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+# DiffCharge: Generating EV Charging Scenarios via a Denoising Diffusion Model
+
+Authors: Siyang Li, Hui Xiong, Yize Chen
+Hong Kong University of Science and Technology (Guangzhou)
+
+![EV Charging Scenarios](Charging_DiffCharge.png)
+
+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.
+