Maximizing the returns of LIDAR systems in wind farms for yaw error correction applications. Issue 6 (18th February 2020)

• Record Type: Journal Article
• Authors: Bakhshi, Roozbeh; Sandborn, Peter
• Is Part Of: Wind energy. Volume 23:Issue 6(2020)
• Page Start: 1408
• Page End: 1421
• Publication Date: 2020-02-18
• Subjects: Financial Engineering -- LIDAR -- Wind Energy -- Net Present Value (NPV) -- Return on Investment (ROI) -- Yaw Error -- Yaw Angle; Wind power -- Periodicals; 621.312136
• DOI: 10.1002/we.2493
• Languages: English
• ISSNs: 1095-4244

Abstract

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.