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Engineering and technology
- Automation and control systems
ICONIC aims to develop innovative physical and digital tools to achieve fundamental breakthroughs for the integrated control of wind farms, considering the whole physical system at farm, turbine, and component levels, in particular the complex aerodynamic interactions among turbines. ICONIC aims to increase farm-wide power production by 15-20% under optimal wind speeds and directions for typical wind farms suffering from wake effects, with a 3%-5% increase in annual energy production (AEP) considering all working conditions over the long term. It targets an LCOE reduction of at least 6% compared with the state-of-the-art control tools deployed in the current wind industry by improving farm-wide AEP and reducing operation & maintenance costs via leveraging the latest AI and digital technologies. Extensive validations for the integrated wind farm control solutions will be conducted via highfidelity simulation models, experiments at a national-level wind tunnel, historical operational data at BP’s and C-Power’s wind farms, a unique collection of test rigs for critical turbine components at respective companies, and real-world wind farm field tests at C-Power. ICONIC’s integrated wind farm control system will contain (1) novel AI-based wind farm control system to unlock wind farms’ full potential; (2) novel data-enhanced wind turbine controllers to fulfil farm-level commands while balancing power generation and load mitigation; (3) an integration with digital twins (DTs) as extra support to improve control and reduce costs, which contains a first-ever farm-level DT for wind farm flow systems replicating detailed physical flow fields and an innovative turbine-level DT with critical component models for loading and lifetime estimations; (4) extensions of the solutions to future 20MW turbines. ICONIC will establish new knowledge and industrial leadership in key digital, enabling and emerging technologies, and deliver next-generation tools for wind farm operation.