Florida International University

Alexander Joseph Stevenson

Arif I Sarwat

Asadullah Khalid

Systems, architectures, devices, and methods for the resilient artificial intelligence-based data-driven dispatch of a battery energy storage system (BESS) are provided. A Mixed-Integer Linear Programming-based BESS dispatch scheduling algorithm utilizes location-specific weather data to forecast photovoltaic generation, load consumption, and grid outages using a plurality of machine learning models, in combination with market data to optimize energy dispatch decisions. A sustainable solution is provided for enabling improved load management during islanded conditions, providing advance operator alerts to enhance safety, and delivering economic benefits by minimizing unplanned outages, reducing associated financial losses, and offsetting high capital costs of BESS deployment through optimized utilization.

System and methods for the resilient AI-based data-driven dispatch of a battery energy storage system

Testbeds for battery management systems (BMSs) and/or batteries, as well as methods of using the same, are provided. A testbed can be a control-hardware-in-the-loop (CHIL) testbed and can include a simulation bench including a battery cell simulator, a temperature simulator, and/or a real-time simulator. The simulator bench can further include a programmable power supply, a relay, a resistor, and/or a communication protocol.

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Miami, FL, United States of America

Alexander Joseph Stevenson