Vanadium Redox Flow Battery System Power Loss Optimization: Genetic Algorithm based Approach

Abstract

Vanadium Redox Flow Battery (VRFB) storage is getting prominence due to its long life cycle. In addition, the unique feature offered by VRFB storage in scaling the power capacity and energy capacity individually has also assisted the rising large scale implementation of VRFB storage as a replacement to the existing energy storage technologies. The proposed work describes the optimization of overall power loss of the VRFB system using Genetic Algorithm (GA) for the first time. Stack power loss and pump power loss are both taken into account at the same time during the multi-variable optimization. The proposed work has been validated by charge-discharge operation data set of a practical 1kW6h VRFB system using four distinct electrolyte flow rates. From the GA based optimization, it has been found that an optimal flow rate of around 6 L/min results in the lowest overall VRFB system power loss for the stack currents of 40A and 50A. The proposed topology can be highly effective for increasing the overall efficiency of scalable VRFB storage, hence assuring the dependability of VRFB integrated power system applications.