A Computational Approach for Predicting the Short-Term Output Power of a Wind Turbine in an Urban Area

This paper presents an approach aimed at estimating the anticipated power output of a wind turbine by leveraging real-time and forecasted wind speed data sourced from the Internet. The methodology incorporates exponential smoothing techniques to reduce forecasting inaccuracies. Additionally, it introduces a mechanism for data storage and visualization of prediction outcomes on the user interface, enhancing user convenience.