Robust estimation method for power system dynamic synchronization with sensor gain degradation

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS ISA transactions Pub Date : 2025-01-01 Epub Date: 2024-11-14 DOI:10.1016/j.isatra.2024.10.031

Yi Wang , Jiawei Zhang , Yaoqiang Wang , Zhongwen Li , Kewen Wang , Jun Liang

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Abstract

Efficient and accurate real-time estimation of power system synchronization is quite important for its safety control and operation. However, signal sensing failure, electromagnetic interference, system delay, etc., will cause the sensor gain degradation. To furnish a dependable method for dynamic estimation in power grid synchronization amid sensor gain degradation, this research presents a robust estimation system capable of monitoring and tracking the frequency, voltage phase angles, and magnitudes. Firstly, the random degradation of measurement data is characterized by a discrete distribution within the range [0,1]. Secondly, the state space model of sensor gain degradation is established. Subsequently, a novel modified fault-tolerant extended Kalman filter (MFTEKF) is developed under the recursive estimator framework. Finally, extensive experimental results definitively demonstrate that the proposed MFTEKF can accurately monitor the dynamic characteristics of the power grid.

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传感器增益衰减情况下电力系统动态同步的鲁棒估计方法。

高效、准确的电力系统同步实时估算对于电力系统的安全控制和运行相当重要。然而，信号传感故障、电磁干扰、系统延迟等都会导致传感器增益衰减。为了在传感器增益衰减的情况下提供可靠的电网同步动态估算方法，本研究提出了一种能够监测和跟踪频率、电压相位角和幅值的鲁棒估算系统。首先，测量数据的随机衰减以 [0,1] 范围内的离散分布为特征。其次，建立传感器增益衰减的状态空间模型。随后，在递归估计器框架下开发了一种新颖的改进型容错扩展卡尔曼滤波器（MFTEKF）。最后，大量实验结果明确表明，所提出的 MFTEKF 能够准确监测电网的动态特性。

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来源期刊

ISA transactions 工程技术-工程：综合

CiteScore

11.70

自引率

12.30%

发文量

824

审稿时长

4.4 months

期刊介绍： ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.