Wind Energy are today developed mainly as large wind farms or clusters of wind farms, offshore or land-based. Attention is on reducing costs and increasing profitability. This can be achieved through design optimization, but also by optimizing the operation and maintenance. The focus of OPWIND is the latter.
Stat-of-the-art wind power plants (WPP = wind farm or cluster of wind farms) apply advanced monitoring and control functions, but not optimized in terms of at all times maximizing the power production balanced against turbine loading and electricity price. This latter requires the use of real time dynamic models of WPP and wind flow interactions, and combining these with monitoring data of WPP operation to calculate the optimized dispatching of relevant control set-points between the wind turbines. OPWIND will address this research challenge to develop knowledge and tools for optimized operation and control of wind power plants, reducing costs and increasing profitability.
The work is organized into four work packages each addressing a distinct research challenge: WP1 will develop a scalable state-space model of a wind power plant, for modal analysis, simulation, state observation, and control design at the plant level. In WP2 research will be undertaken to bridge the gap between high fidelity atmospheric simulations and real-time applications. Tools developed in WP1 and WP2 will be integrated in WP3 to deliver a unified atmosphere/wind power plant model for analysis and real-time control. In WP4, the models are applied and validated by case studies in dialogue with the user partners, possibly including an experimental campaign at a wind test site.
OPWIND is timely and highly relevant. It will link with the international research community through EERA JP wind and IEA Wind Task 37, and it will create useful results for society at large and the user partners in particular, including wind farm operators, service providers and OEMs.