ICONIC

The partners in ICONIC strive to develop innovative digital and physical instruments to fundamentally improve the integrated control of wind farms. This involves looking at the entire physical system and the complex aerodynamic interactions between turbines.

Status

In progress

Duration

Dec 2023 - Nov 2027

Type

DBC as an observer, International project

Wind energy plays a pivotal role in the global pursuit of sustainable development. About 116 GW of new wind farms are expected to be installed in Europe from 2022-2026. However, wind farms’ operating efficiency is still severely constrained, and significant research & application gaps still exist, including:

Needs of an innovative, scalable, practically applicable wind farm (WF) control system to fully understand the effects of aerodynamic interactions between turbines under time-varying environmental condition;
Needs of an efficient digital and physical tools to significantly enhance data collection, data mining and virtual sensing, providing comprehensive information far beyond physical measurement level;
Needs of comprehensive validations and demonstrations (e.g. dedicated experiments and real-world field tests) for new technologies.

ICONIC aims to fill all the above gaps, delivering disruptive technologies to achieve fundamental breakthroughs for wind farm O&M, enabling the transformation towards next-gen wind farm control approaches while meeting the core needs and requirements of wind farm owners and other companies in the wind energy value chain.

Objectives

The principal objectives of the ICONIC project are:

Develop new wind farm control tools to improve wind farm operations leveraging AI innovations;
Investigate turbine control solutions with load-reduction abilities to deliver farm-wide objectives;
Develop digital twins and physical tools for awareness and control enhancement considering remaining useful life assessment of wind turbine key components; and
Validate and exploit the integrated control system and digital twins via wind tunnel tests, historical operational data, dedicated test rigs, and field tests.

Partners: Ghent University, KU Leuven, C-Power, Thornton Bank Maintenance Services and ZF Wind Power (Belgium); University of Warwick, Imperial College London and BP (United Kingdom); Norwegian University of Science and Technology and EDR & Medeso (Norway); Aalborg University (Denmark); Ikerlan and Laulagun (Spain); SKF (Netherlands); and EMBOTECH (Switzerland).