Intelligence-based battery management and economic analysis of an optimized dual-Vanadium Redox Battery (VRB) for a wind-PV hybrid system

Abstract

This paper proposes an intelligent battery management system (BMS) implementing two large Vanadium Redox Battery (VRB) flow batteries in a master-slave mode to provide grid-level energy storage for a wind-solar hybrid power system. The proposed BMS is formulated to effectively meet a predetermined power dispatch formulated based on forecasted wind and solar data while incorporating features like peak shaving and ramp rate limiting. It is compared to a single battery module operated system to showcase the advantages of the proposed intelligent dual battery module in terms of appreciable reduction in battery size and costs while exhibiting improved lifecycle performance. The battery size is optimized based on heuristic optimization algorithms and modelled in Matlab/Simulink environment. An intelligent fuzzy-based BMS is used to control the dual VRB model to ensure optimized power sharing between batteries. The simulations were carried out and an in-depth economic analysis conducted to analyze the costs and other financial metrics of the hybrid project. Results proved the advantages of the dual battery with the proposed BMS and fortify that the introduction of time-based tariffs and other incentives will further make investments in VRB highly attractive for renewable applications.