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A centralized EMPC scheme for PV-powered alkaline electrolyzer

Author

Listed:
  • Zhu, Zheng
  • Chen, Sian
  • Kong, Xiaobing
  • Ma, Lele
  • Liu, Xiangjie
  • Lee, Kwang Y.

Abstract

Photovoltaic (PV)-powered alkaline electrolyzer system (PVPAES) is an advanced technique to convert the off-grid and intermittent PV-based solar energy into storable and transportable electrolyzer-based hydrogen energy with zero carbon emissions. However, it is difficult to realize the coordinated control of the off-grid PV module and the alkaline electrolyzer, due to the multiple timescale dynamics. To address this challenge, the PVPAES is decomposed into the slow part and fast part based on the dynamic time scale. Exploiting the decomposed subsystems, the slow one is assumed to be managed well by the auxiliary controller. For the fast one, a centralized economic model predictive control (CEMPC) scheme is constituted. This CEMPC integrates the energy management system and local feedback control into a single optimal control framework. A mathematical model of the PVPAES is established, on the basis of which the CEMPC directly adopts the economic indices as the cost function to realize the flexible power point tracking, power supply-demand balance, and dynamic economic optimization. Moreover, the inherent strong nonlinearity of PVPAES results in the nonconvex mixed-integer nonlinear programming optimization problem in the CEMPC. The exhaustive search algorithm utilizing finite converter switching states is adopted to achieve the global economic optimum. The effectiveness of the proposed CEMPC controller is illustrated through simulations under varying irradiance conditions.

Suggested Citation

  • Zhu, Zheng & Chen, Sian & Kong, Xiaobing & Ma, Lele & Liu, Xiangjie & Lee, Kwang Y., 2024. "A centralized EMPC scheme for PV-powered alkaline electrolyzer," Renewable Energy, Elsevier, vol. 229(C).
  • Handle: RePEc:eee:renene:v:229:y:2024:i:c:s0960148124007560
    DOI: 10.1016/j.renene.2024.120688
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    References listed on IDEAS

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    1. Liu, Xianyang & Zou, Jun & Long, Rui & Liu, Zhichun & Liu, Wei, 2023. "Variable period sequence control strategy for an off-grid photovoltaic-PEM electrolyzer hydrogen generation system," Renewable Energy, Elsevier, vol. 216(C).
    2. Sun, Li & Li, Guanru & Hua, Q.S. & Jin, Yuhui, 2020. "A hybrid paradigm combining model-based and data-driven methods for fuel cell stack cooling control," Renewable Energy, Elsevier, vol. 147(P1), pages 1642-1652.
    3. Zhao, Congyu & Wang, Jianda & Dong, Kangyin & Wang, Kun, 2024. "Is renewable energy technology innovation an excellent strategy for reducing climate risk? The case of China," Renewable Energy, Elsevier, vol. 223(C).
    4. Wu, Long & Yin, Xunyuan & Pan, Lei & Liu, Jinfeng, 2022. "Economic model predictive control of integrated energy systems: A multi-time-scale framework," Applied Energy, Elsevier, vol. 328(C).
    5. Zhu, Zheng & Liu, Xiangjie & Kong, Xiaobing & Ma, Lele & Lee, Kwang Y. & Xu, Yuping, 2024. "PV/Hydrogen DC microgrid control using distributed economic model predictive control," Renewable Energy, Elsevier, vol. 222(C).
    6. Sharadga, Hussein & Hajimirza, Shima & Balog, Robert S., 2020. "Time series forecasting of solar power generation for large-scale photovoltaic plants," Renewable Energy, Elsevier, vol. 150(C), pages 797-807.
    7. Liu, Xiangjie & Zhu, Zheng & Kong, Xiaobing & Ma, Lele & Lee, Kwang Y., 2023. "An economic model predictive control-based flexible power point tracking strategy for photovoltaic power generation," Energy, Elsevier, vol. 283(C).
    8. Hou, Guolian & Ke, Yin & Huang, Congzhi, 2021. "A flexible constant power generation scheme for photovoltaic system by error-based active disturbance rejection control and perturb & observe," Energy, Elsevier, vol. 237(C).
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    Cited by:

    1. Sarkar, Vaskar & Kolakaluri, Vinay Kumar, 2025. "Two-part power referencing for an efficient serially coordinated distributed flexible power point tracking of photovoltaic plants," Renewable Energy, Elsevier, vol. 238(C).
    2. Yu, Xianxian & Tu, Zhengkai & Widyaparaga, Adhika & Darlianto, Deen & Chan, Siew Hwa, 2026. "Optimizing bipolar plate protrusion design for performance enhancement in zero-gap alkaline water electrolysis," Renewable Energy, Elsevier, vol. 256(PD).
    3. Kumar, Maneesh & Singh, Rhythm & Arora, Pratham & Bhosale, Amit, 2025. "An adaptive control strategy for DC–DC buck converter for a small-scale distributed green hydrogen production unit using SPV-battery-based off-grid system," Renewable Energy, Elsevier, vol. 255(C).
    4. Qiu, Ruohan & Wang, Qihao & Tang, Zihan & Wu, Xiao, 2025. "Economic and flexible operation of solvent-based carbon capture system with solvent storage based on absorption-desorption decentralized predictive control," Energy, Elsevier, vol. 336(C).

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