Deliverable D3.2: Definition of field-testing conditions

Deliverable 3.2 defines and describes the full scale field tests being executed at Enel Green Power´s (EGP) wind farm in Sedini (Italy) as part of Task 3.3 “Demonstration by full-scale testing” under WP3 “Demonstration and validation of prototypes”. An extensive field campaign has been planned at this site to investigate wake characterization for improved modelling of turbine interaction and demonstration of closed loop control, taking wind turbine couplings into account. The planned field tests comprise two types of experiments: first, simple turbine performance, loads and wake characterization for operation with yaw misalignment and reduced induction. These tests will allow to characterize the modelling space and to validate the simplified control oriented system models. The second type of test will be demonstration of farm control algorithms, where the newly developed algorithms are tested and validated against baseline performance.

All the experiments mentioned above were executed in a so-called toggle mode, i.e. switching between experiment mode and baseline mode in 30-60 minute intervals. This allows for similar environmental conditions and therefore better comparison between baseline and altered conditions. Also, during the experiments, selected turbines operated outside of this normal operation mode to ensure that the turbine operation was safe during all times.

Summarizing, this deliverable gives a detailed description of the planned field test. Based on the outcomes of WP1 and WP2, two types of experiments are proposed. The additional instrumentation that is needed for a thorough evaluation is described in detail in this deliverable as well as the expected time line.

You can get the complete document from our download section.

PhD position on numerical and experimental modelling of “Off-Shore Wind Farm Control”

The Department of Mechanical Engineering of Politecnico di Milano and the Delft Centre for Systems and Control of the Technical University of Delft offer one doctoral position in the wind energy field.

These two centres have a strong collaboration in the wind energy field that recently led to the participation in several European projects. The first one, Polimi, has a strong experimental background, with the availability of a large wind tunnel infrastructure and several wind turbine models and scale model wind turbine design procedures. A hardware-in-the-loop framework is adopted to test floating wind turbines installed on the Hexafloat platform for the modelling of the floating wind turbine platform. High fidelity numerical tools (CFD LES actuator line) for wind farm modelling validated vs experiment are also available. The second one, TUDelft, has a strong background on control topics, having specific experience on Wind farm control, Smart dynamic wind turbine control, Data driven control and Nonlinear system identification, with the availability of several reliable and validated numerical models for wind turbines wakes dynamics and interaction with the downwind turbines. Several strategies to minimize LCOE have been developed, acting on wake redirection, induction reduction, minimizing dynamic loading.

What they are looking

A young scientist with a Master Degree latest on 31st October 2019 able to understand concepts quickly, following a sharp learning curve, with good planning skills and the ability to work independently. This person will have enthusiasm, the willingness to exploit his skills in ocean sciences research for the benefits of communities pursuing sustainable growth, and be seeking the opportunity to develop his research career through scientific publications. He will be able to actively participate in the R&D activities of collaborative research projects, both at a national and international level, and have a desire to become a future leader in your field.

Skills and qualifications will include:

– As minimum education requirement, a University Degree (MSc or equivalent) in Science, Technology, Engineering and Mathematics (STEM) disciplines: Physics, Mathematics, Engineering.

– Some experience in computational sciences or statistics, with knowledge and proved use of scientific programming languages or advanced software environments (e.g. Fortran, C, Python, Matlab).

– Fluent English (the list of accepted certificates and levels is available in the call for application).

About the role:

The typical installation of wind turbines is realizing a cluster of closely spaced turbines to minimize the infrastructure cost. The close space between the rotors leads to the interaction between wind turbine wakes, leading to reduction in energy harvesting and undesired fatigue loads. A wind turbine operating in waked condition has a reduction in extracted power, since the upstream rotor reduces the amount of energy of the incoming wind. Moreover the rotor loads may not be uniform, in time and space, due to the mean boundary layer gradient growth and turbulence large size coherent structures. Such dynamic excitation issues are even more critical, given the intrinsic and growing large size of offshore wind turbines, leading to possible fatigue damage and large dynamics of the very flexible blades . The very peculiar dynamics of the floating substructures is giving additional relevance to the control issues of the specific single Wind Turbine in terms of stability and dynamic response to wave excitation. The development of reliable and validated numerical methods suitable for modelling the wind turbines wakes dynamics and interaction with the downwind turbines became the fundamental tool for designing optimized solutions of wind farm control, exploiting innovative wind farm control strategies, acting on wake redirection, induction reduction and other techniques finalized at limiting the wind turbines dynamic loading and at the same time increasing the overall wind farm production.

It is fundamental to develop control strategies, designed together with the structure components, capable of capturing the dynamics of the wake of offshore wind farms, regulating the produced power and reducing fatigue loads, enhancing, as consequence, the machine life and reducing the LCOE.


– Position: Double PhD, Full Time

– Duration: 48 Months

– Salary: € 15.900 net/year (will increase during the years) + travel allowance + research budget

– The position will have as possible Supervisors:


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How to apply:

Application procedure is available at required documents (project proposal, CV, motivation letter etc.) must be uploaded online following the instructions provided at the same link.

For further information on application procedure please contact  or Preliminary enquires during the application process are strongly suggested.

Deadline: 21th May 2019 (2pm, Italian time).

Deliverable D3.1: Definition of wind tunnel testing conditions

One of the main validation activities of the project are the experiments performed at wind tunnel. These experiments have been performed in the wind tunnel facility of Politecnico di Milano (GVPM), a massive structure with a test section 4x14x40 (HxWxL) meters capable of housing multiple wind turbine models, in order to replicate a realistic wind farm.

Deliverable 3.1 reports the definition of the wind tunnel testing activities in the CL-Windcon project, including the description of the wind tunnel facility of Politecnico di Milano, the flow measurement techniques and the flow characteristics that will be adopted for the testing activity. Also, the G1 scaled wind turbines (designed and built by TUM) are described in terms of geometrical and aerodynamic features, presenting the measurement devices that allow achieving information on the turbine operation. The control system is presented as well, illustrating all possible control variables.

The wind tunnel activities cover a total of 45 testing days. The first tests (19.5 days in the first half of the project) regard the characterization of the single or multiple wind turbine wake and the performance of an array of wind turbines with possible wake control strategies (axial induction and yaw redirection), in order to provide input to the wind farm control strategies.

The last tests (25.5 days in the second half of the project), are devoted to test different wind farm control algorithms, developed using different theories, applying the concepts of induction and yaw control to the entire wind farm of scaled wind turbines.

The considered scenarios are realistic and will allow a quantitative characterization of the single turbine and coupled turbine/farm control performance. The coupled G1 wind turbine models / GVPM system represents an effective international scientific reference for wind energy experimentation. All the measured data are stored in a structure including all wind turbine operation information.

You can get the complete document from our download section.

5th CL-Windcon General Meeting at Munich (March 26th – 27th)

Last week (on 26th and 27th of March), CL-Windcon fifth General Meeting took place at Munich, hosted by the Technical University of Munich (TUM), one of the most research-focused universities in Germany and Europe.

Now that the project is heading into the home stretch, the meeting has been mainly focused in the presentation of the most important technical advances, as the last outcomes from the baselines work of fast wake recovery techniques, the progress of the SOWFA group and the data obtained in the experimental campaigns. Also the status of the exploitation and dissemination activities has been discussed.

During the meeting it was also announced that CL-Windcon Final Conference will be organized jointly with WESE (Wind Energy Systems Engineering) workshop next October at Pamplona.

Deliverable D2.2: Methodology for active load control

The objective of this deliverable was to analyze control mechanisms for the reduction of loads caused by a wind turbine being a part of a farm. These loads are mainly due to partial wake overlap, which forces blades to get in and out of one or more upwind turbine wakes, with the corresponding increase in fatigue

CL-Windcon contemplates both the reduction of said cyclic loads via individual pitch control and their avoidance via wake steering. Individual pitch control requires, however, a considerably increased pitch actuator activity and something similar occurred with wake steering and the yaw system. This is why is desirable to be able to activate (or trigger) a load-reducing control features only when partial wake overlaps actually happen. In this way, the deliverable presents estimators for partial wake overlap detection that can be used for that triggering strategy, as well as a novel closed-loop wake steering methodology and a  triggerable individual pitch control implemented by OpenDiscon.

Another important point of the deliverable is the presentation of a technique for the management of sensor failure, which may have applications in wind farm control, where sensor redundancy may not only happen by design, but also by collaboration between turbines.

You can get the complete document from our download section.

Deliverable D2.1: Minimal loading wind turbine de-rating strategy and active yaw controllers

The idea of wind turbine control as a preliminary step for wind farm control developed is treated in this deliverable. The new technologies required at farm level need to be analyzed from the fatigue loading optimization viewpoint and demand to go beyond usual modes of operation of wind turbines.

Therefore, different strategies and combinations for downregulation differentiating between below rated and above rated wind speed regimes are developed. In addition, active yaw control is treated, allowing the development of control techniques for misalignment with the wind direction to redirect the wake with an optimal balance with fatigue loading. As long as these farm control advances, some modifications and adjustments at turbine control level might be required to take into consideration.

All the strategies named above, need to be implemented in a common, flexible and transparent controller structure which will be used as a baseline in subsequent work. An open-source code also has been developed for its use in the near future, being available not only for CL-Windcon partners, but also for the whole wind energy control community. In conclusion, the code will also be open to the community, maximizing its impact and enabling its shared use as a basis for future work on wind farm control.

You can get the complete document from our download section.

Deliverable D1.3: A common pre- and post-processor for wind farms simulations

The third deliverable presents the development of a software toolbox for the pre- and post-processing of wind farm simulations. This new structure developed allows storing all wind turbine/farm specific information as well as simulation specific information for tools of different fidelity. In the same way, the toolbox fulfills the need for having a common definition of wind farms/turbines to be able to exchange wind farm/turbine information without having format constraints.

A common pre-processing is established, which generates the inputs for each simulation tool. With this implementation the information of a wind farm/turbine in the reference structure can be used by creating input files of different wind farm simulation tools.

Another important point is that using the post-processing toolbox, the simulation data of different tools are fed in and analyses functions for the comparison of data are applied.

You can get the complete document from our download section.

Deliverable D1.2: Description of the reference and the control-oriented wind farm models

The objective of this deliverable was to present, in a complete and mathematical manner, the various wind farm models used and extended within the CL-Windcon project. On a lower-fidelity scale, this includes control-oriented surrogate models, which are lightweight and can be used in real time to optimize the operation inside the farm. Among others, a collaborative effort was made towards a steady-state surrogate model called “FLORIS”, which is short for the “FLOw Redirection and Induction in Steady-state” model. This model is being tested through high-fidelity simulation, scaled experiments in the wind tunnel in Milan, and field experiments in a small wind farm in Italy. On the other hand, the higher-fidelity models offer a high spatial and temporal resolution to resolve the different scales of turbulent structures in the flow and turbine dynamics. The high-fidelity model used in CL-Windcon is SOWFA. Finally, the deliverable also includes medium- and multi-fidelity models (like FAST.Farm, SimWindFarm, LongSim, WindFarmSimulator,…), which attempt to bridge the gap between low-fidelity surrogate models and high-fidelity simulation models. This deliverable resulted in a clear overview of the state-of-the-art models that are being used within the project.

As particular outputs from the deliverable, it can be highlighted the implementation of large wind turbines (10MW) in the high-fidelity simulation environment “SOWFA”. A number of wind farm topologies, inflow conditions and surface conditions are specified to cover an appropriate range of wind farm operation in simulations. Another important output from this deliverable has led to an open-source software implementation of the surrogate wind farm model “FLORIS”, available on Github, with the aim of becoming community-driven.

You can get the complete document from our download section.

Poul la Cour Prize 2019

Awarding a major contribution to wind energy in Europe

You can nominate your candidate for the Poul la Cour Prize. This biennial award is a cooperative effort between WindEurope and the Poul la Cour Foundation. Candidates must had contributed to a unique and lasting improvement for the benefit of the development and use of wind power in Europe, despite of their age, educational or scientific background number of years’ experience or industry sector they come from.

The Poul la Cour Prize 2019 will be awarded at the WindEurope Conference & Exhibition 2019 in Bilbao, Spain (2-4 April). The deadline for submissions is next February 10th. You can find more information and submit your candidate at:

Deliverable D1.1: Definition of reference wind farms and simulation scenarios

This first technical deliverable presents the selected reference wind farms and simulation scenarios that are used to make comparisons between the different technologies within the project. The definition of the reference wind farms is essential to ensure a high degree of comparability between the different models, control technologies and algorithms to optimize the performance of wind farms. The definition of the simulation scenarios provides the framework guidelines that enable reference cases to be defined by inputs/outputs, variables and evaluation metrics, for a common analysis and accurate comparisons between the different models and control strategies.

Four different reference wind farms have been defined. Two of them are simple topologies with one and three arrays of three turbines. The two other are more complex layouts with eighty turbines in four rows in the offshore case (Norcowe RFW) and the existing wind farm that will be used in the field experiments (Sedini WF).

The wind turbine selected for the minimal layouts and the offshore wind farm is the reference turbine from the EU project INNWIND, as it is described in detail in public literature and reflects the current state of the art for wind turbine technology. For Sedini wind farm, GE 1.5 MW installed turbines are the reference one. This wind turbine has been for years one of the world’s most widely used in its class.

A set of simulation scenarios have been defined in order to provide guidance on the development and execution of a highly integrated modelling and experimental research activity based on well-established verification and validation (V&V) practices adapted to the development of tools for wind farm dynamic modelling and control. The formal V&V framework adopted was originally developed by Sandia National Laboratory.

You can get the complete document from our download section.