IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i9p2120-d1385633.html
   My bibliography  Save this article

Optimization of Frequency Modulation Energy Storage Configuration in Power Grid Based on Equivalent Full Cycle Model

Author

Listed:
  • Wentao Huang

    (College of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430070, China)

  • Qingqing Zheng

    (College of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430070, China)

  • Ying Hu

    (College of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430070, China)

  • Yalan Huang

    (College of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430070, China)

  • Shasha Zhou

    (College of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430070, China)

Abstract

This paper aims to meet the challenges of large-scale access to renewable energy and increasingly complex power grid structure, and deeply discusses the application value of energy storage configuration optimization scheme in power grid frequency modulation. Based on the equivalent full cycle model and a large number of actual operation data, various energy storage technologies are technically analyzed, and the economic and environmental performance of different energy storage configuration schemes are comprehensively evaluated. On this basis, this paper puts forward a set of efficient and economical energy storage configuration optimization strategies to meet the demand of power grid frequency modulation and promote the wide application of energy storage technology. After an in-depth analysis, it is found that the optimized energy storage configuration scheme is excellent in technology, economy, and environmental protection. Specifically, in terms of technical performance, the optimization scheme has significantly improved key indicators such as energy storage efficiency, capacity and power, and response speed, which can better meet the requirements of power grid frequency modulation. Through the verification of actual operation data, it is found that the overall efficiency of the optimized energy storage configuration scheme is above 55%, which is helpful to the stability and efficiency of power grid frequency modulation. In terms of economic performance, although the initial investment cost of the optimization scheme may be high, it is found that it has good economy through the evaluation of long-term operation benefits. Considering that the energy storage system can reduce the operating cost of the power grid, improve the energy utilization rate, and achieve the optimization of cost-effectiveness in the long run, this scheme is economically feasible and attractive. In terms of environmental performance, the optimization scheme effectively reduces the negative impact on the environment by improving energy storage efficiency, reducing emissions, and optimizing resource utilization. This is not only conducive to the sustainable development of the power grid but also in line with the current global trend of promoting green and low-carbon transformation. To sum up, this paper not only provides an efficient and economical energy storage allocation optimization strategy for power grid frequency modulation but also provides a scientific basis for relevant decision-making departments. By promoting the practical application and development of energy storage technology, this paper is helpful to improve the frequency modulation ability of power grid, optimize energy structure, and reduce environmental pollution, and thus achieve the goal of sustainable energy development. The data results and in-depth analysis of this paper provide strong support for the practical application of energy storage configuration optimization scheme and also provide important reference for the further innovation and development of energy storage technology.

Suggested Citation

  • Wentao Huang & Qingqing Zheng & Ying Hu & Yalan Huang & Shasha Zhou, 2024. "Optimization of Frequency Modulation Energy Storage Configuration in Power Grid Based on Equivalent Full Cycle Model," Energies, MDPI, vol. 17(9), pages 1-15, April.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:9:p:2120-:d:1385633
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/9/2120/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/9/2120/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ghaffari, Abolfazl & Askarzadeh, Alireza & Fadaeinedjad, Roohollah, 2022. "Optimal allocation of energy storage systems, wind turbines and photovoltaic systems in distribution network considering flicker mitigation," Applied Energy, Elsevier, vol. 319(C).
    2. Chang, Hsiu-Chuan & Ghaddar, Bissan & Nathwani, Jatin, 2022. "Shared community energy storage allocation and optimization," Applied Energy, Elsevier, vol. 318(C).
    3. Surender Reddy Salkuti, 2023. "Advanced Technologies for Energy Storage and Electric Vehicles," Energies, MDPI, vol. 16(5), pages 1-7, February.
    4. Wang, Sen & Li, Fengting & Zhang, Gaohang & Yin, Chunya, 2023. "Analysis of energy storage demand for peak shaving and frequency regulation of power systems with high penetration of renewable energy," Energy, Elsevier, vol. 267(C).
    5. Tang, Hong & Wang, Shengwei, 2023. "Life-cycle economic analysis of thermal energy storage, new and second-life batteries in buildings for providing multiple flexibility services in electricity markets," Energy, Elsevier, vol. 264(C).
    Full references (including those not matched with items on IDEAS)

    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. Zhang, Chengyu & Ma, Liangdong & Luo, Zhiwen & Han, Xing & Zhao, Tianyi, 2024. "Forecasting building plug load electricity consumption employing occupant-building interaction input features and bidirectional LSTM with improved swarm intelligent algorithms," Energy, Elsevier, vol. 288(C).
    2. Weifeng Xu & Bing Yu & Qing Song & Liguo Weng & Man Luo & Fan Zhang, 2022. "Economic and Low-Carbon-Oriented Distribution Network Planning Considering the Uncertainties of Photovoltaic Generation and Load Demand to Achieve Their Reliability," Energies, MDPI, vol. 15(24), pages 1-15, December.
    3. Lingling Hu & Junming Zhou & Feng Jiang & Guangming Xie & Jie Hu & Qinglie Mo, 2023. "Research on Optimization of Valley-Filling Charging for Vehicle Network System Based on Multi-Objective Optimization," Sustainability, MDPI, vol. 16(1), pages 1-25, December.
    4. Ziqi Liu & Tingting Su & Zhiying Quan & Quanli Wu & Yu Wang, 2023. "Review on the Optimal Configuration of Distributed Energy Storage," Energies, MDPI, vol. 16(14), pages 1-17, July.
    5. Ma, Tingshan & Li, Zhengkuan & Lv, Kai & Chang, Dongfeng & Hu, Wenshuai & Zou, Ying, 2024. "Design and performance analysis of deep peak shaving scheme for thermal power units based on high-temperature molten salt heat storage system," Energy, Elsevier, vol. 288(C).
    6. Zhao, Bingxu & Duan, Pengfei & Fen, Mengdan & Xue, Qingwen & Hua, Jing & Yang, Zhuoqiang, 2023. "Optimal operation of distribution networks and multiple community energy prosumers based on mixed game theory," Energy, Elsevier, vol. 278(PB).
    7. Cui, Shiting & Wu, Jun & Gao, Yao & Zhu, Ruijin, 2023. "A high altitude prosumer energy cooperation framework considering composite energy storage sharing and electric‑oxygen‑hydrogen flexible supply," Applied Energy, Elsevier, vol. 349(C).
    8. Peipei You & Sitao Li & Chengren Li & Chao Zhang & Hailang Zhou & Huicai Wang & Huiru Zhao & Yihang Zhao, 2023. "Price-Based Demand Response: A Three-Stage Monthly Time-of-Use Tariff Optimization Model," Energies, MDPI, vol. 16(23), pages 1-20, November.
    9. Jing Yu & Jicheng Liu & Yajing Wen & Xue Yu, 2023. "Economic Optimal Coordinated Dispatch of Power for Community Users Considering Shared Energy Storage and Demand Response under Blockchain," Sustainability, MDPI, vol. 15(8), pages 1-26, April.
    10. Xiong, Yongkang & Zeng, Zhenfeng & Xin, Jianbo & Song, Guanhong & Xia, Yonghong & Xu, Zaide, 2023. "Renewable energy time series regulation strategy considering grid flexible load and N-1 faults," Energy, Elsevier, vol. 284(C).
    11. Ahmed T. Hachemi & Fares Sadaoui & Abdelhakim Saim & Mohamed Ebeed & Hossam E. A. Abbou & Salem Arif, 2023. "Optimal Operation of Distribution Networks Considering Renewable Energy Sources Integration and Demand Side Response," Sustainability, MDPI, vol. 15(24), pages 1-34, December.
    12. Luo, Tengqi & Xuan, Ang & Wang, Yafei & Li, Guanglei & Fang, Juan & Liu, Zhengguang, 2023. "Energy efficiency evaluation and optimization of active distribution networks with building integrated photovoltaic systems," Renewable Energy, Elsevier, vol. 219(P1).
    13. Jiahao Chen & Bing Sun & Yuan Zeng & Ruipeng Jing & Shimeng Dong & Jingran Wang, 2023. "An Optimal Scheduling Method of Shared Energy Storage System Considering Distribution Network Operation Risk," Energies, MDPI, vol. 16(5), pages 1-24, March.
    14. Le, Son Tay & Nguyen, Tuan Ngoc & Bui, Dac-Khuong & Teodosio, Birch & Ngo, Tuan Duc, 2024. "Comparative life cycle assessment of renewable energy storage systems for net-zero buildings with varying self-sufficient ratios," Energy, Elsevier, vol. 290(C).
    15. Chen, Xinjiang & Yang, Yu & Wang, Jianxiao & Song, Jie & He, Guannan, 2023. "Battery valuation and management for battery swapping station," Energy, Elsevier, vol. 279(C).
    16. Barone, G. & Buonomano, A. & Forzano, C. & Palombo, A. & Russo, G., 2023. "The role of energy communities in electricity grid balancing: A flexible tool for smart grid power distribution optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    17. Zhang, Liugan & Ye, Kai & Wang, Yongzhen & Han, Wei & Xie, Meina & Chen, Longxiang, 2024. "Performance analysis of a hybrid system combining cryogenic separation carbon capture and liquid air energy storage (CS-LAES)," Energy, Elsevier, vol. 290(C).
    18. Terkes, Musa & Arikan, Oktay & Gokalp, Erdin, 2024. "The effect of electric vehicle charging demand variability on optimal hybrid power systems with second-life lithium-ion or fresh Na–S batteries considering power quality," Energy, Elsevier, vol. 288(C).
    19. Ahmed Amin & Mohamed Ebeed & Loai Nasrat & Mokhtar Aly & Emad M. Ahmed & Emad A. Mohamed & Hammad H. Alnuman & Amal M. Abd El Hamed, 2022. "Techno-Economic Evaluation of Optimal Integration of PV Based DG with DSTATCOM Functionality with Solar Irradiance and Loading Variations," Mathematics, MDPI, vol. 10(14), pages 1-16, July.
    20. Zhang, Mingze & Li, Weidong & Yu, Samson Shenglong & Wen, Kerui & Muyeen, S.M., 2023. "Day-ahead optimization dispatch strategy for large-scale battery energy storage considering multiple regulation and prediction failures," Energy, Elsevier, vol. 270(C).

    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:17:y:2024:i:9:p:2120-:d:1385633. 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.