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ORIGINAL RESEARCH article

Front. Energy Res.
Sec. Energy Storage
Volume 12 - 2024 | doi: 10.3389/fenrg.2024.1415796
This article is part of the Research Topic Optimization and Data-driven Approaches for Energy Storage-based Demand Response to Achieve Power System Flexibility View all 14 articles

Parameter Identification Method of Load Modeling Based on Improved Dung Beetle Optimizer Algorithm

Provisionally accepted
Xing Chao Xing Chao *Xi Xinze Xi Xinze He Xin He Xin Deng Can Deng Can
  • Electric Power Research Institute of Yunnan Power Grid Company, Kunming, China

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

    The role of load modeling in power systems is crucial for both operational and regulatory considerations. It is essential to develop an effective and reliable method for optimizing load modeling parameter identification. In this paper, the dung beetle algorithm is improved by using the good point set, and a load model parameter identification strategy based on the good point set dung beetle optimization algorithm (GDBO) within the framework of the measurement-based load modeling method. The proposed parameter identification strategy involves utilizing PMU voltage data as input, selecting a comprehensive load model, and refining the initialization process based on the good point set to mitigate the influence of local maxima. Through iterative optimization of the objective function using the Dung Beetle Optimizer (DBO) algorithm, the optimal parameters for the comprehensive load model are determined, enhancing the model's ability to accurately capture the power curve. Analysis of examples pertaining to PMU-measured modeling parameter identification reveals that the proposed GDBO algorithm, which incorporates a good point set, outperforms alternative methods such as the improved differential evolution algorithm (IDE), particle swarm optimization algorithm (PSO), grey wolf optimization algorithm (GWO), and conventional DBO algorithm. This demonstrates the superior performance of the introduced approach in the context of load model parameter identification. ' The best position for the dung ball () m Pn A set of good points ' '' ' '' 2 ' ' 0

    Keywords: DBO algorithm, Good point set, Parameter identification, Load modeling, Electric power system

    Received: 11 Apr 2024; Accepted: 19 Jul 2024.

    Copyright: © 2024 Chao, Xinze, Xin and Can. 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: Xing Chao, Electric Power Research Institute of Yunnan Power Grid Company, Kunming, China

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