LSTM-based-Short-Term-Wind-Power-Forecasting

In this study, an advanced version of RNN known as Long Short-Term Memory (LSTM) networks is used for wind power prediction. This implementation contains stacked LSTM and bidirectional LSTM models for short term (hour a head) wind power forecasting. Supported Python version to run this code is 2.7 with google tensor flow deep learning library. Use runProject.py as project startup file.