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Dynamic Boundary Dissemination to Virtual Power Plants for Congestion and Voltage Management in Power Distribution Networks

Author

Listed:
  • Khalil Gholami

    (Renewable Energy and Electric Vehicle (REEV) Lab, School of Engineering, Deakin University, Geelong, VIC 3216, Australia)

  • Mohammad Taufiqul Arif

    (Renewable Energy and Electric Vehicle (REEV) Lab, School of Engineering, Deakin University, Geelong, VIC 3216, Australia)

  • Md Enamul Haque

    (Renewable Energy and Electric Vehicle (REEV) Lab, School of Engineering, Deakin University, Geelong, VIC 3216, Australia)

Abstract

Virtual power plants (VPPs) are optimized to maximize profits by efficiently scheduling their resources. However, dynamic power trading over existing distribution networks can lead to voltage disturbances and branch congestion, posing risks to network security. Moreover, distribution network service providers (DNSPs) face the added challenge of managing VPP operations while complying with privacy preservation. To address these challenges, this paper proposes a decentralized co-optimization technique for integrating VPPs into distribution networks. The approach enables DNSPs to define dynamic operational boundaries for VPPs, effectively mitigating network congestion and voltage fluctuations while ensuring privacy. Additionally, the proposed convex optimization framework allows the publication of operational boundaries for multiple VPPs with minimal computational effort, making it suitable for real-time applications. The effectiveness of the technique is validated using the IEEE benchmark network connected with electricity–hydrogen VPPs. Results demonstrate that the proposed approach maintains voltage levels within standard limits and prevents branch congestion, confirming its suitability for stable and secure grid operations.

Suggested Citation

  • Khalil Gholami & Mohammad Taufiqul Arif & Md Enamul Haque, 2025. "Dynamic Boundary Dissemination to Virtual Power Plants for Congestion and Voltage Management in Power Distribution Networks," Energies, MDPI, vol. 18(3), pages 1-27, January.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:3:p:518-:d:1574532
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    References listed on IDEAS

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    2. Aghdam, Farid Hamzeh & Mudiyanselage, Manthila Wijesooriya & Mohammadi-Ivatloo, Behnam & Marzband, Mousa, 2023. "Optimal scheduling of multi-energy type virtual energy storage system in reconfigurable distribution networks for congestion management," Applied Energy, Elsevier, vol. 333(C).
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    4. J. Boland & J. A. Filar & G. Mohammadian & A. Nazari, 2016. "Australian electricity market and price volatility," Annals of Operations Research, Springer, vol. 241(1), pages 357-372, June.
    5. Oskouei, Morteza Zare & Mohammadi-Ivatloo, Behnam & Abapour, Mehdi & Shafiee, Mahmood & Anvari-Moghaddam, Amjad, 2021. "Privacy-preserving mechanism for collaborative operation of high-renewable power systems and industrial energy hubs," Applied Energy, Elsevier, vol. 283(C).
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