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基于多变量样本卷积交互网络的电力系统频率安全性评估
作者:
作者单位:

1.电动汽车电网接入技术国家地方联合工程实验室(山东大学),山东省济南市 250061;2.山东大学计算机科学与技术学院,山东省青岛市 266200;3.山东大学电气工程学院,山东省济南市 250061

摘要:

现有电力系统暂态频率智能评估方法未充分考虑输入数据的时序特征。因此,文中提出一种基于暂态频率响应曲线智能预测的电力系统频率安全性评估方法。设计了一种多变量样本卷积交互网络,可充分挖掘电力系统量测数据的时序特征,从而提高电力系统暂态频率响应曲线的预测精度;基于所预测的频率响应曲线计算最大频率偏差、最大频率偏差发生时间和准稳态频率等关键指标,并综合评估系统的频率安全性。在频率稳定标准算例上进行仿真测试,结果表明,所提方法与深度学习等经典方法相比,频率响应曲线预测和系统频率安全性评估精度均得到有效提升。

关键词:

基金项目:

国家重点研发计划资助项目(2021YFB2400800)。

通信作者:

作者简介:

刘杰(1999—),男,硕士研究生,主要研究方向:电力系统频率安全。
石访(1982—),男,通信作者,博士,副教授,主要研究方向:电力系统稳定分析与控制、电力系统同步测量技术与应用。E-mail:shifang@sdu.edu.cn
宋雪萌(1990—),女,副教授,博士生导师,主要研究方向:信息技术与人工智能。


Frequency Safety Assessment of Power Systems Based on Multivariable-sample Convolution and Interaction Network
Author:
Affiliation:

1.National Joint Engineering Laboratory of Power Grid with Electric Vehicles (Shandong University), Jinan250061, China;2.School of Computer Science and Technology, Shandong University, Qingdao266200, China;3.School of Electrical Engineering, Shandong University, Jinan250061, China

Abstract:

The existing intelligent transient frequency assessment methods in power systems do not adequately consider the temporal characteristics of input data. Therefore, a frequency safety assessment method for power systems based on intelligent prediction of transient frequency response curves is proposed. A multivariate-sample convolutional interactive network is designed to fully exploit the temporal characteristics of power system measurement data, thereby improving the prediction accuracy of transient frequency response curves of the power system. Key indicators, such as the maximum frequency deviation, occurrence time of the maximum frequency deviation, and the metastability frequency are calculated based on the predicted frequency response curves, and the frequency safety of the system is comprehensively assessed. Simulation tests are conducted on frequency stability standard cases, and the results show that the proposed method effectively improves the accuracies of frequency response curve prediction and system frequency safety assessment compared with classical methods such as deep learning.

Keywords:

Foundation:
This work is supported by National Key R&D Program of China (No. 2021YFB2400800).
引用本文
[1]刘杰,石访,宋雪萌,等.基于多变量样本卷积交互网络的电力系统频率安全性评估[J].电力系统自动化,2024,48(22):160-170. DOI:10.7500/AEPS20231101004.
LIU Jie, SHI Fang, SONG Xuemeng, et al. Frequency Safety Assessment of Power Systems Based on Multivariable-sample Convolution and Interaction Network[J]. Automation of Electric Power Systems, 2024, 48(22):160-170. DOI:10.7500/AEPS20231101004.
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  • 收稿日期:2023-11-01
  • 最后修改日期:2024-02-29
  • 录用日期:2024-04-03
  • 在线发布日期: 2024-11-21
  • 出版日期: