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optimise battery charging/discharging with hourly electricity prices
The open source repository for Electricity Maps App and data parsers that enables a real-time visualisation of the CO2 emissions of electricity consumption
A web interface for running PyPSA scenarios using the snakemake workflow
Online optimisation tool for wind+solar+storage systems
The City Energy Analyst (CEA)
Kspider 是一个爬虫平台，以图形化方式定义爬虫流程，无需代码即可实现一个爬虫流程，Kspider不仅限爬虫，也可用于WEB自动化测试，更多功能等你探索。
PyGWalker: Turn your pandas dataframe into an interactive UI for visual analysis
Chargym simulates the operation of an electric vehicle charging station (EVCS) considering random EV arrivals and departures within a day. This is a generalised environment for charging/discharging…
Optimize your consumption, production and batterystorage of electricity with dynamic prices
Open-source Distributed Energy Resources (DER) Model that represents IEEE Standard 1547-2018 requirements for steady-state and dynamic analyses
The aim of this notebook is to build a model for forecasting electricity prices in Spain. It's based on the datasets provided by: https://www.kaggle.com/datasets/nicholasjhana/energy-consumption-ge…
✨ Local and Fast AI Assistant. Support: Web | iOS | MacOS | Android | Linux | Windows
Chatbot for documentation, that allows you to chat with your data. Privately deployable, provides AI knowledge sharing and integrates knowledge into your AI workflow
基于大模型搭建的聊天机器人，同时支持 微信公众号、企业微信应用、飞书、钉钉 等接入，可选择GPT3.5/GPT-4o/GPT-o1/ Claude/文心一言/讯飞星火/通义千问/ Gemini/GLM-4/Claude/Kimi/LinkAI，能处理文本、语音和图片，访问操作系统和互联网，支持基于自有知识库进行定制企业智能客服。
Codes for the paper "Multivariate probabilistic forecasting of electricity prices with trading applications" ( I Agakishiev, WK Härdle, M Kopa, K Kozmik, and A Petukhina
Code implementation of “Flexible Coordination of Wind Generators and Energy Storages in joint Energy and Frequency Regulation Market“
Modeling time series of electricity spot prices using Deep Learning.
Developed a time series model for forecasting day-ahead electricity prices of biding zone DK1 (Denmark) using data from Entsoe and OpenWeatherMap. Model performance is evaluated using walk-forward …
Harvard CS109: A predictive model for electricity prices in the midwest, and more specifically, the prices of nodes where nuclear plants are located
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
31761 - Renewables in Electricity Markets
atlite: A Lightweight Python Package for Calculating Renewable Power Potentials and Time Series
Wind power visualization with WebGL particles
Panel: The powerful data exploration & web app framework for Python
NN for predictions of electricity prices in Spain's wholesale market based on gas and CO2 prices
GUI-based Python code generator for data science, extension to Jupyter Lab, Jupyter Notebook and Google Colab.