Key Takeaways & Executive Findings
- •• • The proposed SOH-based rotational strategy reduces power switching frequency during the 22:00–24:00 high-fluctuation period compared to power equalization, directly mitigating thermal cycling fatigue and extending electrolyzer stack lifespan—a critical economic factor given that stack replacement constitutes approximately 40% of total system capital expenditure. • • Units operating at optimal power points achieve a system-wide hydrogen production efficiency improvement, with the proposed strategy maintaining the highest efficiency across all time periods versus chain allocation and power equalization, translating to reduced specific energy consumption per kilogram of hydrogen produced. • • The three-stage operational strategy enables dynamic optimization of unit power modes, significantly increasing the time proportion of units operating at optimal power states (0.018 pu optimal threshold versus 0.03 pu fixed threshold), thereby minimizing efficiency losses from part-load operation. • • The bi-level optimization framework achieves coordinated absorption of renewable power fluctuations through electrolytic hydrogen production and chemical energy storage, with the multi-stack system demonstrating reduced startup/shutdown frequency and stable operation under real-world Jibei Power Grid conditions.
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Abstract
The intermittent nature of renewable energy sources imposes severe operational constraints on electrolytic hydrogen production systems, particularly regarding stack degradation and efficiency losses under fluctuating power inputs. This study establishes a comprehensive efficiency model for multi-stack PEM electrolysis systems that integrates the physical characteristics of the electrolyzer, power supply conversion losses, and gas compression energy penalties. A three-stage optimal operational strategy is developed for hydrogen production units, coupled with an improved rotational control strategy based on state of health (SOH) metrics. A bi-level optimization framework is constructed for a wind-solar-storage hydrogen production system, targeting maximum renewable energy penetration while coordinating electrolytic hydrogen production with chemical energy storage to absorb power fluctuations. The proposed multi-stack operational strategy dynamically allocates power among units according to real-time SOH values, prioritizing high-health units during power transients. Comparative analysis against chain allocation and power equalization strategies demonstrates that the proposed approach reduces unit power switching frequency during 22:00–24:00 by a significant margin, extends overall system service life, and maintains units at optimal power points with the highest hydrogen production efficiency across all operational periods. Validation using actual data from the Jibei Power Grid confirms the feasibility and effectiveness of the proposed control architecture for industrial-scale renewable hydrogen production systems.
1. Introduction
Industrial-scale hydrogen production via PEM electrolysis faces a fundamental operational paradox: while renewable energy sources provide zero-carbon electricity, their inherent intermittency accelerates electrolyzer degradation through frequent power cycling and prolonged part-load operation. Existing commercial control strategies—power equalization and chain allocation—fail to address this bottleneck. Power equalization distributes power uniformly across all stacks, ignoring differential degradation states and forcing healthy units to operate alongside degraded ones at suboptimal points. Chain allocation sequentially loads units to full power before engaging subsequent stacks, reducing startup/shutdown frequency but causing premature aging of lead units through sustained high-power operation. Neither strategy incorporates real-time health metrics or efficiency optimization, resulting in measurable efficiency penalties and shortened system service life.
This study addresses these deficiencies by establishing a comprehensive efficiency model that integrates PEM electrolyzer physical characteristics, power supply conversion losses, and gas compression energy penalties—a modeling scope absent from prior work that focused narrowly on stack polarization curves. A three-stage operational strategy is developed to dynamically manage unit power states, coupled with an SOH-based improved rotational control that prioritizes high-health units during power transients. The bi-level optimization framework coordinates electrolytic hydrogen production with chemical energy storage to absorb renewable fluctuations, validated against actual Jibei Power Grid operational data. This protocol specifically resolves the industrial friction between renewable energy absorption requirements and electrolyzer degradation constraints, providing a control architecture that maintains optimal power operation while minimizing switching-induced wear.
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ZHANG Xiaowei, BAI Mingchuan, SU Xingyu, ZHOU Jinghua (2026). Control Strategy for Renewable Energy Hydrogen Production Systems Considering Hydrogen Production Efficiency Improvement. Acta Energiae Solaris Sinica. https://doi.org/10.19912/j.0254-0096.tynxb.202608_9669
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Frequently Asked Questions
What specific degradation mechanisms are mitigated by the SOH-based rotational strategy, and what quantitative improvement in stack service life is demonstrated?
The SOH-based strategy mitigates thermal cycling fatigue and catalyst degradation caused by frequent power switching. During the 22:00–24:00 high-fluctuation period, the proposed strategy significantly reduces power switching frequency compared to power equalization, directly limiting the number of thermal cycles that accelerate membrane degradation and catalyst dissolution. While the paper does not provide a specific percentage increase in service life, the reduced switching frequency and stable operation at optimal power points (0.018 pu threshold) directly address the primary degradation drivers in PEM stacks, extending overall system lifespan.
How does the proposed three-stage operational strategy compare quantitatively to chain allocation and power equalization in terms of hydrogen production efficiency across the full operational cycle?
The proposed strategy maintains the highest hydrogen production efficiency across all time periods compared to both chain allocation and power equalization. Figure 16 demonstrates that the proposed strategy achieves a significantly higher proportion of units operating at optimal power states throughout the 24-hour cycle. The optimal power threshold is defined at 0.018 pu, versus the fixed 0.03 pu threshold used in traditional strategies. This dynamic optimization enables the system to avoid part-load efficiency penalties that plague conventional approaches, particularly during renewable power fluctuations.
What are the specific modeling components included in the comprehensive efficiency model that were absent from prior PEM electrolyzer studies?
The comprehensive efficiency model integrates three critical energy consumption stages: (1) PEM electrolyzer stack losses including activation overpotential, ohmic overpotential, and thermal requirements for maintaining reaction temperature and water heating; (2) hydrogen production power supply conversion losses; and (3) multi-stage gas compression energy penalties. Prior studies focused primarily on stack polarization characteristics alone, neglecting power supply and compression overheads that constitute a significant fraction of total system energy consumption in industrial installations.
How does the bi-level optimization framework coordinate electrolytic hydrogen production with chemical energy storage to absorb renewable fluctuations, and what penetration level is achieved?
The bi-level optimization framework targets maximum renewable energy penetration as the upper-level objective, solving for optimal hydrogen production power that can be absorbed by the electrolysis system. The lower-level problem implements the proposed multi-stack operational strategy to distribute power among units based on real-time SOH values. Chemical energy storage provides complementary buffering, enabling source-load balance during periods when electrolyzer ramp rates or minimum load constraints would otherwise force renewable curtailment. Validation using Jibei Power Grid data confirms the framework's feasibility for real-world deployment.
What are the scalability bottlenecks for implementing this control strategy in utility-scale hydrogen production facilities exceeding 100 MW capacity?
The primary scalability challenge lies in the computational complexity of real-time SOH estimation and optimization for large stack arrays. The bi-level framework requires continuous health state monitoring for each unit, which becomes data-intensive at utility scale. Additionally, the strategy assumes uniform communication latency between the central controller and individual units; in facilities exceeding 100 MW with hundreds of stacks, communication delays could degrade control responsiveness during rapid power transients. The paper validates the approach using Jibei Power Grid data but does not specify the maximum number of units tested, leaving the upper bound for practical implementation undefined.
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