Optimizing AC/DC microgrid scheduling with electro-hydrogen hybrid energy storage for low-carbon buildings
Addressing the urgent need for sustainable energy solutions in the built environment, this paper explores the integration of electro-hydrogen hybrid energy storage within AC/DC microgrids for low-carbon buildings. We construct a system model incorporating photovoltaic generation, diesel generators,...
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| Published in: | International journal of hydrogen energy Vol. 143; pp. 716 - 727 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier Ltd
01.07.2025
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| ISSN: | 0360-3199 |
| Online Access: | Get full text |
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| Abstract | Addressing the urgent need for sustainable energy solutions in the built environment, this paper explores the integration of electro-hydrogen hybrid energy storage within AC/DC microgrids for low-carbon buildings. We construct a system model incorporating photovoltaic generation, diesel generators, battery storage, and a hydrogen subsystem (proton exchange membrane fuel cell and electrolyzer), detailing their operating characteristics based on electrochemical principles. To manage this system efficiently using standard optimization solvers, a two-stage optimal scheduling method is proposed, formulated as Mixed-Integer Linear Programming (MILP) for day-ahead scheduling and Mixed-Integer Quadratic Programming (MIQP) for real-time Model Predictive Control (MPC). Comparative simulations across different scenarios demonstrate that incorporating the electro-hydrogen system significantly reduces total operating costs and pollutant emission costs. Furthermore, the proposed two-stage method yields lower costs than relying solely on day-ahead scheduling. The results affirm the potential of the proposed MILP/MIQP-based approach to enhance the operational economy and environmental performance of microgrids in low-carbon buildings.
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•Models and optimizes AC/DC microgrid with electro-hydrogen hybrid storage.•Two-stage optimal scheduling validated for complex EH-HESS microgrid management.•Integrated EH-HESS & optimized scheduling sharply cut building operating costs. |
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| AbstractList | Addressing the urgent need for sustainable energy solutions in the built environment, this paper explores the integration of electro-hydrogen hybrid energy storage within AC/DC microgrids for low-carbon buildings. We construct a system model incorporating photovoltaic generation, diesel generators, battery storage, and a hydrogen subsystem (proton exchange membrane fuel cell and electrolyzer), detailing their operating characteristics based on electrochemical principles. To manage this system efficiently using standard optimization solvers, a two-stage optimal scheduling method is proposed, formulated as Mixed-Integer Linear Programming (MILP) for day-ahead scheduling and Mixed-Integer Quadratic Programming (MIQP) for real-time Model Predictive Control (MPC). Comparative simulations across different scenarios demonstrate that incorporating the electro-hydrogen system significantly reduces total operating costs and pollutant emission costs. Furthermore, the proposed two-stage method yields lower costs than relying solely on day-ahead scheduling. The results affirm the potential of the proposed MILP/MIQP-based approach to enhance the operational economy and environmental performance of microgrids in low-carbon buildings.
[Display omitted]
•Models and optimizes AC/DC microgrid with electro-hydrogen hybrid storage.•Two-stage optimal scheduling validated for complex EH-HESS microgrid management.•Integrated EH-HESS & optimized scheduling sharply cut building operating costs. |
| Author | Wu, Zaijun Zeng, Fei Quan, Xiangjun Yuan, Xiaodong Miu, Huiyu Xie, Xingfeng |
| Author_xml | – sequence: 1 givenname: Xingfeng orcidid: 0000-0002-2345-9813 surname: Xie fullname: Xie, Xingfeng organization: College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, 730050, China – sequence: 2 givenname: Xiangjun surname: Quan fullname: Quan, Xiangjun email: xquan@seu.edu.cn organization: School of Electrical Engineering, Southeast University, Nanjing, 210000, China – sequence: 3 givenname: Zaijun surname: Wu fullname: Wu, Zaijun organization: School of Electrical Engineering, Southeast University, Nanjing, 210000, China – sequence: 4 givenname: Fei surname: Zeng fullname: Zeng, Fei organization: State Grid Jiangsu Electric Power Co., LTD. Electric power Research Institute, Nanjing, 213000, China – sequence: 5 givenname: Huiyu surname: Miu fullname: Miu, Huiyu organization: State Grid Jiangsu Electric Power Co., LTD. Electric power Research Institute, Nanjing, 213000, China – sequence: 6 givenname: Xiaodong surname: Yuan fullname: Yuan, Xiaodong organization: State Grid Jiangsu Electric Power Co., LTD. Electric power Research Institute, Nanjing, 213000, China |
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| Cites_doi | 10.1016/j.ijhydene.2022.10.204 10.1109/TSTE.2024.3375074 10.35833/MPCE.2023.001027 10.1016/j.ijepes.2019.01.025 10.1109/TIA.2022.3169737 10.3390/app11146242 10.1021/acsomega.2c05319 10.1016/j.jclepro.2022.132933 10.1016/j.ijepes.2022.108341 10.1016/j.energy.2017.10.066 10.1016/j.rser.2024.114720 10.1109/TPWRS.2021.3071867 10.1016/j.ijhydene.2024.07.017 10.1016/j.est.2024.114663 10.1016/j.ijhydene.2022.08.224 10.1109/TIA.2023.3296065 10.3390/en15238851 10.55670/fpll.fuen.3.4.1 10.1063/5.0224725 10.3390/electronics12041062 10.1016/j.energy.2019.02.043 10.1109/TSTE.2015.2405935 10.1080/15435075.2022.2049797 10.1109/ACCESS.2020.3014214 10.1016/j.renene.2024.122047 10.3390/en15186813 10.1016/j.ijhydene.2024.08.023 10.1049/iet-rpg.2019.0544 10.1149/MA2023-02422117mtgabs |
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| Keywords | AC/DC microgrids Model predictive control Mixed-integer linear programming (MILP) Low-carbon buildings Optimal scheduling Electro-hydrogen hybrid energy storage Mixed-integer quadratic programming (MIQP) |
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| SubjectTerms | AC/DC microgrids Electro-hydrogen hybrid energy storage Low-carbon buildings Mixed-integer linear programming (MILP) Mixed-integer quadratic programming (MIQP) Model predictive control Optimal scheduling |
| Title | Optimizing AC/DC microgrid scheduling with electro-hydrogen hybrid energy storage for low-carbon buildings |
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