Smart grids and microgrids are the future of the power system we use today. Integrating the power systems with communication devices and adding a data layer has its perks for power system operators as well as the consumers.
This novel power system will generate enormous amounts of data with its maturity. As researchers, it is quite fascinating for us since this means that we get to combine two disciplines, Machine Learning & Power Systems.
In this blog post, I will list all the possible applications that I come across of machine learning in power systems.
Update: I will start to categorize them into,
- Microgrid research
- Energy forecasting
- Smart grid research
Microgrid research
- Multi-agent systems for microgrid control [link]
- Reinforcement learning for microgrid energy management
- Detect security breaches
- Fault detection and classification
- Microgrid islanding detection
- Multi-agent reinforcement learning for microgrid control
Energy forecasting research
- Solar energy forecasting / Solar irradiation forecasting
- Power system demand forecasting
Smart grid research
- Detect security breaches
- Fault detection and classification
- Data compression in smart grids [link]
