IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i16p5915-d888714.html
   My bibliography  Save this article

Optimal Operation Strategy of PV-Charging-Hydrogenation Composite Energy Station Considering Demand Response

Author

Listed:
  • Liwen Zhu

    (Hubei Collaborative Innovation Center for High-Efficiency Utilization of Solar Energy, Hubei University of Technology, Wuhan 430068, China)

  • Jun He

    (Hubei Collaborative Innovation Center for High-Efficiency Utilization of Solar Energy, Hubei University of Technology, Wuhan 430068, China)

  • Lixun He

    (Hubei Collaborative Innovation Center for High-Efficiency Utilization of Solar Energy, Hubei University of Technology, Wuhan 430068, China)

  • Wentao Huang

    (Hubei Collaborative Innovation Center for High-Efficiency Utilization of Solar Energy, Hubei University of Technology, Wuhan 430068, China)

  • Yanyang Wang

    (Yichang Power Supply Company, State Grid Hubei Electric Power Co., Ltd., Yichang 443200, China)

  • Zong Liu

    (Hubei Collaborative Innovation Center for High-Efficiency Utilization of Solar Energy, Hubei University of Technology, Wuhan 430068, China)

Abstract

Traditional charging stations have a single function, which usually does not consider the construction of energy storage facilities, and it is difficult to promote the consumption of new energy. With the gradual increase in the number of new energy vehicles (NEVs), to give full play to the complementary advantages of source-load resources and provide safe, efficient, and economical energy supply services, this paper proposes the optimal operation strategy of a PV-charging-hydrogenation composite energy station (CES) that considers demand response (DR). Firstly, the operation mode of the CES is analyzed, and the CES model, including a photovoltaic power generation system, fuel cell, hydrogen production, hydrogen storage, hydrogenation, and charging, is established. The purpose is to provide energy supply services for electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs) at the same time. Secondly, according to the travel law of EVs and HFCVs, the distribution of charging demand and hydrogenation demand at different periods of the day is simulated by the Monte Carlo method. On this basis, the following two demand response models are established: charging load demand response based on the price elasticity matrix and interruptible load demand response based on incentives. Finally, a multi-objective optimal operation model considering DR is proposed to minimize the comprehensive operating cost and load fluctuation of CES, and the maximum–minimum method and analytic hierarchy process (AHP) are used to transform this into a linearly weighted single-objective function, which is solved via an improved moth–flame optimization algorithm (IMFO). Through the simulation examples, operation results in four different scenarios are obtained. Compared with a situation not considering DR, the operation strategy proposed in this paper can reduce the comprehensive operation cost of CES by CNY 1051.5 and reduce the load fluctuation by 17.8%, which verifies the effectiveness of the proposed model. In addition, the impact of solar radiation and energy recharge demand changes on operations was also studied, and the resulting data show that CES operations were more sensitive to energy recharge demand changes.

Suggested Citation

  • Liwen Zhu & Jun He & Lixun He & Wentao Huang & Yanyang Wang & Zong Liu, 2022. "Optimal Operation Strategy of PV-Charging-Hydrogenation Composite Energy Station Considering Demand Response," Energies, MDPI, vol. 15(16), pages 1-23, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:16:p:5915-:d:888714
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/16/5915/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/16/5915/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kroniger, Daniel & Madlener, Reinhard, 2014. "Hydrogen storage for wind parks: A real options evaluation for an optimal investment in more flexibility," Applied Energy, Elsevier, vol. 136(C), pages 931-946.
    2. Li, Lei & Al Chami, Zaher & Manier, Hervé & Manier, Marie-Ange & Xue, Jian, 2021. "Incorporating fuel delivery in network design for hydrogen fueling stations: Formulation and two metaheuristic approaches," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    3. Min Wang & Xiaobin Dong & Youchun Zhai, 2021. "Optimal Configuration of the Integrated Charging Station for PV and Hydrogen Storage," Energies, MDPI, vol. 14(21), pages 1-12, October.
    4. Majed A. Alotaibi & Ali M. Eltamaly, 2021. "A Smart Strategy for Sizing of Hybrid Renewable Energy System to Supply Remote Loads in Saudi Arabia," Energies, MDPI, vol. 14(21), pages 1-24, October.
    5. Chen, Huicui & Pei, Pucheng & Song, Mancun, 2015. "Lifetime prediction and the economic lifetime of Proton Exchange Membrane fuel cells," Applied Energy, Elsevier, vol. 142(C), pages 154-163.
    6. Beccali, M. & Brunone, S. & Finocchiaro, P. & Galletto, J.M., 2013. "Method for size optimisation of large wind–hydrogen systems with high penetration on power grids," Applied Energy, Elsevier, vol. 102(C), pages 534-544.
    7. Hui Hwang Goh & Lian Zong & Dongdong Zhang & Wei Dai & Chee Shen Lim & Tonni Agustiono Kurniawan & Kai Chen Goh, 2022. "Orderly Charging Strategy Based on Optimal Time of Use Price Demand Response of Electric Vehicles in Distribution Network," Energies, MDPI, vol. 15(5), pages 1-25, March.
    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. Zhang, Qian & Qin, Tianxi & Wu, Jiaqi & Hao, Ruiyi & Su, Xin & Li, Chunyan, 2024. "Synergistic operation strategy of electric-hydrogen charging station alliance based on differentiated characteristics," Energy, Elsevier, vol. 304(C).
    2. Arindita Saha & Puja Dash & Naladi Ram Babu & Tirumalasetty Chiranjeevi & Bathina Venkateswararao & Łukasz Knypiński, 2022. "Impact of Spotted Hyena Optimized Cascade Controller in Load Frequency Control of Wave-Solar-Double Compensated Capacitive Energy Storage Based Interconnected Power System," Energies, MDPI, vol. 15(19), pages 1-25, September.
    3. Elias Roumpakias & Tassos Stamatelos, 2023. "Comparative Performance Analysis of a Grid-Connected Photovoltaic Plant in Central Greece after Several Years of Operation Using Neural Networks," Sustainability, MDPI, vol. 15(10), pages 1-26, May.
    4. Aleksandra V. Varganova & Vadim R. Khramshin & Andrey A. Radionov, 2022. "Improving Efficiency of Electric Energy System and Grid Operating Modes: Review of Optimization Techniques," Energies, MDPI, vol. 15(19), pages 1-16, September.

    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. Li, Yingjie & Liu, Fang & Chen, Ke & Liu, Yinghui, 2024. "Technical and economic analysis of a hybrid PV/wind energy system for hydrogen refueling stations," Energy, Elsevier, vol. 303(C).
    2. Nistor, Silviu & Dave, Saraansh & Fan, Zhong & Sooriyabandara, Mahesh, 2016. "Technical and economic analysis of hydrogen refuelling," Applied Energy, Elsevier, vol. 167(C), pages 211-220.
    3. Locatelli, Giorgio & Palerma, Emanuele & Mancini, Mauro, 2015. "Assessing the economics of large Energy Storage Plants with an optimisation methodology," Energy, Elsevier, vol. 83(C), pages 15-28.
    4. Grüger, Fabian & Dylewski, Lucy & Robinius, Martin & Stolten, Detlef, 2018. "Carsharing with fuel cell vehicles: Sizing hydrogen refueling stations based on refueling behavior," Applied Energy, Elsevier, vol. 228(C), pages 1540-1549.
    5. Bhogilla, Satya Sekhar & Ito, Hiroshi & Kato, Atsushi & Nakano, Akihiro, 2016. "Experimental study on a laboratory scale Totalized Hydrogen Energy Utilization System for solar photovoltaic application," Applied Energy, Elsevier, vol. 177(C), pages 309-322.
    6. Li, Tianyu & Liu, Huiying & Wang, Hui & Yao, Yongming, 2020. "Hierarchical predictive control-based economic energy management for fuel cell hybrid construction vehicles," Energy, Elsevier, vol. 198(C).
    7. Work, James & Hauer, Grant & Luckert, M.K. (Marty), 2018. "What ethanol prices would induce growers to switch from agriculture to poplar in Alberta? A multiple options approach," Journal of Forest Economics, Elsevier, vol. 33(C), pages 51-62.
    8. Chi, Lixun & Su, Huai & Zio, Enrico & Zhang, Jinjun & Li, Xueyi & Zhang, Li & Fan, Lin & Zhou, Jing & Bai, Hua, 2020. "Integrated Deterministic and Probabilistic Safety Analysis of Integrated Energy Systems with bi-directional conversion," Energy, Elsevier, vol. 212(C).
    9. Zheng Huang & Laisuo Su & Yunjie Yang & Linsong Gao & Xinyu Liu & Heng Huang & Yubai Li & Yongchen Song, 2023. "Three-Dimensional Simulation on the Effects of Different Parameters and Pt Loading on the Long-Term Performance of Proton Exchange Membrane Fuel Cells," Sustainability, MDPI, vol. 15(4), pages 1-22, February.
    10. Juhui Gim & Minsu Kim & Changsun Ahn, 2022. "Energy Management Control Strategy for Saving Trip Costs of Fuel Cell/Battery Electric Vehicles," Energies, MDPI, vol. 15(6), pages 1-15, March.
    11. Karamanev, Dimitre & Pupkevich, Victor & Penev, Kalin & Glibin, Vassili & Gohil, Jay & Vajihinejad, Vahid, 2017. "Biological conversion of hydrogen to electricity for energy storage," Energy, Elsevier, vol. 129(C), pages 237-245.
    12. Tubagus Aryandi Gunawan & Alessandro Singlitico & Paul Blount & James Burchill & James G. Carton & Rory F. D. Monaghan, 2020. "At What Cost Can Renewable Hydrogen Offset Fossil Fuel Use in Ireland’s Gas Network?," Energies, MDPI, vol. 13(7), pages 1-23, April.
    13. Huang, Ruchen & He, Hongwen & Gao, Miaojue, 2023. "Training-efficient and cost-optimal energy management for fuel cell hybrid electric bus based on a novel distributed deep reinforcement learning framework," Applied Energy, Elsevier, vol. 346(C).
    14. Abadie, Luis Mª & Chamorro, José M., 2023. "Investment in wind-based hydrogen production under economic and physical uncertainties," Applied Energy, Elsevier, vol. 337(C).
    15. Olga Bogdanova & Karīna Viskuba & Laila Zemīte, 2023. "A Review of Barriers and Enables in Demand Response Performance Chain," Energies, MDPI, vol. 16(18), pages 1-33, September.
    16. Sanghyun Yun & Jinwon Yun & Jaeyoung Han, 2023. "Development of a 470-Horsepower Fuel Cell–Battery Hybrid Xcient Dynamic Model Using Simscape TM," Energies, MDPI, vol. 16(24), pages 1-22, December.
    17. Eypasch, Martin & Schimpe, Michael & Kanwar, Aastha & Hartmann, Tobias & Herzog, Simon & Frank, Torsten & Hamacher, Thomas, 2017. "Model-based techno-economic evaluation of an electricity storage system based on Liquid Organic Hydrogen Carriers," Applied Energy, Elsevier, vol. 185(P1), pages 320-330.
    18. Yi Zhang & Qiang Guo & Jie Song, 2023. "Internet-Distributed Hardware-in-the-Loop Simulation Platform for Plug-In Fuel Cell Hybrid Vehicles," Energies, MDPI, vol. 16(18), pages 1-17, September.
    19. Moon, Yongma & Baran, Mesut, 2018. "Economic analysis of a residential PV system from the timing perspective: A real option model," Renewable Energy, Elsevier, vol. 125(C), pages 783-795.
    20. Qi Huang & Aihua Jiang & Yu Zeng & Jianan Xu, 2022. "Community Flexible Load Dispatching Model Based on Herd Mentality," Energies, MDPI, vol. 15(13), pages 1-18, June.

    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:15:y:2022:i:16:p:5915-:d:888714. 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.