Power Management of Hybrid Flywheel-Battery Energy Storage Systems Considering the State of Charge and Power Ramp Rate

A flywheel and lithium-ion battery's complementary power and energy characteristics offer grid services with an enhanced power response, energy capacity, and cycling capability with a prolonged system lifetime. Real-time Power management and considering storage components' State of Charge (SoC) and ramp rate are crucial for optimizing performance. However, there is a need for further improvements in SoC correction techniques and rigorous, realistic testing to ensure accurate and efficient management strategies. This paper proposes a Moving Average (MA) and Fuzzy Logic-based power management for a Hybrid Flywheel and Battery Energy Storage System that optimally share the power among the two technologies, considering the flywheel's SoC and the battery's ramp rate as the most concerning variable of each technology. The system minimizes SoC and ramp rate imbalances by integrating Moving Averages for dynamic energy demand adjustments and Fuzzy Logic controllers for efficient power redistribution. A Power Hardware-in-the-Loop (PHIL) experimental validation utilizing a 120 kW, 7.2 kWh flywheel-based energy storage system coupled with a simulated battery demonstrates improved SoC correction and ramp rate management performance.