FUJIWARA Masaki, a second-year pre-doctoral student in the Electrical Engineering Program at the Graduate School of Science and Technology (Power System Laboratory; academic supervisor: Associate Professor KAWASAKI Shoji), received the Encouragement Award at the 2024 Joint Technical Meeting on Power Engineering and Power Systems Engineering of the Institute of Electrical Engineers of Japan (September 19 and 20, Tohoku University).
FUJIWARA Masaki proposed a wind power generation output prediction method, which combines a switching method that includes data smoothed by an exponential moving average line in its switching conditions, in order to understand the fluctuation trend of wind speed, and altitude correction using a roughness length determination method that takes into account the magnitude of wind speed, and presented the results of verifying the usefulness of the proposed method by case studies.
Title: A Study on Wind Power Generation Output Prediction by Switching Machine Learning Considering Surrounding Regional Altitude Differences and Wind Speed Fluctuation Trends
Author: FUJIWARA Masaki, KAWASAKI Shoji
≪Japanese version≫
