Artificial intelligence (AI) control strategies for Energy Storage Systems

Artificial intelligence (AI) control strategies for Energy Storage Systems

Background: In a shipboard power system with energy storage systems (ESSs), e.g., battery and supercapacitor, and renewable energy source, e.g., fuel cell, a coordinated control behavior is required for the system. As a result, the shipboard power system can be considered as a single, self-sufficient entity. Using ESSs has several advantages in marine systems, including regulating the power to provide consistent power for the sensitive loads during the operation mode switching and reduce the supply-demand mismatch.

Objective: The main objective of the project is to use AI to design an optimal control strategy for fuel cell integrated with ESS, which is a combination of ultracapacitor and lithium-ion battery to regulate the bus voltage and quickly respond to disruptive events. As a result, AI could allow a shipboard power system to become self-regulating by forecasting and balancing the load and supply.

Collaborator: Wärtsilä