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: https://windeurope.org/about-wind/campaigns/poul-la-cour/

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.

Cl-Windcon supports the COP24 and the EC climate policies

The CL-WINDCON project supports COP24, a conference that seeks to help in the reduction of greenhouse gas (GHG) emissions and the slowdown of global warming.

The 2018 UN climate change conference (COP24) held in the Polish city of Katowice from 2 to 14 December 2018. The key objective of COP24 is to adopt the implementation guidelines of the Paris Climate Change Agreement. In this sense, this Summit will be key when it comes to design the instruments that enable climate goals to be tackled and achieved effectively and efficiently.

Nowadays, climate change is an undeniable fact: the concentration of greenhouse gases (GHGs) in the atmosphere has been progressively increasing since the Industrial Revolution and reversing this trend is only achievable via worldwide action and by tackling the problem forcefully from all angles.

In this context, CL-WINDCON is fully aligned with the European climate change strategies and the energy transition. Its goal is set on power production with wind farm models, O&M costs, full system reliability, lifetime extension, economic growth and competitiveness, and environmental and social job creation impact.

According to the energy Union Strategy, the SET-Plan is one of the seven research priorities defined by the Strategic Research Agenda of CL-WINDCON. This project addresses wind topic on LCE-07-2016.2017: “Developing the next generation technologies of renewable electricity and heating/cooling”. It will evaluate the overall value chain of the new control strategy through a Life Cycle Assessment, including supplies, production, distribution, use and disposal as well as all intervening transportation steps necessary or caused by the equipment’s existence. This is especially relevant in case of modifications of existing wind farms.

 

About COP24

The main objectives of COP24 are:

  • To take the decisions necessary to ensure the full implementation of the Paris Agreement.
  • To take stock of the collective achievements made by the Parties in their efforts to meet the objectives agreed in Paris.

Public deliverables available for download

Following the aim to disseminate the results of the project and its economic, social and environmental benefits, CL-Windcon public deliverables are going to be available in open access. A dedicated section for project deliverables downloading is already active in this project website as content central hub. From now on the section will be updated with the latest issued and approved deliverables.

The first approved public deliverables can already be downloaded in this section. In order to broaden the dissemination of projects results, a social media campaign is going to be launched to announce and give insights of the content that can be found on each of the available documents. The deliverables can be downloaded here:

http://www.clwindcon.eu/public-deliverables/

CanWEA review on Wind Energy and Bat Conservation

Wind energy is playing an important role in the environment protection through the production of clean, renewable energy. But in addition, the wind industry is also committed in wild life conservation by finding ways to minimize potential impacts from wind parks operation.

One of the vulnerable species that can be affected are bats, which can fatally collide with operational wind turbines and other structures. The wind industry in collaboration with academia, government scientists and conservation organizations has been contributing to the knowledge of the bats interaction with wind turbines in order to apply risk mitigation actions. Now, the Canadian Wind Energy Association (CanWEA) has gone one step further and has commissioned DNV GL to gather all the available information accumulated over the last several decades into a detailed review report. This report was released last week and it is available here:

https://canwea.ca/wind-facts/wildlife/wind-energy-and-bat-conservation-review

CL-Windcon project is also committed to the environment protection and in particular to reducing the impact on wildlife during the wind farm level tests that it will be performing. A risk analysis is being taken within work package 7 of the project, and this report from CanWEA will help on the development of this task.

CL-Windcon at ACC 2018

This week some CL-Windcon partners have flown to Milwaukee to attend the ACC 2018. The American Control Conference (ACC) is an annual 3-day meeting that brings together an international community of researchers and practitioners in all areas related to the engineering and science of control systems.

Our TU-Delft fellow Bart Doekemeijer participated chairing the ‘Advanced Flow Control of Wind Farms’ session. During that session, Johannes Schreiber (TUM) presented the work “Online Model Updating by a Wake Detector for Wind Farm Control (I)”, where it was explained the real-time calibration of the FLORIS model. During the ‘Energy Systems I’ session, Daan van der Hoek (ECN-TNO) made a presentation comparing single turbine down-regulation control strategies and their effects on fatigue loads.

CL-Windcon presence at Torque 2018

During last week, Torque 2018 “The Science of Making Torque from Wind” conference was held at Milano with participation of CL-Windcon. This year the conference was chaired by our partner Alessandro Croce.

During the appetizers of the event, a CL-Windcon technical update meeting took place, with the attendance of Paul Fleming and Jennifer Annoni from the project external advisor NREL. The technical progress was reviewed and insightful discussions were maintained with our NREL fellows.

During the conference, CL-Windcon presence was very significant at the ‘Control and Monitoring’ and ‘Modeling and Simulation Technology’ sessions. Bart M. Doekemeijer from TU Delft presented parameter estimation techniques for control-oriented wind farm model. Steffen Raach from USTUTT showed project developments in LiDAR-based closed-loop wake redirection control. Irene Eguinoa from CENER explained results about the assessment of different derating strategies for upwind turbines from fatigue load perspective. Johannes Schreiber from TUM has presented a study of wind farm control potential based on SCADA data. Ervin Bossanyi from DNV-GL showed first insights for the combination of axial induction and yaw steering control for farm operation optimization, developed at the project. Sebastian Mulders from TU Delft presented Open Source wind turbine control contributions to the community. Marta Bertelè from TUM explained formulation for the estimation of wind shear and misalignments from rotor loads applied to IPC-controlled wind turbines. Chengyu Wang from TUM showed validation of large-eddy simulations of scaled wind turbines against experimental data. And Alberto Fortes from TUM presented a reduced-order model obtained by directly compressing high-fidelity CFD simulation data using the proper orthogonal decomposition (POD) for wake steering control.

You can download the different papers at: http://iopscience.iop.org/volume/1742-6596/1037