IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v335y2025ics0360544225037016.html

Research on dynamic economic scheduling of plug in electric vehicles based on improved ant-lion algorithm

Author

Listed:
  • Yang, Wenqiang
  • Dong, Ning
  • Yang, Zhile
  • Nie, Fuquan
  • Li, Kunyan
  • Cai, Jingkao
  • Wang, Yang

Abstract

The dynamic economic dispatch (DED) problem involving plug-in electric vehicles (PEVs) has evolved into a complex constrained optimization challenge characterized by non-smooth, non-linear, and non-convex properties, particularly when considering valve point effects and transmission losses. The integration of grid-connected PEVs through vehicle-to-grid (V2G) technology can effectively mitigate grid fluctuations and facilitate peak shaving and valley filling. This study proposes a model of the dynamic economic dispatch problem that incorporates PEV charging to simulate the effects of day-ahead scheduling and PEV integration in the power system, thereby addressing grid fluctuations and energy consumption. Additionally, an enhanced ant-lion optimization algorithm (EALO) is developed to efficiently solve this model. An elitist transformation mechanism is incorporated to improve the algorithm's random wandering capability, resulting in faster convergence and enhanced global search performance. In addition, a simple and effective treatment of power balance constraints is proposed for infeasible solutions. The EALO's efficacy is evaluated through eight benchmark functions and applied to three different scales of DED scenarios, with comparisons made to existing methods in the literature. The experiment results indicate that the EALO algorithm offers significant advantages in addressing DED challenges.

Suggested Citation

  • Yang, Wenqiang & Dong, Ning & Yang, Zhile & Nie, Fuquan & Li, Kunyan & Cai, Jingkao & Wang, Yang, 2025. "Research on dynamic economic scheduling of plug in electric vehicles based on improved ant-lion algorithm," Energy, Elsevier, vol. 335(C).
  • Handle: RePEc:eee:energy:v:335:y:2025:i:c:s0360544225037016
    DOI: 10.1016/j.energy.2025.138059
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225037016
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2025.138059?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Shen, Xin & Zou, Dexuan & Duan, Na & Zhang, Qiang, 2019. "An efficient fitness-based differential evolution algorithm and a constraint handling technique for dynamic economic emission dispatch," Energy, Elsevier, vol. 186(C).
    2. Wenqiang Yang & Yihang Zhang & Xinxin Zhu & Kunyan Li & Zhile Yang, 2024. "Research on Dynamic Economic Dispatch Optimization Problem Based on Improved Grey Wolf Algorithm," Energies, MDPI, vol. 17(6), pages 1-29, March.
    3. Tang, Xiongmin & Li, Zhengshuo & Xu, Xuancong & Zeng, Zhijun & Jiang, Tianhong & Fang, Wenrui & Meng, Anbo, 2022. "Multi-objective economic emission dispatch based on an extended crisscross search optimization algorithm," Energy, Elsevier, vol. 244(PA).
    4. Qiao, Baihao & Liu, Jing, 2020. "Multi-objective dynamic economic emission dispatch based on electric vehicles and wind power integrated system using differential evolution algorithm," Renewable Energy, Elsevier, vol. 154(C), pages 316-336.
    5. Chen, Xu, 2020. "Novel dual-population adaptive differential evolution algorithm for large-scale multi-fuel economic dispatch with valve-point effects," Energy, Elsevier, vol. 203(C).
    6. Sun, Chuanwang & Xu, Mengjie & Wang, Bo, 2024. "Deep learning: Spatiotemporal impact of digital economy on energy productivity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    7. Zhang, Hong & Irfan, Muhammad & Ai, Fengyi & Al-Aiban, Khalid M. & Abbas, Shujaat, 2024. "Analyzing barriers to the adoption and development of electric vehicles: A roadmap towards sustainable transportation system," Renewable Energy, Elsevier, vol. 233(C).
    8. Sun, Chuanwang & Min, Jialin, 2024. "Dynamic trends and regional differences of economic effects of ultra-high-voltage transmission projects," Energy Economics, Elsevier, vol. 138(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. Yang, Fei & Liu, Kang & Wu, Lei & Ren, Yi & Liang, Tian, 2025. "Urban geometry and energy efficiency: Evidence from 282 cities in China," Energy, Elsevier, vol. 319(C).
    2. Wang, Xiaotong & Wang, Yuezhu & Li, Gujie, 2025. "The impact of FDI on the development of China's low-carbon economy in the context of the “Dual Circulation” policy," Economic Analysis and Policy, Elsevier, vol. 86(C), pages 321-335.
    3. Sheng, Wanxing & Li, Rui & Yan, Tao & Tseng, Ming-Lang & Lou, Jiale & Li, Lingling, 2023. "A hybrid dynamic economics emissions dispatch model: Distributed renewable power systems based on improved COOT optimization algorithm," Renewable Energy, Elsevier, vol. 204(C), pages 493-506.
    4. Liu, Zhi-Feng & Li, Ling-Ling & Liu, Yu-Wei & Liu, Jia-Qi & Li, Heng-Yi & Shen, Qiang, 2021. "Dynamic economic emission dispatch considering renewable energy generation: A novel multi-objective optimization approach," Energy, Elsevier, vol. 235(C).
    5. Feng, Yanchao & Yan, Tong & Zhang, Ci & Zhang, Zhenhua & Pan, Yuxi, 2025. "Assessing the internal nexus of energy transition at the global level: Insights from triple aspects of scale, structure, and efficiency," Energy, Elsevier, vol. 320(C).
    6. Lee, Seoyoung & Kim, Hongbum & Hwang, Junseok, 2025. "Is the transition to electric vehicles a crisis or an opportunity? The South Korean automotive industry experience," Journal of Asian Economics, Elsevier, vol. 98(C).
    7. Xu, Mengmeng & Chen, Can & Zhou, Xiaoshi, 2024. "Enhancing understanding of rebound effect: A novel varying coefficient model for China's industrial sector," Energy, Elsevier, vol. 313(C).
    8. Cui, Huan-yu & Cao, Yue-qun, 2026. "Does the baby that cries get milk? Direct and indirect effects of public participation on environmental governance in China," World Development, Elsevier, vol. 198(C).
    9. Xu, Shengping & Xiong, Guojiang & Mohamed, Ali Wagdy & Bouchekara, Houssem R.E.H., 2022. "Forgetting velocity based improved comprehensive learning particle swarm optimization for non-convex economic dispatch problems with valve-point effects and multi-fuel options," Energy, Elsevier, vol. 256(C).
    10. Shao, Liuguo & Nong, Hao & Zhang, Hua, 2026. "Analysis of homogeneous and heterogeneous response of clean energy metal prices under geopolitical risk shocks," Energy Policy, Elsevier, vol. 208(C).
    11. Yang, Wenqiang & Zhu, Xinxin & Xiao, Qinge & Yang, Zhile, 2023. "Enhanced multi-objective marine predator algorithm for dynamic economic-grid fluctuation dispatch with plug-in electric vehicles," Energy, Elsevier, vol. 282(C).
    12. Ling, Long & Hu, Lu & Li, Shaoqiu & Zhao, Xing & Ye, Xixi, 2025. "How does open public data affect enterprise green transformation?," Socio-Economic Planning Sciences, Elsevier, vol. 102(C).
    13. Luo, Kun & Wang, Xiaolu, 2025. "Green investor entry and corporate green transformation: Evidence from Chinese resource-based industry," Resources Policy, Elsevier, vol. 109(C).
    14. Ye, Ruike & Yang, Xirui & Zhou, Yunheng & Lin, Changfeng & Chen, Yiming & Chen, Jiawei & Bian, Mengying, 2025. "Energy demand security in OPEC+ countries: A revised 4As framework beyond supply security," Energy, Elsevier, vol. 320(C).
    15. Yang, Xiaodong & Hunjra, Ahmed Imran & Alharbi, Samar S. & Zhao, Shikuan, 2025. "Towards more inclusive finance: Exploring the mystery of low carbon green technological innovation," Research in International Business and Finance, Elsevier, vol. 78(C).
    16. Feng, Yanchao & Yan, Tong & Cao, Manqian & Pan, Yuxi, 2025. "Identifying the new momentum from the instrumental substitution of energy industry in China: Empirical evidence from the ultra-high voltage transmission projects," Energy, Elsevier, vol. 320(C).
    17. Zare, Mohsen & Farhang, Saman & Akbari, Mohammad Amin & Azizipanah-Abarghooee, Rasoul & Trojovský, Pavel, 2024. "Optimizing reserve-constrained economic dispatch: Cheetah optimizer with constraint handling method in static/dynamic/single/multi-area systems," Energy, Elsevier, vol. 313(C).
    18. Xu, Bin & Xu, Renjing, 2025. "How can government expenditure effectively achieve energy poverty reduction? A non-linear perspective," Energy, Elsevier, vol. 335(C).
    19. Du, Mengfan & Zhang, Yue-Jun, 2025. "Green digital finance and energy transition: Considering the differentiating role of regional policy uncertainty," Economic Analysis and Policy, Elsevier, vol. 86(C), pages 30-48.
    20. Zhao, Bingyu & Hu, Haiqing, 2025. "Digital economy as a new engine for synergy of multi-pollutant mitigation: Evidence from a new perspective of marginal cost," Energy Policy, Elsevier, vol. 196(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:335:y:2025:i:c:s0360544225037016. 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.