Distributed control

At present, different individual pitch control (IPC) algorithms are available for the reduction of blade loads. Although these can lead to large reduction of the 1P (once per revolution) blade loads, the resulting cyclic pitching of the blades easily reaches the speed limits of the blade pitch actuators. For achieving 2P, 3P and higher blade load reduction with IPC, a much wider (practically infeasible) bandwidth of the pitch actuators is required. To circumvent this bandwidth restriction, actuation mechanisms that influence the local aerodynamic characteristics of the blades can be used, such micro-electro-mechanical translational tabs and trailing edge flaps. Such actuation devices have a much broader bandwidth, allowing for higher harmonics control. 

“Smart” sensors and other control enabling technologies have generated an emerging research agenda in the scientific wind power community. Already, a lot of projects worldwide are exploring the technological feasibility of a future generation of blades, which - through the means of embedded intelligence - achieves superior possibilities for fast, reliable and active load control though spanwise distributed devices. While promising lines of enquiry and candidate sensor and actuation principles are being investigated in largely parallel efforts, only little research has so far been done into system integration - and more particularly into the optimal design of control structures, on the stability and the interaction between the local control loops, the use of more advanced multivariate control techniques, the interactions between the blades and the effect on the loads of other turbine components. For a detailed stability analysis and control design, appropriate linearized turbine models with realistic blade-element effective wind speed signals, should be available. Such models can be derived using the ECN software TURBU and allow for the analysis and design of sophisticated and reliable control algorithms for fatigue reduction at reasonable computational burden. In 2010 an initial scoping analysis will be completed within the UpWind project.