IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i17p6132-d1223166.html
   My bibliography  Save this article

Operation Optimization of Wind/Battery Storage/Alkaline Electrolyzer System Considering Dynamic Hydrogen Production Efficiency

Author

Listed:
  • Meng Niu

    (National Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, China)

  • Xiangjun Li

    (National Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, China)

  • Chen Sun

    (National Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, China)

  • Xiaoqing Xiu

    (National Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, China)

  • Yue Wang

    (National Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, China)

  • Mingyue Hu

    (National Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, China)

  • Haitao Dong

    (National Key Laboratory of Renewable Energy Grid-Integration, China Electric Power Research Institute, Beijing 100192, China)

Abstract

Hydrogen energy is regarded as a key path to combat climate change and promote sustainable economic and social development. The fluctuation of renewable energy leads to frequent start/stop cycles in hydrogen electrolysis equipment. However, electrochemical energy storage, with its fast response characteristics, helps regulate the power of hydrogen electrolysis, enabling smooth operation. In this study, a multi-objective constrained operation optimization model for a wind/battery storage/alkaline electrolyzer system is constructed. Both profit maximization and power abandonment rate minimization are considered. In addition, some constraints, such as minimum start/stop times, upper and lower power limits, and input fluctuation limits, are also taken into account. Then, the non-dominated sorting genetic algorithm II (NSGA-II) algorithm and the entropy method are used to optimize the operation strategy of the hybrid energy system by considering dynamic hydrogen production efficiency, and through optimization to obtain the best hydrogen production power of the system under the two objectives. The change in dynamic hydrogen production efficiency is mainly related to the change in electrolyzer power, and the system can be better adjusted according to the actual supply of renewable energy to avoid the waste of renewable energy. Our results show that the distribution of Pareto solutions is uniform, which indicates the suitability of the NSGA-II algorithm. In addition, the optimal solution indicates that the battery storage and alkaline electrolyzer can complement each other in operation and achieve the absorption of wind power. The dynamic hydrogen production efficiency can make the electrolyzer operate more efficiently, which paves the way for system optimization. A sensitivity analysis reveals that the profit is sensitive to the price of hydrogen energy.

Suggested Citation

  • Meng Niu & Xiangjun Li & Chen Sun & Xiaoqing Xiu & Yue Wang & Mingyue Hu & Haitao Dong, 2023. "Operation Optimization of Wind/Battery Storage/Alkaline Electrolyzer System Considering Dynamic Hydrogen Production Efficiency," Energies, MDPI, vol. 16(17), pages 1-20, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6132-:d:1223166
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/17/6132/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/17/6132/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xi Yang & Chris P. Nielsen & Shaojie Song & Michael B. McElroy, 2022. "Breaking the hard-to-abate bottleneck in China’s path to carbon neutrality with clean hydrogen," Nature Energy, Nature, vol. 7(10), pages 955-965, October.
    2. Wadim Strielkowski & Lubomír Civín & Elena Tarkhanova & Manuela Tvaronavičienė & Yelena Petrenko, 2021. "Renewable Energy in the Sustainable Development of Electrical Power Sector: A Review," Energies, MDPI, vol. 14(24), pages 1-24, December.
    3. Comodi, Gabriele & Bartolini, Andrea & Carducci, Francesco & Nagaranjan, Balamurugan & Romagnoli, Alessandro, 2019. "Achieving low carbon local energy communities in hot climates by exploiting networks synergies in multi energy systems," Applied Energy, Elsevier, vol. 256(C).
    4. Li, Miao & Mu, Hailin & Li, Nan & Ma, Baoyu, 2016. "Optimal design and operation strategy for integrated evaluation of CCHP (combined cooling heating and power) system," Energy, Elsevier, vol. 99(C), pages 202-220.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Di Lu & Yonggang Peng & Jing Sun, 2024. "Dual-Stage Optimization Scheduling Model for a Grid-Connected Renewable Energy System with Hybrid Energy Storage," Energies, MDPI, vol. 17(3), pages 1-19, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xinxin Liu & Nan Li & Feng Liu & Hailin Mu & Longxi Li & Xiaoyu Liu, 2021. "Optimal Design on Fossil-to-Renewable Energy Transition of Regional Integrated Energy Systems under CO 2 Emission Abatement Control: A Case Study in Dalian, China," Energies, MDPI, vol. 14(10), pages 1-25, May.
    2. Lan, Yuncheng & Lu, Junhui & Wang, Suilin, 2023. "Study of the geometry and structure of a thermoelectric leg with variable material properties and side heat dissipation based on thermodynamic, economic, and environmental analysis," Energy, Elsevier, vol. 282(C).
    3. Wang, Lixiao & Jing, Z.X. & Zheng, J.H. & Wu, Q.H. & Wei, Feng, 2018. "Decentralized optimization of coordinated electrical and thermal generations in hierarchical integrated energy systems considering competitive individuals," Energy, Elsevier, vol. 158(C), pages 607-622.
    4. Li, Ruonan & Mahalec, Vladimir, 2022. "Integrated design and operation of energy systems for residential buildings, commercial buildings, and light industries," Applied Energy, Elsevier, vol. 305(C).
    5. Nazar, Mehrdad Setayesh & Jafarpour, Pourya & Shafie-khah, Miadreza & Catalão, João P.S., 2024. "Optimal planning of self-healing multi-carriers energy systems considering integration of smart buildings and parking lots energy resources," Energy, Elsevier, vol. 286(C).
    6. Afzali, Sayyed Faridoddin & Mahalec, Vladimir, 2017. "Optimal design, operation and analytical criteria for determining optimal operating modes of a CCHP with fired HRSG, boiler, electric chiller and absorption chiller," Energy, Elsevier, vol. 139(C), pages 1052-1065.
    7. Fouladvand, Javanshir & Aranguren Rojas, Maria & Hoppe, Thomas & Ghorbani, Amineh, 2022. "Simulating thermal energy community formation: Institutional enablers outplaying technological choice," Applied Energy, Elsevier, vol. 306(PA).
    8. Li, Nan & Zhao, Xunwen & Shi, Xunpeng & Pei, Zhenwei & Mu, Hailin & Taghizadeh-Hesary, Farhad, 2021. "Integrated energy systems with CCHP and hydrogen supply: A new outlet for curtailed wind power," Applied Energy, Elsevier, vol. 303(C).
    9. Li, Yanbin & Zhang, Feng & Li, Yun & Wang, Yuwei, 2021. "An improved two-stage robust optimization model for CCHP-P2G microgrid system considering multi-energy operation under wind power outputs uncertainties," Energy, Elsevier, vol. 223(C).
    10. Guozheng Li & Rui Wang & Tao Zhang & Mengjun Ming, 2018. "Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g," Energies, MDPI, vol. 11(4), pages 1-26, March.
    11. Zheng, Xuyue & Wu, Guoce & Qiu, Yuwei & Zhan, Xiangyan & Shah, Nilay & Li, Ning & Zhao, Yingru, 2018. "A MINLP multi-objective optimization model for operational planning of a case study CCHP system in urban China," Applied Energy, Elsevier, vol. 210(C), pages 1126-1140.
    12. Urbano, Eva M. & Martinez-Viol, Victor & Kampouropoulos, Konstantinos & Romeral, Luis, 2021. "Energy equipment sizing and operation optimisation for prosumer industrial SMEs – A lifetime approach," Applied Energy, Elsevier, vol. 299(C).
    13. Gordon, Joel A. & Balta-Ozkan, Nazmiye & Nabavi, Seyed Ali, 2023. "Price promises, trust deficits and energy justice: Public perceptions of hydrogen homes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    14. Gheorghe Dumitrașcu & Michel Feidt & Ştefan Grigorean, 2021. "Finite Physical Dimensions Thermodynamics Analysis and Design of Closed Irreversible Cycles," Energies, MDPI, vol. 14(12), pages 1-19, June.
    15. Junchao Cheng & Yongyi Huang & Hongjing He & Abdul Matin Ibrahimi & Tomonobu Senjyu, 2023. "Optimal Operation of CCHP System Combined Electric Vehicles Considering Seasons," Energies, MDPI, vol. 16(10), pages 1-21, May.
    16. Natei Ermias Benti & Mesfin Diro Chaka & Addisu Gezahegn Semie, 2023. "Forecasting Renewable Energy Generation with Machine Learning and Deep Learning: Current Advances and Future Prospects," Sustainability, MDPI, vol. 15(9), pages 1-33, April.
    17. Li, C.Y. & Deethayat, T. & Wu, J.Y. & Kiatsiriroat, T. & Wang, R.Z., 2018. "Simulation and evaluation of a biomass gasification-based combined cooling, heating, and power system integrated with an organic Rankine cycle," Energy, Elsevier, vol. 158(C), pages 238-255.
    18. Zhang, Ying & Deng, Shuai & Ni, Jiaxin & Zhao, Li & Yang, Xingyang & Li, Minxia, 2017. "A literature research on feasible application of mixed working fluid in flexible distributed energy system," Energy, Elsevier, vol. 137(C), pages 377-390.
    19. Im, Yong-Hoon & Liu, Jie, 2018. "Feasibility study on the low temperature district heating and cooling system with bi-lateral heat trades model," Energy, Elsevier, vol. 153(C), pages 988-999.
    20. Yuandong Yan & Ruyi Wang & Qian Zheng & Jiaying Zhong & Weichang Hao & Shicheng Yan & Zhigang Zou, 2023. "Nonredox trivalent nickel catalyzing nucleophilic electrooxidation of organics," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6132-:d:1223166. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.