Dynamic Modeling and Control of Multi-Stack Alkaline Water Electrolysis Systems with Shared Gas Separators and Lye Circulation: An Experiment-Based Study

TL;DR

This study models and controls a multi-stack alkaline water electrolysis system sharing components, demonstrating through experiments that it performs comparably to multiple independent systems with reduced cost and complexity.

Contribution

It develops an experimental-validated state-space model and nonlinear model predictive controller for multi-stack AWE systems, enabling effective load tracking and operational stability.

Findings

Multi-stack AWE system achieves similar performance to multiple 1-in-1 systems.

Load-tracking error, temperature, and energy consumption differences are minimal.

Experimental validation confirms the model's accuracy and control effectiveness.

Abstract

An emerging approach for large-scale renewable hydrogen production is integrating multiple alkaline water electrolysis (AWE) stacks into one balance-of-plant (BoP) system, sharing gas-lye separation and lye circulation components. While this configuration, termed $N$-in-1, reduces cost and complexity, its dynamic performance under fluctuating power remains unclear compared with conventional 1-in-1 systems. This paper develops a state-space model of the multi-stack AWE system, capturing lye circulation, temperature, and hydrogen-to-oxygen (HTO) dynamics, calibrated via experiments on a 4,000 Nm$^3$/h-rated 4-in-1 system. A nonlinear model predictive controller (NMPC) is then designed to coordinate inter-stack current distribution, lye flow, and cooling for load tracking and operational stability. Simulations on the experimental-validated model show that a $4$-in-1 system can achieve very similar performance compared to four parallel 1-in-1 systems. Differences in load-tracking error, temperature stabilization, and specific energy consumption remain below 0.015 MW, 0.346 K, and 0.001 kWh/Nm$^3$ under wind power supply.