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储能系统技术 储能系统 SiC器件 多物理场耦合 ★ 5.0

功率振荡定位:一种基于同步相量的自适应Vold-Kalman滤波能量法

Power Oscillation Localization: A Synchrophasor Based Adaptive Vold-Kalman Filtering Energy Flow

作者 Qin Huang · Wei Qiu · Yao Zheng · Junfeng Duan · Jian Zuo · Wenxuan Yao
期刊 IEEE Transactions on Power Delivery
出版日期 2024年11月
技术分类 储能系统技术
技术标签 储能系统 SiC器件 多物理场耦合
相关度评分 ★★★★★ 5.0 / 5.0
关键词 电力振荡源定位 自适应Vold - Kalman滤波 能量法 同步相量测量 振荡频率识别
语言:

中文摘要

随着相量测量单元(PMU)在电力系统中的广泛应用,利用同步相量数据实现功率振荡源定位成为可能。然而,传统的基于能量的定位方法易受噪声及无关频率成分干扰。为此,本文提出一种基于自适应Vold-Kalman滤波的能量法(A-VKF-Energy)。首先通过快速傅里叶变换识别有功功率中的振荡频率,进而采用自适应Vold-Kalman滤波提取各支路振荡分量,并计算其耗散能量。以能量变化斜率比作为能量流动方向判据,自动判定振荡源位置。仿真与实际事件验证表明,该方法能有效抑制频域耦合干扰,准确识别振荡源。

English Abstract

With widespread deployments of phasor measurement units (PMUs) in power systems, the localization of power oscillations using synchrophasor measurements has become feasible. However, the classical method for source localization, known as the energy-based method, is significantly impacted by noise and other irrelevant frequency components, which are common in synchrophasor measurements. In response to this challenge, the paper proposes an adaptive Vold-Kalman filtering-based Energy method (A-VKF-Energy). Initially, the Fast Fourier Transform is employed to identify oscillation frequency in active power, offering a reference for subsequent component extraction. The Adaptive Vold-Kalman filtering is then utilized to extract oscillation components from PMU data, which are subsequently employed in computing dissipating energy for each branch. Moreover, the slope ratio of the energy is employed as an indicator of the energy flow direction in the power system, automating the process of determining the source of oscillations. The superior performance of adaptive Vold-Kalman filtering in frequency coupling is verified by simulated experiments. Furthermore, simulation using WECC 179 test case data and actual experiments using a real oscillation event are carried out to verify the effectiveness of proposed method. The results reveal that A-VKF-Energy method can successfully identify oscillation sources.
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SunView 深度解读

该功率振荡定位技术对阳光电源大型储能系统(PowerTitan)和构网型控制产品具有重要应用价值。在储能电站并网场景中,A-VKF-Energy方法可集成至iSolarCloud平台,实时监测ST系列储能变流器引发的次同步/超同步振荡,通过PMU数据精准定位振荡源支路,避免误判。该技术可优化GFM构网型控制策略的参数整定,在多储能单元并联时快速识别振荡发起者,触发自适应阻尼控制或主动解列保护。对于光储融合电站,该算法能区分光伏逆变器与储能系统的振荡贡献度,为SiC器件开关频率优化和多物理场耦合抑制提供数据支撑,提升系统稳定性和故障诊断能力。