Predictive control-based flow battery energy storage system for microgrid peak shaving

The incorporation of energy storage systems, particularly vanadium redox flow batteries (VRFBs), is critically significant for the operation of microgrids, facilitating effective peak shaving and load balancing. VRFBs exhibit essential attributes such as high flexibility, fast response times, and prolonged operational lifespans, rendering them particularly advantageous for small-scale microgrid applications. Building upon this foundation, the present study proposes a novel microgrid system that is fundamentally based on VRFB technology. This system integrates biomass gasification and solid oxide fuel cells (SOFCs) as primary power generation sources, thereby ensuring a reliable and consistent electricity supply that is specifically tailored to the energy requirements of rural areas. To enhance the charge-discharge efficiency of VRFBs, a new predictive control methodology is introduced, aimed at maximizing the utilization of energy stored within the batteries. This predictive control approach dynamically modifies battery operations in response to real-time battery conditions and projected load demands. The study also assesses peak-shaving strategies in terms of their effectiveness in mitigating demand peaks and enhancing grid stability. In comparison to traditional fixed control methods, the proposed predictive control strategy demonstrates superior intelligence and adaptability, allowing for seamless adjustments to the fluctuating power needs of microgrid systems. By significantly improving the efficiency of VRFBs and lowering operational costs, this innovative approach has the potential to advance the sustainability and resilience of microgrid infrastructures.