Dynamic Operation and Control of a Multi-Stack Alkaline Water Electrolysis System with Shared Gas Separators and Lye Circulation: A Model-Based Study

TL;DR

This work tackles the dynamic operation of large-scale alkaline water electrolysis by modeling and controlling an N-in-1 system where multiple stacks share a single BoP, including gas separators and lye circulation. A state-space model captures inter-stack coupling through lye flow, heat transfer, and HTO impurity accumulation, and a nonlinear model predictive controller (NMPC) coordinates inter-stack currents, lye flow, and cooling to maximize hydrogen yield while tracking wind-driven power input and limiting temperature rise and impurity buildup. Simulation results for a 4-in-1 system show that, with proper NMPC, inter-stack coordination yields comparable load-tracking, temperature stability, and specific energy consumption to four independent 1-in-1 systems, across different lye-topology configurations and wind scenarios. The findings support the practical viability of N-in-1 designs for wind-to-hydrogen applications, offering cost and land-use advantages without sacrificing operational flexibility, while highlighting areas for future work such as startup/shutdown scheduling and uncertainty-aware control.

Abstract

An emerging approach for large-scale hydrogen production using renewable energy is to integrate multiple alkaline water electrolysis (AWE) stacks into a single balance of plant (BoP) system, sharing components such as gas-lye separation and lye circulation. This configuration, termed the $N$-in-1 AWE system, packs $N$ stacks into a modular system, reducing land requirements, the complexity of plant topology, and overall capital costs. However, the coupling of these stacks through the shared BoP introduces challenges in dynamic operation under varying energy inputs, making their performance unclear compared to traditional 1-in-1 systems. To address this, we develop a state-space model of the $N$-in-1 AWE system, capturing the dynamic behaviors of lye circulation, temperature, and HTO impurity, and their impact on energy conversion efficiency. We then propose a nonlinear model predictive controller (NMPC) to coordinately optimize inter-stack electrolytic current distribution, lye flow, and cooling, enabling the system to dynamically track varying load commands while maximizing efficiency, stabilizing temperature, and limiting HTO impurity accumulation. Simulation studies on a 4,000 Nm$^3$/h-rated 4-in-1 system verify the proposed controller under dynamic operation. Comparison with 4 independent 1-in-1 systems reveals that, with proper control, the $N$-in-1 configuration offers comparable flexibility in accommodating real-world wind power inputs. The average differences in the root-mean-square errors (RMSEs) for load-tracking and stack temperature stabilization, and specific energy consumption are below 0.014 MW, 2.356 K, and 0.003 kWh/Nm$^3$.

Figures (13)

• Figure 1: (a) Photo of 4-in-1 AWE systems in installation. (b) Schematic diagram of a typical 4-in-1 AWE system.
• Figure 2: Topologies for inter-stack lye flow distribution. (a) 4 lye circulation pumps. (b) 2 lye circulation pumps. (c) 1 lye circulation pump.
• Figure 3: Interrelationships between state variables, control, and responses in the $N$-in-1 AWE system with the 1-pump topology in Fig. \ref{['fig:cir']}(c).
• Figure 4: Polyhedral approximation of the production function of a 1,000 Nm$^3$/h-rated stack.
• Figure 5: Open-loop responses of the 4-in-1 AWE system. (a) Electrolytic currents of the stacks. (c) Lye flow rates of the stacks and Cooling water flow rate. (c) Temperature of the stacks and separator; (d) HTO impurity at the gas phase of the separator.

Theorems & Definitions (3)

• Remark 1
• Remark 2
• Remark 3