A centralized EMPC scheme for PV-powered alkaline electrolyzer
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 c...
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| Vydáno v: | Renewable energy Ročník 229; s. 120688 |
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| Hlavní autoři: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Ltd
01.08.2024
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| ISSN: | 0960-1481, 1879-0682 |
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| 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.
•A CEMPC scheme is developed for a PV-powered alkaline electrolyzer system.•A converter-based mathematical model is constructed for the system.•An efficient algorithm is proposed to solve non-convex CEMPC optimization problem.•The CEMPC is validated by simulations under varying irradiance conditions. |
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| AbstractList | 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. 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. •A CEMPC scheme is developed for a PV-powered alkaline electrolyzer system.•A converter-based mathematical model is constructed for the system.•An efficient algorithm is proposed to solve non-convex CEMPC optimization problem.•The CEMPC is validated by simulations under varying irradiance conditions. |
| ArticleNumber | 120688 |
| Author | Ma, Lele Liu, Xiangjie Lee, Kwang Y. Chen, Sian Kong, Xiaobing Zhu, Zheng |
| Author_xml | – sequence: 1 givenname: Zheng orcidid: 0009-0004-5104-7578 surname: Zhu fullname: Zhu, Zheng organization: The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, 102206, China – sequence: 2 givenname: Sian surname: Chen fullname: Chen, Sian organization: The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, 102206, China – sequence: 3 givenname: Xiaobing surname: Kong fullname: Kong, Xiaobing email: kongxiaobing@ncepu.edu.cn organization: The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, 102206, China – sequence: 4 givenname: Lele surname: Ma fullname: Ma, Lele organization: The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, 102206, China – sequence: 5 givenname: Xiangjie surname: Liu fullname: Liu, Xiangjie organization: The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, 102206, China – sequence: 6 givenname: Kwang Y. surname: Lee fullname: Lee, Kwang Y. organization: Department of Electrical and Computer Engineering, Baylor University, Waco, 76798, TX, USA |
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| Keywords | Model predictive control (MPC) Solar photovoltaic power generation Centralized economic model predictive control (CEMPC) Hydrogen gas generation Alkaline electrolyzer |
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| SubjectTerms | algorithms Alkaline electrolyzer carbon Centralized economic model predictive control (CEMPC) econometric models energy hydrogen Hydrogen gas generation light intensity management systems mathematical models Model predictive control (MPC) solar collectors solar energy Solar photovoltaic power generation system optimization |
| Title | A centralized EMPC scheme for PV-powered alkaline electrolyzer |
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