Tobi-Tob/TransformersForEnergyManagement
In this repository, we explore the application of Transformer-based Reinforcement Learning approaches to solve complex real-world energy management problems using the CityLearn environment (Challenge 2022 and 2023).
This project helps urban energy managers and building operators automatically optimize building energy consumption to reduce greenhouse gas emissions and support the electrical grid. It takes in real-time building sensor data and grid conditions, and outputs optimized control signals for building systems like HVAC and battery storage. The system aims to balance energy efficiency, occupant comfort, and resilience during power outages.
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Use this if you manage a portfolio of buildings and want an advanced, autonomous system to optimize their energy usage in response to grid demands while maintaining tenant comfort.
Not ideal if you are looking for simple energy monitoring or manual control recommendations, rather than an autonomous control system.
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Python
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Last pushed
Dec 12, 2023
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