IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v305y2024ics0360544224019716.html
   My bibliography  Save this article

Enhancing energy efficiency in distributed systems with hybrid energy storage

Author

Listed:
  • Meng, Linghao
  • Li, Mei
  • Yang, Hongzhi

Abstract

This paper presents a pioneering approach to enhance energy efficiency within distributed energy systems by integrating hybrid energy storage. Unlike prior research, our study focuses on synergizing two distinct energy storage systems while concurrently optimizing system configuration and operational strategies to enhance performance and reduce costs. The employed distributed energy system incorporates hybrid energy storage, merging thermal energy storage with power storage technologies such as supercapacitors and lithium batteries. We conduct a comprehensive investigation into the impact of this innovative system on distributed energy systems, employing a dual-objective cooperative optimization method that addresses energy efficiency and economic factors alongside environmental considerations. This approach is applied to an almost zero-energy community, demonstrating its efficacy in improving load profiles and optimizing energy management through demand-side management. Additionally, we incorporate stochastic energy management, renewable energy resource planning, and dynamic storage to account for uncertainties in energy sources and demand, utilizing the Two-Point Estimate Method (2P + E PEM). To address the complexity of the problem, we introduce an advanced multi-objective optimization algorithm, the Horse Herd Optimization Algorithm (HOA), inspired by the movement behavior of horses in a herd. This algorithm exhibits superior performance with various operators including elite selection and crossover. In conclusion, our contributions include the introduction of a distributed energy system with hybrid storage, a dual-objective cooperative optimization method, and the application of advanced algorithms. Our results demonstrate significant reductions, with primary energy consumption decreasing by nearly 54.8 % and equivalent pollutant emissions by 63.6 %, highlighting the significance and effectiveness of our proposed approach.

Suggested Citation

  • Meng, Linghao & Li, Mei & Yang, Hongzhi, 2024. "Enhancing energy efficiency in distributed systems with hybrid energy storage," Energy, Elsevier, vol. 305(C).
    • Handle: RePEc:eee:energy:v:305:y:2024:i:c:s0360544224019716
    DOI: 10.1016/j.energy.2024.132197
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224019716
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2024.132197?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2022. "Modelling and optimal energy management for battery energy storage systems in renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    2. Wang, Jiangjiang & Chen, Yuzhu & Dou, Chao & Gao, Yuefen & Zhao, Zheng, 2018. "Adjustable performance analysis of combined cooling heating and power system integrated with ground source heat pump," Energy, Elsevier, vol. 163(C), pages 475-489.
    3. Gao, Jiajia & Kang, Jing & Zhang, Chong & Gang, Wenjie, 2018. "Energy performance and operation characteristics of distributed energy systems with district cooling systems in subtropical areas under different control strategies," Energy, Elsevier, vol. 153(C), pages 849-860.
    4. Ma, Weiwu & Fang, Song & Liu, Gang, 2017. "Hybrid optimization method and seasonal operation strategy for distributed energy system integrating CCHP, photovoltaic and ground source heat pump," Energy, Elsevier, vol. 141(C), pages 1439-1455.
    5. Liu, Zhijian & Fan, Guangyao & Sun, Dekang & Wu, Di & Guo, Jiacheng & Zhang, Shicong & Yang, Xinyan & Lin, Xianping & Ai, Lei, 2022. "A novel distributed energy system combining hybrid energy storage and a multi-objective optimization method for nearly zero-energy communities and buildings," Energy, Elsevier, vol. 239(PE).
    6. Li, Shuangqi & He, Hongwen & Zhao, Pengfei, 2021. "Energy management for hybrid energy storage system in electric vehicle: A cyber-physical system perspective," Energy, Elsevier, vol. 230(C).
    7. Heendeniya, Charitha Buddhika & Sumper, Andreas & Eicker, Ursula, 2020. "The multi-energy system co-planning of nearly zero-energy districts – Status-quo and future research potential," Applied Energy, Elsevier, vol. 267(C).
    8. Tang, Xiaopeng & Liu, Kailong & Lu, Jingyi & Liu, Boyang & Wang, Xin & Gao, Furong, 2020. "Battery incremental capacity curve extraction by a two-dimensional Luenberger–Gaussian-moving-average filter," Applied Energy, Elsevier, vol. 280(C).
    9. Kandil, Sarah M. & Farag, Hany E.Z. & Shaaban, Mostafa F. & El-Sharafy, M. Zaki, 2018. "A combined resource allocation framework for PEVs charging stations, renewable energy resources and distributed energy storage systems," Energy, Elsevier, vol. 143(C), pages 961-972.
    10. Zhang, Tairan & Sobhani, Behrouz, 2023. "Optimal economic programming of an energy hub in the power system while taking into account the uncertainty of renewable resources, risk-taking and electric vehicles using a developed routing method," Energy, Elsevier, vol. 271(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. Wang, Jiangjiang & Liu, Yi & Ren, Fukang & Lu, Shuaikang, 2020. "Multi-objective optimization and selection of hybrid combined cooling, heating and power systems considering operational flexibility," Energy, Elsevier, vol. 197(C).
    2. Zhang, Yijie & Ma, Tao & Yang, Hongxing, 2022. "Grid-connected photovoltaic battery systems: A comprehensive review and perspectives," Applied Energy, Elsevier, vol. 328(C).
    3. Liu, Zhijian & Li, Ying & Fan, Guangyao & Wu, Di & Guo, Jiacheng & Jin, Guangya & Zhang, Shicong & Yang, Xinyan, 2022. "Co-optimization of a novel distributed energy system integrated with hybrid energy storage in different nearly zero energy community scenarios," Energy, Elsevier, vol. 247(C).
    4. Guo, Jiacheng & Liu, Zhijian & Li, Ying & Wu, Di & Liu, Xuan & Zhang, Shicong & Yang, Xinyan & Ge, Hua & Zhang, Peiwen, 2022. "Thermodynamic performance analyses and optimization design method of a novel distributed energy system coupled with hybrid-energy storage," Renewable Energy, Elsevier, vol. 182(C), pages 1182-1200.
    5. Jie, Pengfei & Li, Zhe & Ren, Yanli & Wei, Fengjun, 2023. "Economy-energy-environment optimization of biomass gasification CCHP system integrated with ground source heat pump," Energy, Elsevier, vol. 277(C).
    6. Zhou, Yuan & Wang, Jiangjiang & Dong, Fuxiang & Qin, Yanbo & Ma, Zherui & Ma, Yanpeng & Li, Jianqiang, 2021. "Novel flexibility evaluation of hybrid combined cooling, heating and power system with an improved operation strategy," Applied Energy, Elsevier, vol. 300(C).
    7. Zhang, Zhonglian & Yang, Xiaohui & Li, Moxuan & Deng, Fuwei & Xiao, Riying & Mei, Linghao & Hu, Zecheng, 2023. "Optimal configuration of improved dynamic carbon neutral energy systems based on hybrid energy storage and market incentives," Energy, Elsevier, vol. 284(C).
    8. Zhang, Yajun & Liu, Yajie & Wang, Jia & Zhang, Tao, 2022. "State-of-health estimation for lithium-ion batteries by combining model-based incremental capacity analysis with support vector regression," Energy, Elsevier, vol. 239(PB).
    9. Luo, Lizi & Wu, Zhi & Gu, Wei & Huang, He & Gao, Song & Han, Jun, 2020. "Coordinated allocation of distributed generation resources and electric vehicle charging stations in distribution systems with vehicle-to-grid interaction," Energy, Elsevier, vol. 192(C).
    10. Dai, Houde & Wang, Jiaxin & Huang, Yiyang & Lai, Yuan & Zhu, Liqi, 2024. "Lightweight state-of-health estimation of lithium-ion batteries based on statistical feature optimization," Renewable Energy, Elsevier, vol. 222(C).
    11. Liu, Hong & Zhao, Yue & Gu, Chenghong & Ge, Shaoyun & Yang, Zan, 2021. "Adjustable capability of the distributed energy system: Definition, framework, and evaluation model," Energy, Elsevier, vol. 222(C).
    12. Li, Yan & Feng, Tian-tian & Liu, Li-li & Zhang, Meng-xi, 2023. "How do the electricity market and carbon market interact and achieve integrated development?--A bibliometric-based review," Energy, Elsevier, vol. 265(C).
    13. Ren, Fukang & Wei, Ziqing & Zhai, Xiaoqiang, 2021. "Multi-objective optimization and evaluation of hybrid CCHP systems for different building types," Energy, Elsevier, vol. 215(PA).
    14. Baohong Jin & Zhichao Liu & Yichuan Liao, 2023. "Exploring the Impact of Regional Integrated Energy Systems Performance by Energy Storage Devices Based on a Bi-Level Dynamic Optimization Model," Energies, MDPI, vol. 16(6), pages 1-21, March.
    15. Lau, Jat-Syu & Jiang, Yihuo & Li, Ziyuan & Qian, Qian, 2023. "Stochastic trading of storage systems in short term electricity markets considering intraday demand response market," Energy, Elsevier, vol. 280(C).
    16. Jin, Baohong, 2023. "Impact of renewable energy penetration in power systems on the optimization and operation of regional distributed energy systems," Energy, Elsevier, vol. 273(C).
    17. Zhang, Tairan & Sobhani, Behrouz, 2023. "Optimal economic programming of an energy hub in the power system while taking into account the uncertainty of renewable resources, risk-taking and electric vehicles using a developed routing method," Energy, Elsevier, vol. 271(C).
    18. Mirzaei, Mohammad Reza & Kasaeian, Alibakhsh & Sadeghi Motlagh, Maryam & Fereidoni, Sahar, 2024. "Thermo-economic analysis of an integrated combined heating, cooling, and power unit with dish collector and organic Rankine cycle," Energy, Elsevier, vol. 296(C).
    19. Yang, Chengying & Wu, Zhixin & Li, Xuetao & Fars, Ashk, 2024. "Risk-constrained stochastic scheduling for energy hub: Integrating renewables, demand response, and electric vehicles," Energy, Elsevier, vol. 288(C).
    20. Lin, Mingqiang & Yan, Chenhao & Wang, Wei & Dong, Guangzhong & Meng, Jinhao & Wu, Ji, 2023. "A data-driven approach for estimating state-of-health of lithium-ion batteries considering internal resistance," Energy, Elsevier, vol. 277(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:eee:energy:v:305:y:2024:i:c:s0360544224019716. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.