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Smart meter data-driven dynamic operating envelopes for DERs

Author

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  • Kumarawadu, Achala
  • Azim, M. Imran
  • Khorasany, Mohsen
  • Razzaghi, Reza
  • Heidari, Rahmat

Abstract

This paper proposes a data-driven method for determining dynamic operating envelopes for distributed energy resources in low-voltage distribution networks using smart meter data. The proposed method utilizes voltage sensitivity coefficients, derived from individual consumer/prosumer smart meter data, to estimate the network impedance values. These estimated network impedance values are used to compute dynamic operating envelopes for each distributed energy resource. The estimated impedance values include coupling between phases, which would accurately capture the effects of network unbalance and neutral voltage shift on prosumers. Furthermore, a voltage sensitivity-based capacity allocation for dynamic operating envelopes calculation is presented, and its performance is evaluated against equal kW reduction and maximizing exports objective functions. The proposed framework is tested on an unbalanced, 3-phase 4-wire low-voltage distribution network, and the simulation results show that it can accurately capture network behavior, which would enable the computation of dynamic operating envelopes for networks with unknown or inaccurate topologies.

Suggested Citation

  • Kumarawadu, Achala & Azim, M. Imran & Khorasany, Mohsen & Razzaghi, Reza & Heidari, Rahmat, 2025. "Smart meter data-driven dynamic operating envelopes for DERs," Applied Energy, Elsevier, vol. 384(C).
    • Handle: RePEc:eee:appene:v:384:y:2025:i:c:s0306261925001990
    DOI: 10.1016/j.apenergy.2025.125469
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    References listed on IDEAS

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    1. Jiang, Zhisen & Guo, Ye & Wang, Jianxiao, 2025. "Dynamic operating envelopes embedded peer-to-peer-to-grid energy trading," Applied Energy, Elsevier, vol. 377(PB).
    2. Kharrazi, A. & Sreeram, V. & Mishra, Y., 2020. "Assessment techniques of the impact of grid-tied rooftop photovoltaic generation on the power quality of low voltage distribution network - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    3. Hoque, Md Murshadul & Khorasany, Mohsen & Azim, M. Imran & Razzaghi, Reza & Jalili, Mahdi, 2024. "A framework for prosumer-centric peer-to-peer energy trading using network-secure export–import limits," Applied Energy, Elsevier, vol. 361(C).
    4. Zabihinia Gerdroodbari, Yasin & Khorasany, Mohsen & Razzaghi, Reza, 2022. "Dynamic PQ Operating Envelopes for prosumers in distribution networks," Applied Energy, Elsevier, vol. 325(C).
    5. Shabbir, Noman & Kütt, Lauri & Astapov, Victor & Daniel, Kamran & Jawad, Muhammad & Husev, Oleksandr & Rosin, Argo & Martins, João, 2024. "Enhancing PV hosting capacity and mitigating congestion in distribution networks with deep learning based PV forecasting and battery management," Applied Energy, Elsevier, vol. 372(C).
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