Unscented H-infinity Wind Speed Estimation and H-infinity Control of Wind Turbines
Date
2021-05-13
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Abstract
Wind energy is a fast-growing industry in Canada and worldwide. As wind turbine size and capacity increase, control systems become exceedingly important to maximize the efficiency of the power output and to reduce loads to extend their longevity. This thesis aims to provide better knowledge of the input wind speed and to design turbine control based on this normally unknown input. First, non-linear robust methods of state estimation are introduced in order to deal with the nonlinearities present in the wind turbine model and the large exogenous disturbance of wind speed. Specifically, the unscented Kalman filter and an algorithm for the unscented H-infinity filter and their variants are analyzed in a case study for robustness and accuracy. An augmented unscented H-infinity scheme is then adopted in combination with a data fusion technique to estimate effective wind speed (EWS). This technique utilizes high frequency data from the anemometer and treats the turbine as a sensor to fuse them as one EWS measurement. The EWS is used to determine the optimal tip speed ratio (TSR) for the reference for the turbine. This is accomplished with a mixed sensitivity H-infinity tracking controller to optimize power output. The results show up to 15% improvement from the baseline controller for a 5 MW turbine and consistently high power output for a 1.5 MW turbine.
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Keywords
wind speed estimation, Kalman filter, H-infinity filter
Citation
Owen, E. (2021). Unscented H-infinity Wind Speed Estimation and H-infinity Control of Wind Turbines (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.