IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v269y2023ics0360544222033928.html
   My bibliography  Save this article

A two-stage energy management for integrated thermal/energy optimization of aircraft airborne system based on Stackelberg game

Author

Listed:
  • Zheng, Fengying
  • Chen, Yuang
  • Zhang, Jingyang
  • Cheng, Fengna
  • Zhang, Jingzhou

Abstract

As a new integrated airborne electromechanical system, APTMS extracts air, shaft power and fuel from aircraft engines which will cause complex effects on fuel consumption and stability margin of aircraft engine. The performance conflict between aircraft engine and APTMS caused by multiple forms of energy cross-linking greatly increases the difficulty of energy management and optimization. Considering the contradictory of the optimization objectives of this coupling model. a two-stage Stackelberg game is proposed to solve the energy optimization. By setting aircraft engine as a leader and APTMS as a follower with the constraints, an energy optimization Stackelberg game is established. The existence of Stackelberg equilibrium is proved by multivariate nonlinear fitting and the value of equilibrium is obtained by dynamic iteration. Additionally, in order to jump out of the local optimal solution, adaptive chaos search particle swarm optimization (ACPSO) is introduced to the solution accuracy. Finally, compared with multi-objective optimizations base on Pareto equilibrium under typical conditions, the advantages of this new method are verified.

Suggested Citation

  • Zheng, Fengying & Chen, Yuang & Zhang, Jingyang & Cheng, Fengna & Zhang, Jingzhou, 2023. "A two-stage energy management for integrated thermal/energy optimization of aircraft airborne system based on Stackelberg game," Energy, Elsevier, vol. 269(C).
    • Handle: RePEc:eee:energy:v:269:y:2023:i:c:s0360544222033928
    DOI: 10.1016/j.energy.2022.126506
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222033928
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.126506?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. Zhang, Jinning & Roumeliotis, Ioannis & Zolotas, Argyrios, 2022. "Model-based fully coupled propulsion-aerodynamics optimization for hybrid electric aircraft energy management strategy," Energy, Elsevier, vol. 245(C).
    2. Hu, Xiaosong & Zou, Yuan & Yang, Yalian, 2016. "Greener plug-in hybrid electric vehicles incorporating renewable energy and rapid system optimization," Energy, Elsevier, vol. 111(C), pages 971-980.
    3. Huang, Yujing & Wang, Yudong & Liu, Nian, 2022. "A two-stage energy management for heat-electricity integrated energy system considering dynamic pricing of Stackelberg game and operation strategy optimization," Energy, Elsevier, vol. 244(PA).
    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. Ming Foong Soong & Rahizar Ramli & Ahmad Saifizul, 2017. "Between simplicity and accuracy: Effect of adding modeling details on quarter vehicle model accuracy," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-23, June.
    2. Zhihan Shi & Weisong Han & Guangming Zhang & Zhiqing Bai & Mingxiang Zhu & Xiaodong Lv, 2022. "Research on Low-Carbon Energy Sharing through the Alliance of Integrated Energy Systems with Multiple Uncertainties," Energies, MDPI, vol. 15(24), pages 1-20, December.
    3. Jing Li & Tong Wu & Tianxin Fan & Yan He & Lingshuai Meng & Zuoyue Han, 2020. "Clamping force control of electro–mechanical brakes based on driver intentions," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-30, September.
    4. Shaobo Xie & Xiaosong Hu & Kun Lang & Shanwei Qi & Tong Liu, 2018. "Powering Mode-Integrated Energy Management Strategy for a Plug-In Hybrid Electric Truck with an Automatic Mechanical Transmission Based on Pontryagin’s Minimum Principle," Sustainability, MDPI, vol. 10(10), pages 1-23, October.
    5. Liu, Hui & Duan, Zhu & Chen, Chao, 2020. "Wind speed big data forecasting using time-variant multi-resolution ensemble model with clustering auto-encoder," Applied Energy, Elsevier, vol. 280(C).
    6. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Zhao, Yunlong & Gao, Chong, 2023. "A stochastic hierarchical optimization and revenue allocation approach for multi-regional integrated energy systems based on cooperative games," Applied Energy, Elsevier, vol. 350(C).
    7. Wang, Mingkai & Xiaoyang, Guotai & He, Ruichen & Zhang, Shuguang & Ma, Jintao, 2023. "Bi-layer sizing and design optimization method of propulsion system for electric vertical takeoff and landing aircraft," Energy, Elsevier, vol. 283(C).
    8. García-Vázquez, Carlos A. & Llorens-Iborra, Francisco & Fernández-Ramírez, Luis M. & Sánchez-Sainz, Higinio & Jurado, Francisco, 2017. "Comparative study of dynamic wireless charging of electric vehicles in motorway, highway and urban stretches," Energy, Elsevier, vol. 137(C), pages 42-57.
    9. Wu, Xiaohua & Hu, Xiaosong & Yin, Xiaofeng & Zhang, Caiping & Qian, Shide, 2017. "Optimal battery sizing of smart home via convex programming," Energy, Elsevier, vol. 140(P1), pages 444-453.
    10. Colmenar-Santos, A. & de Palacio-Rodriguez, Carlos & Rosales-Asensio, Enrique & Borge-Diez, David, 2017. "Estimating the benefits of vehicle-to-home in islands: The case of the Canary Islands," Energy, Elsevier, vol. 134(C), pages 311-322.
    11. Fei Liu & Zhiyuan Zeng & Rong Jiang, 2017. "A video-based real-time adaptive vehicle-counting system for urban roads," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-16, November.
    12. Li-Qiang Jin & Mingze Ling & Weiqiang Yue, 2017. "Tire-road friction estimation and traction control strategy for motorized electric vehicle," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-18, June.
    13. Yang, Chao & Lu, Zhexi & Wang, Weida & Wang, Muyao & Zhao, Jing, 2023. "An efficient intelligent energy management strategy based on deep reinforcement learning for hybrid electric flying car," Energy, Elsevier, vol. 280(C).
    14. Wang, Bin & Wang, Chaohui & Wang, Zhiyu & Ni, Siliang & Yang, Yixin & Tian, Pengyu, 2023. "Adaptive state of energy evaluation for supercapacitor in emergency power system of more-electric aircraft," Energy, Elsevier, vol. 263(PA).
    15. Chattopadhyay, Kabitri & Kies, Alexander & Lorenz, Elke & von Bremen, Lüder & Heinemann, Detlev, 2017. "The impact of different PV module configurations on storage and additional balancing needs for a fully renewable European power system," Renewable Energy, Elsevier, vol. 113(C), pages 176-189.
    16. Xie, Shaobo & Hu, Xiaosong & Qi, Shanwei & Lang, Kun, 2018. "An artificial neural network-enhanced energy management strategy for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 163(C), pages 837-848.
    17. Peng, Fei & Zhao, Yuanzhe & Chen, Ting & Zhang, Xuexia & Chen, Weirong & Zhou, Donghua & Li, Qi, 2018. "Development of robust suboptimal real-time power sharing strategy for modern fuel cell based hybrid tramways considering operational uncertainties and performance degradation," Applied Energy, Elsevier, vol. 226(C), pages 503-521.
    18. Yang, Chao & Li, Liang & You, Sixiong & Yan, Bingjie & Du, Xian, 2017. "Cloud computing-based energy optimization control framework for plug-in hybrid electric bus," Energy, Elsevier, vol. 125(C), pages 11-26.
    19. Noman Khan & Fath U Min Ullah & Ijaz Ul Haq & Samee Ullah Khan & Mi Young Lee & Sung Wook Baik, 2021. "AB-Net: A Novel Deep Learning Assisted Framework for Renewable Energy Generation Forecasting," Mathematics, MDPI, vol. 9(19), pages 1-18, October.
    20. Pirouzi, Sasan & Aghaei, Jamshid & Niknam, Taher & Shafie-khah, Miadreza & Vahidinasab, Vahid & Catalão, João P.S., 2017. "Two alternative robust optimization models for flexible power management of electric vehicles in distribution networks," Energy, Elsevier, vol. 141(C), pages 635-651.

    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:269:y:2023:i:c:s0360544222033928. 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.