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Using digital filtering techniques as an aid in wind turbine data analysis

provide a stable baseline against which operational HAW data can be compared. Research involving very large sets of digital data is often difficult due to the enormity of the database. In the case of a wind turbine operating under varying environmental conditions, determining which data are representative of the blade aerodynamics and which are due to transient flow ingestion effects or errors in instrumentation, operation, and data collection is of primary concem to researchers. The National Renewable Energy Laboratory in Golden, Colorado collected extensive data on a downwind horizontal axis wind turbine ( H A W during a turbine test project called the Combined Experiment. A principal objective of this experiment was to provide a means to predict H A W aerodynamic, mechanical, and electrical operational loads based upon analytical models of aerodynamic performance related to blade design and inflow conditions. In a collaborative effort with the Aerospace Engineering Department at the University of Colorado at Boulder, a team of researchers has evolved and utilized various digital filtering techniques in analyzing the data from the Combined Experiment. Introduction Wind is a readily available, non-polluting renewable source of energy. Yet, wind enetgy currently accounts for a very small percentage of power produced in the United States because costs remain comparatively high. A major problem with wind energy costs is that wind turbines have shorter lifetimes than that predicted by wind tunnel tests. Wind turbines, designed to last 20 to 30 years, often break after only 2 to 3 years in the field. It is suspected that environmental aerodynamic effects are responsible for large transient loads which damage the wind turbines and their blades. If these effects were fully characterized and understood, turbines could be designed to minimize the damage now caused by the unexpectedly large transient loads. Such improvements could reduce the costs of wind energy to half of the current levels, making wind energy competitive in cost to conventional energy sources. A preliminary analysis of the data set was performed to determine how to best approach the data. A filter based upon data norms was employed to identify and correct anomalous data, most of which appeared to arise from equipment malfunctions. Likewise, a filter was utilized to smooth noise in the data. Thereafter, a determination of the stochastic distribution of the data was made. Several different filtering techniques were then employed to obtain a reduced data set based upon this preliminary analysis. The reduced data set emphasized selection of inflow conditions such that the aerodynamic data could be compared directly to wind tunnel data obtained for the same airfoil design as used for the H A W S blades. It will be shown that this reduced data set has yielded valid, reproducible results that a simple averaging technique or a random selection approach cannot achieve. These findings A primary focus of the National Renewable Energy Laboratory (NREL) is the study of wind energy in an attempt to maximize energy production, minimize cost, and eliminate the associated problems. Currently wind tunnel tests are used to predict the loads and thus the lifetimes of the blades, gearboxes, and generators but are conducted only under fairly constant, low turbulence conditions. However, the operational environment of wind turbines is quite different than that in a wind tunnel. They must operate across a variety of environmentally-induced inflow conditions and even within turbine-induced inflow conditions such as those experienced in wind farms. To bridge the gap between wind tunnel testing and wind turbine operational aerodynamics, NREL designed the Combined Experiment. This experiment consists of a highly instrumented horizontal axis wind turbine ( H A W operating at Rocky Flats, a few miles south of Boulder, Colorado. The extensive data obtained from the Combined Experiment must be evaluated to (1) reveal the operating characteristics encountered by H A M S in the field and (2) to discern the relations between wind tunnel tests and field runs.