Proceedings of the ASME 2018 Power and Energy Conference, PowerEnergy2018, June 24-28, 2018, Lake Buena Vista, FL, USA

Using LIDAR on Wind Turbines for Yaw Error Correction: A Financial Prospective

Roozbeh Bakhshi and Peter Sandborn
CALCE, Center for Advanced Life Cycle Engineering, Department of Mechanical Engineering, University of Maryland, College Park, Maryland 20740, USA


T he rise of sustainable energies and wind energy in particular has created new challenges . Wind energy and especially offshore wind energy face s an uphill battle in the United States to become a mainstream source of energy generation due to its high price relative to fossil fuels . The w ind industry is looking for methods to reduce the costs of energy production by improving the efficiency of wind turbines and reducing their operation and maintenance costs. Correction of yaw error is one way to lower th e price of wind energy . Yaw error is the angle between the turbine’s central axis in horizontal plane and the wind flow direction. LIDAR devices are used to correct yaw error, however they are expensive. Therefore, there is a need to develop a return on inv estment model (ROI) to calculate the cost trade offs of using such systems. In this work, we review how yaw error affects the performance and maintenance costs of wind turbines , discuss the development of an ROI model and provide a case study w ith two scenarios where LIDAR is used to correct the yaw error of an onshore and an offshore wind farm.

This article is available online here and to CALCE Consortium Members for personal review.

[Home Page] [Articles Page]
Copyright © 2018 by CALCE and the University of Maryland, All Rights Reserved