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基于改进生成对抗网络的谐波状态估计方法
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作者单位:

1.华北电力大学控制与计算机工程学院,北京市 102206;2.华北电力大学电气与电子工程学院,北京市 102206

摘要:

传统的基于最小二乘法的谐波状态估计受到量测装置少、精确的谐波阻抗获取难、网络拓扑结构复杂以及电网运行方式变化等因素的限制,造成量测方程欠定、系统非全局可观以及节点间耦合关系难以准确提取等问题。文中提出了一种基于改进生成对抗网络的谐波状态估计方法。该方法基于pix2pix谐波状态估计网络拟合监测节点与目标节点间的耦合关系,利用采集的历史谐波数据,对模型进行批量训练,通过训练之后的生成网络估算目标节点谐波电流、谐波电压幅值,实现基于数据驱动的谐波状态估计。在加噪环境下对模型进行测试,仿真结果验证了所提方法的有效性。

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作者简介:

马永硕(1996—),男,硕士研究生,主要研究方向:深度学习应用、电能质量信息处理。E-mail:844063587@qq.com
齐林海(1964—),男,通信作者,副教授,主要研究方向:电能质量智能信息处理、智能电网大数据应用。E-mail:qilinhai@ncepu.edu.cn
肖湘宁(1953—),男,教授,博士生导师,主要研究方向:新能源电网中的电力电子技术、电力系统电能质量。E-mail:xxn@ncepu.edu.cn


Estimation Method of Harmonic State Based on Improved Generative Adversarial Network
Author:
Affiliation:

1.School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China;2.School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China

Abstract:

The traditional harmonic state estimation based on the least-square method is limited by the few measuring devices, difficulty in obtaining accurate harmonic impedance, complex network topology and the variation of grid operation mode, which results in problems such as underdetermined measurement equations, non-global observation of the power system and difficulty in accurately extracting coupling relationships between buses. This paper proposes a harmonic state estimation method based on the improved generative adversarial network. The method is based on the pix2pix harmonic state estimation network to fit the coupling relationship between the monitoring buses and the target buses. And the collected historical harmonic data is used to batch train the model. The harmonic current and harmonic voltage amplitude of the target buses are estimated by the generated network after training to achieve data-driven harmonic state estimation. The model is tested in an environment with noise, and the simulation results verify the effectiveness of the proposed method.

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引用本文
[1]马永硕,齐林海,肖湘宁,等.基于改进生成对抗网络的谐波状态估计方法[J].电力系统自动化,2022,46(1):139-145. DOI:10.7500/AEPS20201024001.
MA Yongshuo, QI Linhai, XIAO Xiangning, et al. Estimation Method of Harmonic State Based on Improved Generative Adversarial Network[J]. Automation of Electric Power Systems, 2022, 46(1):139-145. DOI:10.7500/AEPS20201024001.
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  • 收稿日期:2020-10-24
  • 最后修改日期:2021-01-20
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  • 在线发布日期: 2022-01-05
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