Optimization of Electrolyte Rebalancing in Vanadium Redox Flow Batteries

TL;DR

This paper introduces a new algorithm for optimizing electrolyte rebalancing in vanadium redox flow batteries, aiming to extend battery life and maximize profits through energy arbitrage, with proven convexity and an MILP solution approach.

Contribution

It develops a novel MILP-based algorithm for optimal rebalancing scheduling, including a convexity proof and analytical solutions for simplified cases.

Findings

The problem's objective function is convex.

The linearized problem can be solved analytically.

The algorithm improves energy arbitrage profitability.

Abstract

This paper presents a novel algorithm to optimize energy capacity restoration of vanadium redox flow batteries (VRFBs). VRFB technologies can have their lives prolonged through a partially restoration of the lost capacity by electrolyte rebalancing. Our algorithm finds the optimal number and time of these rebalancing services to minimize the service cost, while maximizing the revenues from energy arbitrage. We show that the linearized form of this problem can be analytically solved, and that the objective function is convex. To solve the complete problem, we develop a two-step mixed integer linear programming (MILP) algorithm, which first finds the bounds for optimal number of services and then optimizes the number, and time of the services. We then present a theoretical analysis and optimization results for a case study of energy arbitrage in New York ISO.