Research on MPC-Based Power Allocation Strategy and Dynamic Value Evaluation of Wind–Hydrogen Coupled Systems

With rising renewable energy penetration, wind–hydrogen coupling systems are key to large-scale green hydrogen production and wind power integration. This paper proposes a multi-timescale power allocation measure and evaluation framework that executes scheduling planning, rolling updates and real-time control sequentially. First, an intelligent power allocation strategy based on model predictive control (MPC) and State of Health (SOH) prediction is designed, which pursues short-term operational efficiency while actively avoiding electrolyzer-damaging conditions. Second, a comprehensive evaluation model integrating dynamic hydrogen value and flexibility value is built, overcoming the limitations of traditional fixed-hydrogen-value and single-system-value evaluations to quantify operational strategy viability more accurately. Simulation results show that the proposed strategy boosts the system’s lifecycle Net Present Value (NPV) by ~12.7% versus conventional strategies, verifying the framework’s effectiveness and superiority in improving wind–hydrogen coupling system performance.

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Journal
Processes
Published
2026-03-14
DOI
https://doi.org/10.3390/pr14060924
Primary Topic
Hybrid Renewable Energy Systems
Type
article
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article

Research on MPC-Based Power Allocation Strategy and Dynamic Value Evaluation of Wind–Hydrogen Coupled Systems

Jiyong Li, Chen Ye, Yide Peng, Kaiyue Wang et al.
Processes
Hybrid Renewable Energy Systems
article

Research on MPC-Based Power Allocation Strategy and Dynamic Value Evaluation of Wind–Hydrogen Coupled Systems

Jiyong Li, Chen Ye, Yide Peng, Kaiyue Wang, Zhiliang Cheng, Hao Huang
article en

Abstract

With rising renewable energy penetration, wind–hydrogen coupling systems are key to large-scale green hydrogen production and wind power integration. This paper proposes a multi-timescale power allocation measure and evaluation framework that executes scheduling planning, rolling updates and real-time control sequentially. First, an intelligent power allocation strategy based on model predictive control (MPC) and State of Health (SOH) prediction is designed, which pursues short-term operational efficiency while actively avoiding electrolyzer-damaging conditions. Second, a comprehensive evaluation model integrating dynamic hydrogen value and flexibility value is built, overcoming the limitations of traditional fixed-hydrogen-value and single-system-value evaluations to quantify operational strategy viability more accurately. Simulation results show that the proposed strategy boosts the system’s lifecycle Net Present Value (NPV) by ~12.7% versus conventional strategies, verifying the framework’s effectiveness and superiority in improving wind–hydrogen coupling system performance.

ProcessesVol. 14(6)
Guangxi University (CN)
Affordable and clean energy
Openalex Percentile: Top 23%
Hybrid Renewable Energy Systems
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