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ORIGINAL RESEARCH article

Front. Energy Res.
Sec. Smart Grids
Volume 12 - 2024 | doi: 10.3389/fenrg.2024.1514705
This article is part of the Research Topic Distributed Learning, Optimization, and Control Methods for Future Power Grids, Volume II View all 20 articles

On-line Strength Assessment of Distribution Systems with Distributed Energy Resources

Provisionally accepted
Jifeng Liang Jifeng Liang 1Shiyang Rong Shiyang Rong 1Tengkai Yu Tengkai Yu 1Tiecheng Li Tiecheng Li 1Hanzhang Qu Hanzhang Qu 2Ye Cao Ye Cao 2*
  • 1 State Grid Hebei Electric Power Research Institute, Shijiazhuang, Hebei Province, China
  • 2 Xi'an Jiaotong University, Xi'an, China

The final, formatted version of the article will be published soon.

    To enable the online strength assessment of distribution systems integrated with Distributed Energy Resources (DERs), a novel hybrid model and data-driven approach is proposed. Based on the IEC-60909 standard, a new short-circuit calculation method is developed, allowing inverterbased DERs (IBDERs) to be represented as either voltage or current sources with controllable internal impedance. This method also accounts for the impact of distant generators by introducing a site-dependent Short Circuit Ratio (SCR) index to evaluate system strength. An adaptive sampling strategy is employed to generate synthetic data for real-time assessment. To predict the strength of distribution systems under various conditions, a rectified linear unit (ReLU) neural network is trained and further reformulated as a mixed-integer linear programming (MILP) problem to verify its robustness and input stability. The proposed method is validated through case studies on modified IEEE-33 and IEEE-69 bus systems, demonstrating its effectiveness regarding the varying operating conditions within the system.

    Keywords: System strength, Short circuit ratio, Distribution systems, input stability verification, Online forecasting

    Received: 21 Oct 2024; Accepted: 13 Dec 2024.

    Copyright: © 2024 Liang, Rong, Yu, Li, Qu and Cao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Ye Cao, Xi'an Jiaotong University, Xi'an, China

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