Title: MAXIMIZING THE FINANCIAL RETURNS OF USING LIDAR SYSTEMS IN WIND FARMS FOR YAW ERROR CORRECTION APPLICATIONS
Date: Tuesday, November 5th, 2019
Time: 8:00am
Location: DeWalt Conference Room Martin Hall (EGR-2162
Committee:
Professor Peter Sandborn (Chair)
Professor Patrick McCluskey
Professor Abhijit Dasgupta
Professor Laurent Fresard
Professor James Baeder (Dean’s Representative)
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. Ideally, wind turbines have to be aligned with wind flow at all times. However, this is not the case and there exists and angle between a wind turbine nacelle’s central axis and the wind flow. This angle is called yaw error. Yaw error lowers the efficiency of turbines as well as lowers the reliability of key components in turbines. LIDAR devices can correct the yaw error; however, they are expensive and there is a trade-off between their costs and benefits. In this dissertation, a stochastic discrete-event simulation is developed that models the operation of a wind farm. By maximizing the Net Present Value (NPV) changes associated with using LIDAR devices in a wind farm, the optimum number of LIDAR devices and their associated turbine stay time will be determined. These optimum values are a function of number of turbines in the wind farm for specific turbine sizes. The outcome of this dissertation will help wind farm owners and operators to make informed decisions about purchasing LIDAR devices for their wind farms.