Wind power is the world's fastest growing renewable energy source, but operations and maintenance costs are still a major obstacle toward reliability and widescale adoption of wind power, accounting for a large part of the cost of energy for offshore installations. Structural health monitoring systems have been proposed for implementing condition-based maintenance. The wind energy industry currently uses condition monitoring systems that are mostly adapted from roating machinery in other power generation industries. However, these systems have had limited effectiveness on wind turbines because of their atypical operating conditions, which are characterized by low and variable rotational speed, rapidly varying torque, extremely large rotors and stochastic loading from the wind. Although existing systems primarily take measurements from the nacelle, valuable information can be extracted from the structural dynamic response of the rotor blades to mitigate potentially damaging loading conditions.
One such condition is rotor imbalance, which not only reduces the aerodynamic efficiency of the turbine and therefore its power output but can also lead to very large increases in loading on the drivetrain, blades and tower. The National Renewable Energy Laboratory's fast software was used to model both mass and aerodynamic imbalance in a 5 MW offshore wind turbine. It is shown that a combination of blade and nacelle measurements, most of which can be obtained from standard instrumentation already found on utility-scale wind turbines, can be formulated into an algorithm used to detect and locate imbalance. The method described herein allows for imbalance detection that is potentially more sensitive than existing on-line systems, while taking advantage of sensors that are already in place on many utility-scale wind turbines. Copyright © 2014 John Wiley & Sons, Ltd.