Synthetic Time Series Generation using Generative Adversarial Network in Smart Grid

Code that replicate work Generative Adversarial Network for Synthetic Time Series Data Generation in Smart Grids.

Note that in this repo, we change our model to ACGAN instead of the original Conditional GAN.

Focus on periodic time series with daily, weekly and yearly patterns including load and PV generation.

Package Requirements

tqdm==4.30.0
numpy==1.16.2
Keras==2.2.4
tensorboardX==1.6
tensorflow==1.15
tensorboard==1.13.0

Usage

Example:

• To train a model using Pecan Street Dataset for user with id 171, run

python main.py --train --num_epoch 100 --id 171

• To generate synthetic data, run

python main.py --id 171

License

MIT