Modern control design methods like non-linear model predictive control can take account of complex dynamics and actuator constraints, while making use of richer information input from advanced sensors such as LIDARs. They contribute to the coordinated control of entire wind farms while meeting new operational demands from the electricity system. The session addresses advanced state estimation methods, an important component of such controllers. You will hear about field test results from a controller using wind preview from a LIDAR sensor as well as changes in design and certification guidelines needed to account for the use of LIDARs.

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Learning objectives

• Advanced non-linear state estimation techniques for wind turbines that run in real time;
• Non-linear model predictive control that rung in real time and improve performances;
• A LIDAR-assisted flatness-based controller validated in field tests;
• Requirements for design and certification of wind turbines with LIDAR assisted control;
• A wind farm control framework that can mitigate wake effects and provide grid balancing services.