of doing so should be small as the under-utilised potential of extensive instrumentation and control systems that individual wind turbines already have will be harnessed. The proposed research will develop and validate wind farm control algorithms. Both model-based and model-free algorithms can be adopted and evaluated. The advanced control strategies developed will improve efficiency of wind farms and reduce the cost of wind energy.

The Scottish university will be responsible for development and validation of the control algorithms.

The deadline for project submission is February 16th, 2016. Interested partners should respond to this posting by January 25th, 2016. The envisaged duration of the project is up to 4 years.
Stage of Development:
Proposal under development
Technical Specification or Expertise Sought:
The partners sought, their desired expertise, research and industrial facilities and tasks to be performed are as follows:

i) A commercial or public research organization or a university with expertise in wind tunnel testing of structures. The size of the tunnel should be such that at least two (and preferably more) spatially distributed small scale wind turbines can be tested for their interactions due to wake. The experimental work will include determination of wake patterns due to various positions of rotor and blades and their motion, their influence on power production, and laboratory scale evaluation of control algorithm efficiency.

ii) A commercial or public research organization, university or industrial partner with expertise in computational fluid dynamics (CFD) applied to wind turbines and farms. The numerical work will include determination of wake patterns due to various positions of rotor and blades and their motion to provide simulated data for the development and validation of control algorithm efficiency.

iii) Up to two or three SMEs or larger industrial partners specialising in the development, manufacturing and/or integration of sensing and control systems for wind turbines and farms. The tasks will include software and hardware implementation of the control algorithms developed for wind tunnel testing and full-scale prototyping for future commercial deployment and exploitation.

iv) An operator of a large wind farm facility. Their task will include the generation and collection of full-scale, in-situ data sets of wake effects on wind farm productivity to underpin realistic numerical simulations of control algorithms.


Partner sought

Partner Sought:
Partner Type 1 (PT1): Research organisation/university PT1: Research PT1: Large scale wind tunnel testing PT1: Wind tunnel testing to determine wake characteristics due to different rotor and blade configurations and testing the performance of the control algorithms developed PT2: A commercial or public research organisation/university/industry PT2: Research PT2: Computational fluid dynamics (CFD) applied to wind turbines and farms PT2: Numerical work to determine wake patterns due to various positions of rotor and blades and their motion, and interactions between turbines to provide simulated data for the development and validation of control algorithms PT3: SMEs or larger industrial partners PT3: Development, manufacturing and/or integration of control systems PT3: Control system software and hardware for wind turbines PT3: Software and hardware implementation of the developed control algorithms for testing in a wind tunnel PT4: Large wind farm operator PT4: Operation of large wind farms PT4: Operation and control of large wind farms PT4: Generation and collection of full-scale, in-situ data sets of wake effects on wind farm productivity to underpin realistic numerical simulations of control algorithms
Type of Partnership Considered:
RDR

Client

Type and Size of Client:
University
Already Engaged in Trans-National Cooperation:
No
Languages Spoken:
English
Polish

Dissemination

Programme-call

Evaluation Scheme:
Single-stage submission scheme
Anticipated Project Budget:
2-5 million Euros
Coordinator Required:
No
Deadline for Call:
16/02/2016
Project Duration:
208
Project title and Acronym:
Control of whole wind farms to mitigate wake effects and maximise productivity