Sunwoda Electronic Co., Ltd, and Tsinghua Berkeley Shenzhen Institute (TBSI) generate the TBSI Sunwoda Battery Dataset. We open-source this dataset to inspire more data-driven novel material verifi…

Code for PulseBat dataset. We use conditional variational autoencoder to generate sufficient pulse voltage response data across random battery SOC retirement conditions, facilitating rapid, accurat…

A real-world dataset for EV-related research, e.g., spatiotemporal prediction and urban energy management.

🍒 Cherry Studio is a desktop client that supports for multiple LLM providers. Support deepseek-r1

Get up and running with Llama 3.3, DeepSeek-R1, Phi-4, Gemma 2, and other large language models.

[KDD'2024] "UrbanGPT: Spatio-Temporal Large Language Models"

An extension package of PowerModels.jl for Stochastic (Optimal) Power Flow

This repository contains the Matpower files of a synthetic network model for National Electricity Market (NEM) of Australia.

Battery charging schedule optimization to minimize lithium-ion battery degradation.

Predict battery state of charge (SOC) using machine learning + Streamlit web app.

Julia installer and version multiplexer

open testbench for control and optimization methods for the energy management of a simple solar home

Personal analysis of the "Solar home electricity" dataset from Ausgrid

Public Release of Julia and Python code and data from CSIRO's Low-Voltage Feeder Taxonomy (LVFT) Study

Represent trained machine learning models as Pyomo optimization formulations

Query the OSM Overpass API and get a GeoDataFrame

Open-source no-code web data extraction platform. Turn websites to APIs & spreadsheets with no-code robots in minutes.

PulseBat dataset for retired battery reuse and recycling decision making. We open-source the collected PulseBat dataset for pulse voltage response generation of the retired batteries across random …

Julia package to run Dynamic Power System simulations. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.

Transportation Networks for Research

Benchmarks for the Optimal Power Flow Problem with HVDC Lines

基于神经网络的通用股票预测模型 A general stock prediction model based on neural networks

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

Embed trained machine learning predictors in JuMP

Causal discovery algorithms and tools for implementing new ones

EV-EcoSim: A grid-aware co-simulation platform for the design and optimization of EV Charging Infrastructure. Link to publication: https://doi.org/10.1109/TSG.2023.3339374

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…

🦜🔗 Build context-aware reasoning applications