IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i13p7645-d845648.html
   My bibliography  Save this article

An Optimal Dispatching Model for Integrated Energy Microgrid Considering the Reliability Principal–Agent Contract

Author

Listed:
  • Biyun Chen

    (Guangxi Key Laboratory of Power System Optimization and Energy-Saving Technology, School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Yanni Chen

    (Guangxi Key Laboratory of Power System Optimization and Energy-Saving Technology, School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Bin Li

    (Guangxi Key Laboratory of Power System Optimization and Energy-Saving Technology, School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Yun Zhu

    (Guangxi Key Laboratory of Power System Optimization and Energy-Saving Technology, School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Chi Zhang

    (Guangxi Key Laboratory of Power System Optimization and Energy-Saving Technology, School of Electrical Engineering, Guangxi University, Nanning 530004, China)

Abstract

As the increasing penetration of sustainable energy brings risks and opportunities for energy system reliability, at the same time, considering the multi-dimensional differentiation of users’ reliability demands can further explore the potential value of reliability resources in Integrated Energy Microgrid (IEM). To activate the reliability resources in a market-oriented perspective and flexibly optimize the operational reservation in dispatch, an optimal dispatching model in IEM considering reliability principal–agent contracts is proposed. We establish the reliability principal–agent mechanism and propose a cooperative gaming model of Integrated Energy Operator (IEO) and Integrated Energy User (IEU) based on the optimal dispatching model. At the upper level, the economic dispatching model of IEO is established to optimize the operation reservation, and the reliability principal–agent contract from users in the lower level would influence reliability improvement. Each IEU in the lower level maximizes its energy utilization and gives the corresponding reliability principal–agent incentives according to the reliability improvement degree and its actual demand. The bi-level model is solved by the KKT condition and strong duality theorem. A case study verifies the effectiveness of the proposed model in reducing the energy dispatch cost, improving the economic benefits of each participant, realizing the optimal allocation of reliability resources and optimizing the IEM energy structure, and the sensitivity analysis of dispatch cost with the user’s energy-using benefits is discussed.

Suggested Citation

  • Biyun Chen & Yanni Chen & Bin Li & Yun Zhu & Chi Zhang, 2022. "An Optimal Dispatching Model for Integrated Energy Microgrid Considering the Reliability Principal–Agent Contract," Sustainability, MDPI, vol. 14(13), pages 1-16, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:7645-:d:845648
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/13/7645/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/13/7645/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tsai, Chen-Hao & Figueroa-Acevedo, Armando & Boese, Maire & Li, Yifan & Mohan, Nihal & Okullo, James & Heath, Brandon & Bakke, Jordan, 2020. "Challenges of planning for high renewable futures: Experience in the U.S. midcontinent electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    2. Krakowski, Vincent & Assoumou, Edi & Mazauric, Vincent & Maïzi, Nadia, 2016. "Feasible path toward 40–100% renewable energy shares for power supply in France by 2050: A prospective analysis," Applied Energy, Elsevier, vol. 171(C), pages 501-522.
    3. Krakowski, Vincent & Assoumou, Edi & Mazauric, Vincent & Maïzi, Nadia, 2016. "Reprint of Feasible path toward 40–100% renewable energy shares for power supply in France by 2050: A prospective analysis," Applied Energy, Elsevier, vol. 184(C), pages 1529-1550.
    4. Li Yao & Xiuli Wang & Tao Qian & Shixiong Qi & Chengzhi Zhu, 2018. "Robust Day-Ahead Scheduling of Electricity and Natural Gas Systems via a Risk-Averse Adjustable Uncertainty Set Approach," Sustainability, MDPI, vol. 10(11), pages 1-16, October.
    5. Li, Haoran & Zhang, Chenghui & Sun, Bo, 2021. "Optimal design for component capacity of integrated energy system based on the active dispatch mode of multiple energy storages," Energy, Elsevier, vol. 227(C).
    6. Liang Tian & Yunlei Xie & Bo Hu & Xinping Liu & Tuoyu Deng & Huanhuan Luo & Fengqiang Li, 2019. "A Deep Peak Regulation Auxiliary Service Bidding Strategy for CHP Units Based on a Risk-Averse Model and District Heating Network Energy Storage," Energies, MDPI, vol. 12(17), pages 1-27, August.
    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. Xiaoqing Bai & Chun Wei & Peijie Li & Dongliang Xiao, 2023. "Editorial for the Special Issue on Sustainable Power Systems and Optimization," Sustainability, MDPI, vol. 15(6), pages 1-3, March.

    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. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    2. Behrang Shirizadeh, Quentin Perrier, and Philippe Quirion, 2022. "How Sensitive are Optimal Fully Renewable Power Systems to Technology Cost Uncertainty?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    3. Maruf, Md. Nasimul Islam, 2021. "Open model-based analysis of a 100% renewable and sector-coupled energy system–The case of Germany in 2050," Applied Energy, Elsevier, vol. 288(C).
    4. Lenzen, Manfred & McBain, Bonnie & Trainer, Ted & Jütte, Silke & Rey-Lescure, Olivier & Huang, Jing, 2016. "Simulating low-carbon electricity supply for Australia," Applied Energy, Elsevier, vol. 179(C), pages 553-564.
    5. Shirizadeh, Behrang & Quirion, Philippe, 2021. "Low-carbon options for the French power sector: What role for renewables, nuclear energy and carbon capture and storage?," Energy Economics, Elsevier, vol. 95(C).
    6. Fortes, Patrícia & Simoes, Sofia G. & Gouveia, João Pedro & Seixas, Júlia, 2019. "Electricity, the silver bullet for the deep decarbonisation of the energy system? Cost-effectiveness analysis for Portugal," Applied Energy, Elsevier, vol. 237(C), pages 292-303.
    7. Mostafa Rezaei & Ali Mostafaeipour & Mojtaba Qolipour & Hamid-Reza Arabnia, 2018. "Hydrogen production using wind energy from sea water: A case study on Southern and Northern coasts of Iran," Energy & Environment, , vol. 29(3), pages 333-357, May.
    8. Icaza-Alvarez, Daniel & Jurado, Francisco & Tostado-Véliz, Marcos & Arevalo, Paúl, 2022. "Decarbonization of the Galapagos Islands. Proposal to transform the energy system into 100% renewable by 2050," Renewable Energy, Elsevier, vol. 189(C), pages 199-220.
    9. Maïzi, Nadia & Mazauric, Vincent & Assoumou, Edi & Bouckaert, Stéphanie & Krakowski, Vincent & Li, Xiang & Wang, Pengbo, 2018. "Maximizing intermittency in 100% renewable and reliable power systems: A holistic approach applied to Reunion Island in 2030," Applied Energy, Elsevier, vol. 227(C), pages 332-341.
    10. Vaillancourt, Kathleen & Bahn, Olivier & Frenette, Erik & Sigvaldason, Oskar, 2017. "Exploring deep decarbonization pathways to 2050 for Canada using an optimization energy model framework," Applied Energy, Elsevier, vol. 195(C), pages 774-785.
    11. Zimmermann, Florian & Keles, Dogan, 2022. "State or market: Investments in new nuclear power plants in France and their domestic and cross-border effects," Working Paper Series in Production and Energy 64, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    12. Lo Piano, S. & Smith, S.T., 2022. "Energy demand and its temporal flexibility: Approaches, criticalities and ways forward," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    13. Mirjat, Nayyar Hussain & Uqaili, Mohammad Aslam & Harijan, Khanji & Valasai, Gordhan Das & Shaikh, Faheemullah & Waris, M., 2017. "A review of energy and power planning and policies of Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 110-127.
    14. Mauleón, Ignacio, 2019. "Optimizing individual renewable energies roadmaps: Criteria, methods, and end targets," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    15. Thimet, P.J. & Mavromatidis, G., 2022. "Review of model-based electricity system transition scenarios: An analysis for Switzerland, Germany, France, and Italy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    16. Frédéric Babonneau & Javiera Barrera & Javiera Toledo, 2021. "Decarbonizing the Chilean Electric Power System: A Prospective Analysis of Alternative Carbon Emissions Policies," Energies, MDPI, vol. 14(16), pages 1-16, August.
    17. Mertens, Tim & Poncelet, Kris & Duerinck, Jan & Delarue, Erik, 2020. "Representing cross-border trade of electricity in long-term energy-system optimization models with a limited geographical scope," Applied Energy, Elsevier, vol. 261(C).
    18. Shirizadeh, Behrang & Quirion, Philippe, 2022. "Do multi-sector energy system optimization models need hourly temporal resolution? A case study with an investment and dispatch model applied to France," Applied Energy, Elsevier, vol. 305(C).
    19. Zerrahn, Alexander & Schill, Wolf-Peter, 2017. "Long-run power storage requirements for high shares of renewables: review and a new model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1518-1534.
    20. Olumayegun, Olumide & Wang, Meihong & Kelsall, Greg, 2017. "Thermodynamic analysis and preliminary design of closed Brayton cycle using nitrogen as working fluid and coupled to small modular Sodium-cooled fast reactor (SM-SFR)," Applied Energy, Elsevier, vol. 191(C), pages 436-453.

    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:jsusta:v:14:y:2022:i:13:p:7645-:d:845648. 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.