Python基于深度学习的风机发电风速及功率预测项目源码+权重文件

# Deep-Spatio-Temporal Code for [Deep Spatio-Temporal Wind Power Forecasting](https://arxiv.org/abs/2109.14530) ## How to use The model is validated on two datasets. ### Wind power forecasting This dataset is from https://aml.engr.tamu.edu/book-dswe/dswe-datasets/. The data used here is Wind Spatio-Temporal Dataset2. Download data, put it into the './data' folder and rename it to 'wind_power.csv'. Then, run following ``` python train.py --name wind_power --epoch 300 --batch_size 20000 --lr 0.001 --k 5 --n_turbines 200 ``` ### Wind speed forecasting The model performance on wind speed forecasting is validated on NREL WIND dataset (https://www.nrel.gov/wind/data-tools.html). We select one wind farm with 100 turbines from Wyoming. To get data, first run ``` python getNRELdata.py ``` Then run ``` python train.py --name wind_speed --epoch 300 --batch_size 20000 --lr 0.001 --k 9 --n_turbines 100 ```