Authors: Siyang Li, Hui Xiong, Yize Chen Hong Kong University of Science and Technology (Guangzhou)
This is the repository for the paper ["DiffCharge: Generating EV Charging Scenarios via a Denoising Diffusion Model"]{https://arxiv.org/abs/2308.09857}.
Recent proliferation of electric vehicle (EV) charging events has brought prominent stress over power grid operation. Due to the stochastic and volatile EV charging behaviors, the induced charging loads are extremely uncertain, posing modeling and control challenges for grid operators and charging management. Generating EV charging scenarios would aid via synthesizing a myriad of realistic charging scenarios. we propose a novel denoising Diffusion-based Charging scenario generation model DiffCharge, which is capable of generating a broad variety of realistic EV charging profiles with distinctive temporal properties.
To generate EV charging curves using trained model, run
Questions? Contact Siyang at sli572@connect.hkust-gz.edu.cn.