PVLearn: Reinforcement Learning for smart photovoltaic energy management

This project is closed.

Intelligent energy management is key to integrate renewable energy systems into the electrical grid. Photovoltaics as generators and electrical batteries as storage are the main components for this.

This project will investigate PV-battery energy management using reinforcement learning. We have developed in-house code for RL and battery as well as electricity demand (www.citylearn.net). PV systems can be simulated using available libraries.

We are looking for a CS/EE/ECE student who is interested in exploring this area with great potential. If successful, the results might be implemented in a real life environment.

Project Website
Intelligent Environments Laboratory
Qualifications

Python coding is a must
C/C++ is helpful
Knowledge in PV systems is beneficial but not necessary
Knowledge in machine learning and reinforcement learning is beneficial

Duties

Simulate PV systems using PVLIB in Python
Simulate battery systems in Python
Integrate building electricity demand simulation with PV & battery
Integrate control algorithm

Typical Time Commitment
10
Desired Length of Commitment
1
Tags
python
artificial intelligence
smart buildings
photovoltaics
reinforcement learning
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Project Lead
Who to Contact
Zoltan Nagy
Contact Email
nagy@utexas.edu

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