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Structural load mitigation control for wind turbines: A new performance measure

SummaryStructural loads of wind turbines are becoming critical because of the growing size of wind turbines in combination with the required dynamic output demands. Wind turbine tower and blades are therefore affected by structural loads. To mitigate the loads while maintaining other desired conditions such as the optimization of power generated or the regulation of rotor speed, advanced control schemes have been developed during the last decade. However, conflict and trade‐off between structural load reduction capacity of the controllers and other goals arise; when trying to reduce the structural loads, the power production or regulation performance may be also reduced. Suitable measures are needed when designing controllers to evaluate the control performance with respect to the conflicting control goals. Existing measures for structural loads only consider the loads without referring to the relationship between loads and other control performance aspects. In this contribution, the conflicts are clearly defined and expressed to evaluate the effectiveness of control methods by introducing novel measures. New measures considering structural loads, power production, and regulation to prove the control performance and to formulate criteria for controller design are proposed. The proposed measures allow graphical illustration and numerical criteria describing conflicting control goals and the relationship between goals. Two control approaches for wind turbines, PI and observer‐based state feedback, are defined and used to illustrate and to compare the newly introduced measures. The results are obtained by simulation using Fatigue, Aerodynamics, Structures, and Turbulence (FAST) tool, developed by the National Renewable Energy Laboratory (NREL), USA.
Renewable energy, Artificial intelligence, Environmental Engineering, Aerospace Engineering, FOS: Mechanical engineering, Control (management), Building Ventilation, Aerodynamics, Engineering, Maschinenbau, Control theory (sociology), Biology, Control engineering, Controller (irrigation), Urban Wind Environment and Air Quality Modeling, FOS: Environmental engineering, Computer science, Mechanical engineering, Agronomy, Wind Farm Optimization, Aerospace engineering, Analysis and Control of Axially Moving Dynamics, Control and Systems Engineering, Electrical engineering, Physical Sciences, Environmental Science, Wind Energy Technology and Aerodynamics, Wind power, Turbine
Renewable energy, Artificial intelligence, Environmental Engineering, Aerospace Engineering, FOS: Mechanical engineering, Control (management), Building Ventilation, Aerodynamics, Engineering, Maschinenbau, Control theory (sociology), Biology, Control engineering, Controller (irrigation), Urban Wind Environment and Air Quality Modeling, FOS: Environmental engineering, Computer science, Mechanical engineering, Agronomy, Wind Farm Optimization, Aerospace engineering, Analysis and Control of Axially Moving Dynamics, Control and Systems Engineering, Electrical engineering, Physical Sciences, Environmental Science, Wind Energy Technology and Aerodynamics, Wind power, Turbine
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