Wind Energy. 2020;1–14, February 2020, DOI: 10.1002/we.2493

Maximizing the Returns of LIDAR Systems in Wind Farms for Yaw Error Correction Applications


Roozbeh Bakhshi and Peter Sandborn
CALCE, Center for Advanced Life Cycle Engineering,
Department of Mechanical Engineering,
University of Maryland, College Park, Maryland 20742, USA

Abstract:

Wind energy is an important source of renewable energy with significant untapped potential around the world. However, the cost of wind energy production is high, and efforts to lower the cost of energy generation will help enable more widespread use of wind energy. Yaw error reduces the efficiency of turbines as well as lowers the reliability of key components in turbines. Light detection and ranging (LIDAR) devices can correct the yaw error; however, they are expensive, and there is a trade‐off between their costs and benefits. In this study, a stochastic discrete‐event simulation was developed that models the operation of a wind farm. We maximize the net present value (NPV) changes associated with using LIDAR devices in a wind farm and determine the optimum number of LIDAR devices and their associated turbine stay time as a function of number of turbines in the wind farm for specific turbine sizes. The outcome of this work will help wind farm owners and operators make informed decisions about purchasing LIDAR devices for their wind farms.

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

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