IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i15p5593-d1201957.html
   My bibliography  Save this article

Coordinated Dispatch Optimization between the Main Grid and Virtual Power Plants Based on Multi-Parametric Quadratic Programming

Author

Listed:
  • Guixing Yang

    (Xinjiang University, Urumchi 830000, China)

  • Mingze Xu

    (The Chinese University of Hong Kong-Shenzhen, Shenzhen 518000, China)

  • Weiqing Wang

    (Xinjiang University, Urumchi 830000, China)

  • Shunbo Lei

    (The Chinese University of Hong Kong-Shenzhen, Shenzhen 518000, China)

Abstract

Virtual power plants (VPPs) are a critical technology for distribution systems that can integrate various renewable energy resourcescontrollable loads and energy storage systems into one specific power plant through a distributed energy management system. This paper proposes a coordinated dispatch optimization model between the main grid and VPPs aiming to minimize both the power generation cost and total system active loss. When the time of the equivalent dispatching model is not divisible due to the existence of a time coupling constraint inside the VPPs, this model can obtain the global optimal solution through iteration between the main grid and the VPPs. By employing multi-parametric quadratic programming to obtain accurate critical domains and optimal cost functions, the convergence speed and stability are significantly improved. Additionally, a reactive power and voltage optimization technique leveraging the generalized Benders decomposition is presented for the coordination of the main grid and the VPPs. Moreover, the impact of distributed energy resource (DER) clusters on the main grid was studied, from which we proved that the proposed approach can expeditiously abate energy production expenditure and system active dissipation whilst enhancing the system equilibrium.

Suggested Citation

  • Guixing Yang & Mingze Xu & Weiqing Wang & Shunbo Lei, 2023. "Coordinated Dispatch Optimization between the Main Grid and Virtual Power Plants Based on Multi-Parametric Quadratic Programming," Energies, MDPI, vol. 16(15), pages 1-15, July.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:15:p:5593-:d:1201957
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/15/5593/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/15/5593/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alanne, Kari & Saari, Arto, 2006. "Distributed energy generation and sustainable development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(6), pages 539-558, December.
    2. Wang, Qi & Zhang, Chunyu & Ding, Yi & Xydis, George & Wang, Jianhui & Østergaard, Jacob, 2015. "Review of real-time electricity markets for integrating Distributed Energy Resources and Demand Response," Applied Energy, Elsevier, vol. 138(C), pages 695-706.
    3. Akorede, Mudathir Funsho & Hizam, Hashim & Pouresmaeil, Edris, 2010. "Distributed energy resources and benefits to the environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(2), pages 724-734, February.
    4. Spiller, Elisheba & Esparza, Ricardo & Mohlin, Kristina & Tapia-Ahumada, Karen & Ünel, Burçin, 2023. "The role of electricity tariff design in distributed energy resource deployment," Energy Economics, Elsevier, vol. 120(C).
    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. Wei Dai & Yang Gao & Hui Hwang Goh & Jiangyi Jian & Zhihong Zeng & Yuelin Liu, 2024. "A Non-Iterative Coordinated Scheduling Method for a AC-DC Hybrid Distribution Network Based on a Projection of the Feasible Region of Tie Line Transmission Power," Energies, MDPI, vol. 17(6), pages 1-20, 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. Moroni, Stefano & Antoniucci, Valentina & Bisello, Adriano, 2016. "Energy sprawl, land taking and distributed generation: towards a multi-layered density," Energy Policy, Elsevier, vol. 98(C), pages 266-273.
    2. Adil, Ali M. & Ko, Yekang, 2016. "Socio-technical evolution of Decentralized Energy Systems: A critical review and implications for urban planning and policy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1025-1037.
    3. Tan, Wen-Shan & Hassan, Mohammad Yusri & Majid, Md Shah & Abdul Rahman, Hasimah, 2013. "Optimal distributed renewable generation planning: A review of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 626-645.
    4. Botelho, D.F. & de Oliveira, L.W. & Dias, B.H. & Soares, T.A. & Moraes, C.A., 2022. "Prosumer integration into the Brazilian energy sector: An overview of innovative business models and regulatory challenges," Energy Policy, Elsevier, vol. 161(C).
    5. Hernandez, J.A. & Velasco, D. & Trujillo, C.L., 2011. "Analysis of the effect of the implementation of photovoltaic systems like option of distributed generation in Colombia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(5), pages 2290-2298, June.
    6. Zhang, Chong & Xue, Xue & Du, Qianzhou & Luo, Yimo & Gang, Wenjie, 2019. "Study on the performance of distributed energy systems based on historical loads considering parameter uncertainties for decision making," Energy, Elsevier, vol. 176(C), pages 778-791.
    7. 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.
    8. Oliva H., Sebastian, 2017. "Residential energy efficiency and distributed generation - Natural partners or competition?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 932-940.
    9. Francesco Pasimeni, 2017. "Adoption and Diffusion of Micro-Grids in Italy. An Analysis of Regional Factors Using Agent-Based Modelling," SPRU Working Paper Series 2017-09, SPRU - Science Policy Research Unit, University of Sussex Business School.
    10. Mallikarjun, Sreekanth & Lewis, Herbert F., 2014. "Energy technology allocation for distributed energy resources: A strategic technology-policy framework," Energy, Elsevier, vol. 72(C), pages 783-799.
    11. Yifang Tang & Zhiqiang Liu & Lan Li, 2019. "Performance Comparison of a Distributed Energy System under Different Control Strategies with a Conventional Energy System," Energies, MDPI, vol. 12(24), pages 1-17, December.
    12. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Design of distributed energy systems under uncertainty: A two-stage stochastic programming approach," Applied Energy, Elsevier, vol. 222(C), pages 932-950.
    13. Yanine, Franco F. & Sauma, Enzo E., 2013. "Review of grid-tie micro-generation systems without energy storage: Towards a new approach to sustainable hybrid energy systems linked to energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 60-95.
    14. Ante, L. & Steinmetz, F. & Fiedler, I., 2021. "Blockchain and energy: A bibliometric analysis and review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    15. Mandelli, Stefano & Barbieri, Jacopo & Mereu, Riccardo & Colombo, Emanuela, 2016. "Off-grid systems for rural electrification in developing countries: Definitions, classification and a comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1621-1646.
    16. Ilaria Delponte & Corrado Schenone, 2020. "RES Implementation in Urban Areas: An Updated Overview," Sustainability, MDPI, vol. 12(1), pages 1-14, January.
    17. Mehleri, E.D. & Sarimveis, H. & Markatos, N.C. & Papageorgiou, L.G., 2013. "Optimal design and operation of distributed energy systems: Application to Greek residential sector," Renewable Energy, Elsevier, vol. 51(C), pages 331-342.
    18. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Uncertainty and global sensitivity analysis for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 214(C), pages 219-238.
    19. Wolsink, Maarten, 2020. "Distributed energy systems as common goods: Socio-political acceptance of renewables in intelligent microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    20. Yi, Ji Hyun & Ko, Woong & Park, Jong-Keun & Park, Hyeongon, 2018. "Impact of carbon emission constraint on design of small scale multi-energy system," Energy, Elsevier, vol. 161(C), pages 792-808.

    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:16:y:2023:i:15:p:5593-:d:1201957. 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.