This article presents an ensemble Kalman filter algorithm for wind energy forecasting, which combines the benefits of ensemble forecasting and Kalman filter techniques.
This study proposes a novel approach for wind energy forecasting using an ensemble Kalman filter algorithm, which is compared with other state-of-the-art methods.
The National Renewable Energy Laboratory (NREL) discusses the application of ensemble Kalman filter algorithms for renewable energy forecasting, including wind energy.
This tutorial provides an introduction to the ensemble Kalman filter algorithm and its application in various fields, including wind energy forecasting.
This paper presents a review of ensemble methods for wind power forecasting, including the ensemble Kalman filter algorithm.
This study proposes an ensemble Kalman filter algorithm for wind speed forecasting, which is evaluated using real-world data.
This video provides an introduction to the ensemble Kalman filter algorithm and its application in various fields, including wind energy forecasting.
This GitHub repository provides an implementation of the ensemble Kalman filter algorithm in Python, which can be used for wind energy forecasting.