A Deep Reinforcement Learning based approach for energy supply management in MicroGrids
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Updated
Mar 16, 2021 - Jupyter Notebook
A Deep Reinforcement Learning based approach for energy supply management in MicroGrids
Operational & economic simulation of Microgrid projects. Python package of the Microgrids.X family.
Operational & economic simulation of Microgrid projects. Julia package of the Microgrids.X family.
OpenModelica_Microgrids is a library to simulate three phase AC Microgrids. Usable as stand-alone version or part of the toolbox OpenModelica Microgrid Gym (https://github.com/upb-lea/openmodelica-microgrid-gym).
The Cyber-Informed Engineering Microgrid Analysis Tool (CIEMAT) can inform engineering and traditional cybersecurity mitigations to make Microgrid Site Installation more resilient to cyber attack and its impact.
A simple microgrid energy balance modeling tool used for education and first-order estimation of renewable energy impacts on grids.
Code for the lab's published articles on the topic of "Economic Dispatch of a Single Micro-Gas Turbine Under CHP Operation"
Renewable Energy Maximization for Pelagic Islands Network of Microgrids Through Battery Swapping Using Deep Reinforcement Learning
This repository contains the final course project entitled “Event-Based Control of DC-DC Converters Connected to Constant Power Loads”
Operational & economic simulation of Microgrid projects. Matlab/Octave package of the Microgrids.X family.
Real-Time Smart Grid Control System for Hydropower Retrofit (Typhoon HIL & Modbus Integration)
An open-source architecture for AI data centers that use zero freshwater. This repo provides practical designs for replacing evaporative cooling with closed-loop immersion, heat-to-power recovery, and adaptive AI-based thermal control, reducing water usage by 100% and energy demand by up to 20%.Built through a cross-AI collaboration.
Package for dynamical modeling of power grids. To cite this Original Software Publication: https://www.sciencedirect.com/science/article/pii/S2352711021001345
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