Roozbeh Bakhshi of Center for Advanced Life Cycle Engineering (CALCE) UMD

The rise of energy prices, concerns over climate change and geopolitical issues have brought special attention to renewable energies and wind energy in particular. Based on NREL projections, the United States has more than 32,000 TWh of onshore and 17,000 TWh of offshore wind power generation potential, which is far beyond its 11,000 TWh of current annual electricity consumption However there are a number of efficiency challenges that must be overcome in order to turn this potential into actual production. One area that can potentially improve the energy production of wind turbines is the correction of yaw error. Yaw error (also referred to as yaw angle or yaw misalignment) is the angle between the turbine`s rotor and the wind direction. A yaw error reduces turbine`s power production at wind speeds of less than the rated speed.

Besides impacting the power producing ability of a turbine, yaw error also affects the reliability of critical subsystems in wind turbines. Variation in yaw error (at any wind speed and not only below the rated speed) affects the loads on the components and the subsequent mechanical stresses. These mechanical stresses change the damage accumulation for components and sub-assemblies, which ultimately affects their reliability. About 17 to 28% of wind project costs are attribute to O&M costs, which are directly affected by the reliability.

LIDAR devices use laser beams to detect the wind speed and direction from miles ahead. Using LIDAR will give a near perfect alignment of turbine with the wind direction, which subsequently improves the turbine energy production and reliability. However, LIDAR devices are expensive and there is a trade-off between the costs of LIDAR and its financial benefits. In this work, a stochastic return on investment model is developed to illustrate how LIDAR devices can benefit the farm owner and manufacturers.

Biography:

Roozbeh Bakhshi received his B.S degree in Mechanical Engineering from the K.N. Toosi University of Technology, Tehran, Iran, and his M.S. degree in Mechanical Engineering from the University of Maryland, College Park, MD, USA. He is currently pursuing his Ph.D. degree in Mechanical Engineering at the Center for Advanced Life Cycle Engineering (CALCE) at University of Maryland, College Park, MD, USA.

His research interests include reliability, life cycle cost modeling and return on investment analysis.

Address:Maryland, United States

Roozbeh Bakhshi of Center for Advanced Life Cycle Engineering (CALCE) UMD

Biography:

Address:Maryland, United States