The SUDOCO partnership is a dynamic and multidisciplinary group composed of experts with diverse backgrounds, each bringing unique skills and knowledge to project. At its core, the team is coordinated by Professor Jan-Willem van Wingerden (Delft University of Technology), who coordinates a group of experts from both academia and the private sector. The workgroup comprises individuals with diverse expertise, ranging from engineering and environmental issues to the intersection of science and society. This holistic approach aligns with the team’s commitment to create not just efficient but also environmentally and socially responsible wind energy solutions.
The consortium is composed by the following institutions and enterprises:
Our international team is working closely with the EU’s BRIDGE initiative, which brings together previous and current projects that address hybrid grids, power electronics, and protection systems. This allows us to draw on previous knowledge and to share our own achievements and insights with related projects.
Related projects
Collaboration amplifies innovation. Alongside the SUDOCO project, several other initiatives dedicated to advancing wind energy solutions are working towards shared goals of environmental sustainability. With SUDOCO, this network of independent projects addresses complementary challenges and engages a broad range of stakeholders.
TWAIN
TWAIN is a 48-month Horizon Europe project led by 12 partners, dedicated to ensuring the reliable and cost-effective design and operation of wind power plants, with a specific emphasis on system stability, security, and environmental considerations. The project aligns with the European Union’s decarbonization goals, acknowledging the transformative influence of artificial intelligence and digitalization as drivers of the energy transition and enabling the integration of wind farm control technology processes into the operation and design of future energy systems.
WILLOW
WILLOW, “Wholistic and Integrated Digital Tools for Extended Lifetime and Profitability of Offshore Wind Farms”, aims to achieve an integrated system that will provide a health aware curtailment strategy to the offshore wind farm operators. Physical models and data-driven models (AI/ML) will be used to assist decision-making and planning of wind turbine operation and maintenance (O&M) activities considering factors such as component degradation, the particular complexity of grid integration, or specific offshore issues like corrosion or the additional loads from waves, tides and currents.
ICONIC
The ICONIC consortium aims to develop innovative digital and physical 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. The proposed integrated control solutions will be demonstrated by an extensive validation study via high-fidelity simulation models, experiments at a national-level wind tunnel, historical operational data, and real-world wind farm field tests.
MERIDIONAL
MERIDIONAL has the aim to produce a knowledge and data hub and a toolchain that will be accessible to a range of users from industrial to academic sectors to improve wind farm design, performance assessment, and loading. The research will draw on a comprehensive set of data including simulations and field campaigns and be demonstrated through selected use cases, onshore, offshore, and airborne.
AIRE
The AIRE project, led by CENER, aims to optimize wind energy by improving the understanding of atmospheric impacts on turbines. Current models overlook high-altitude wind flow physics and weather conditions like precipitation and sand, which affect efficiency and predictability. AIRE will gather data from various sites to create new models and design tools, addressing climate impacts across different terrains. Over four years, it will reduce risks, lower costs, and enhance turbine longevity. The project is part of the Horizon Europe program (grant No 101083716).
