Coupling Dynamics for Power Systems with Iterative Discrete Decision Making Architectures

USF inventors have developed a power system control method that uses machine learning as a method of decision making within the system. The system is decentralized as it uses multiple control agents to perform decision making while limiting the exchange of information, protecting information privacy. This invention is applicable to the development of smart buildings, electric power system networks, and advanced energy storage systems.  

Competitive Advantages:

•     Multiple control centers
•     Does not overburden any processing units
•     Ensures security of sensitive information

Schematic of the Control System 

Desired Partnerships:

• License
• Sponsored Research
• Co-development