Cohort Level: Cohort - II

Career Goal: I plan on continuing research related to atmospheric science and/or renewable energy.

Expected Graduation Date: May 20, 2021

Degree: M.S Mechanical Engineering

Research Title: Reduction of Wind Power Prediction Uncertainty from Meteorological Characterization using Decision Tree

Research Synopsis: A new method utilizing machine learning algorithms is introduced to group atmospheric variables such as wind speed, wind shear, vertical wind profile shape, and environmental lapse rate and to relate them to 10-minute average power production from an operational wind turbine. The dataset used in this study consists of measurements from a scanning Doppler wind lidar, a meteorological tower, and a 2MW coastal turbine during the VERTical Enhanced miXing campaign (VERTEX).