05/29/2026
By Danielle Fretwell

The Francis College of Engineering, Department of Mechanical Engineering, invites you to attend a Doctoral Dissertation Proposal defense by Henning Hoene titled: "Integrated Modeling of Large-Scale Energy Storage Systems: Hydrogen Storage and Redox-Mediated Flow Batteries"

Candidate Name: Henning Hoene
Degree: Doctoral
Defense Date: Wednesday, June 10th, 2026
Time: 1-3 p.m.
Location: Perry Hall, Room 415

Committee:
Advisor: Ertan Agar, PhD, Department of Mechanical & Industrial Engineering, University of Massachusetts Lowell

Committee Members
1. Xinfang Jin, PhD, Department of Mechanical Engineering, University of Texas at Dallas
2. Fuqiang Liu, PhD, Department of Mechanical & Industrial Engineering, University of Massachusetts Lowell
3. Juan Pablo Trelles, PhD, Department of Mechanical & Industrial Engineering, University of Massachusetts Lowell

Abstract:
As renewable energy adoption expands in utility-scale power systems, large-scale energy storage is increasingly necessary for grid reliability and energy security. This doctoral research demonstrates the use of systematic modeling tools to develop and optimize grid-scale energy storage technologies. Hydrogen energy storage systems (HESS) are a mature solution for large-scale storage. Task 1 develops a techno-economic systems model for HESS integrated with hybrid power generation. This task investigates the role of storage sizing and resilience for grid-scale applications. The study then shifts focus to redox flow batteries (RFBs), an emerging storage technology limited by low energy density which result in high installation costs. A promising solution is redox-mediated flow batteries (RMFBs) which introduce the use of solid active materials, known as solid boosters, to address the low energy density limitation. Task 2 develops a detailed Multiphysics model for RMFBs by coupling a standard 2D transient RFB model to a 2D transient solid booster stack model. Limited studies exist for characterizing the booster reaction and modeling solid-active material behavior. Expanding the model to a 2D framework enables deeper analysis of the tank reaction and transport behavior. Task 3 applies the model to characterize parameters influencing capacity utilization, tank kinetics, and physical structure. By investigating these fundamental characteristics, the aim is to optimize solid booster reactions and improve overall RMFB performance. This doctoral research aims to advance the understanding and optimization of grid-scale energy storage systems through modeling-driven analysis, while supporting the development of RMFBs as a more cost-effective energy storage technology.