Physics-informed design of PV coupled alkaline water electrolysis with battery energy storage under fluctuating power through dynamic modeling
Year: 2026
Type: article
Abstract: Expanding renewable energy is essential for sustainability, but fluctuating power sources pose significant challenges to the stability of green hydrogen systems. Although PV coupled water electrolyzer systems are often designed using conventional techno-economic metrics, such approaches neglect dynamic electrochemical and thermal responses under variable power operation. This study develops a physics-based dynamic model for a PV coupled alkaline water electrolysis and battery system. The model resolves coupled dynamics across the stack and the balance of plant. Twelve scenarios are proposed to examine the impact of physically informed considerations on system design. Each scenario is evaluated using three decision-making methods, comparing a conventional indicator set with an augmented set that includes physically informed indicators. The conventional indicators include LCOH, curtailment, and battery state of charge variation, while the physically informed indicators include cell voltage variation, rapid O 2 in H 2 rise duration, and system efficiency. The results show that the Const 695 kW scenario held rank 3 in all three methods under the conventional indicator set but fell below rank 10 when the physically informed indicators were included, revealing safety risks that conventional indicators failed to capture. In contrast, the Ramp 695 kW scenario ranked first across all evaluation cases, confirming that a large AWE with a small battery operated to follow the PV output is robust under both economic and safety perspectives. These findings demonstrate that physics-based dynamic modeling is essential for identifying hidden safety vulnerabilities and enabling more informed design decisions under fluctuating renewable power.
Source: Energy
Institutions: Seoul National University, University of California, Irvine
Language: English
Subfield: Energy Engineering and Power Technology
Field: Energy
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,260
Award: G3804641546
OpenAlex ID: W7219008044
