"A Hybrid LSTM-LightGBM Model for Precise Short-Term Wind Power Forecas" by Md Omer Faruque, Md Alamgir Hossain et al.
This paper proposes a novel hybrid model that combines long short-term memory (LSTM) with light gradient boosting (LightGBM) to achieve precise onshore wind power prediction in Australia. The intermittent nature of renewable energy sources like wind power necessitates accurate forecasting to minimize operational costs and enhance power system reliability and security. The hybrid model showcases promising results in forecasting 15-minute interval short-term wind generation data. Performance is evaluated using root mean squared errors (RMSE) and means absolute errors (MAE), and compares the prop...