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Research tools for the Adaptive Charging Network
A Python tool for distributed model-based predictive control of energy suppy chains
Greenhouse gas emissions data packaged for easy exploration and charting
This project implements blockchain applications for climate action and accounting, including emissions calculations, carbon trading, and validation of climate claims. It is part of the Linux Founda…
Decentralized emission trade market built on the Blockchain.
Code for "Machine learning pipeline for battery state-of-health estimation"
Lithium ion battery state of health estimation and remaining useful life prediction using ELM
State of health (SOH) prediction for Lithium-ion batteries using regression and LSTM
MeteoNet's toolbox and documentation
A set of documented functions for simulating the performance of photovoltaic energy systems.
The windML framework provides an easy-to-use access to wind data sources within the Python world, building upon numpy, scipy, sklearn, and matplotlib. Renewable Wind Energy, Forecasting, Prediction
Python client libraries for ISO and other power grid data sources.
The Public Utility Data Liberation Project provides analysis-ready energy system data to climate advocates, researchers, policymakers, and journalists.
A tool to quickly and easily create inputs for power systems models
This R package provides a crawler to scrape the European Energy Market EPEX SPOT at https://www.epexspot.com and the European Energy Exchange at https://www.eex.com
Python library for fetching Nord Pool spot prices.
ETL that builds a data warehouse in redshift with energy data from ENTSOE Transparency Platform
Forecasts next 24 hours of hourly energy demand with Keras, Prophet, and SARIMA (statsmodels)
An end-to-end electrical load forecast prediction service
A real-time visualisation of the CO2 emissions of electricity consumption
A real-time visualisation of the CO2 emissions of electricity consumption
Python client for the ENTSO-E API (european network of transmission system operators for electricity)
Spark tutorial using Zeppelin notebooks.
Activities and exercises for the Part IA computing course in Michaelmas Term
Dataset of GPT-2 outputs for research in detection, biases, and more
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Code for the paper "Language Models are Unsupervised Multitask Learners"