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电动汽车驱动 ★ 5.0

基于发电机测量的强迫振荡源定位

Forced Oscillation Source Localization From Generator Measurements

作者 Melvyn Tyloo · Marc Vuffray · Andrey Y. Lokhov
期刊 IEEE Transactions on Power Systems
出版日期 2025年9月
技术分类 电动汽车驱动
相关度评分 ★★★★★ 5.0 / 5.0
关键词 广域振荡 强迫振荡 源定位 数据驱动方法 Kron约简
语言:

中文摘要

设备故障、误操作或周期性负荷变化可能引发持续的周期性扰动,导致系统内能量异常传递,即强迫振荡。广域振荡可能损坏设备、触发误跳闸或控制动作,甚至导致设备失效。然而,其振源的位置、频率和幅值难以确定。近期提出了一种基于数据驱动的最大似然方法用于传输电网中的振源定位,但该方法依赖全PMU覆盖且假设所有母线具有惯性和阻尼。本文将其扩展至更真实场景,包含无惯性和阻尼的节点(如被动负荷和逆变型电源)。通过将克朗降阶直接融入最大似然估计器,可准确识别施加于传统发电机和负荷上的强迫源位置与频率。

English Abstract

Malfunctioning equipment, erroneous operating conditions or periodic load variations can cause periodic disturbances that would persist over time, creating an undesirable transfer of energy across the system – an effect referred to as forced oscillations. Wide-area oscillations may damage assets, trigger inadvertent tripping or control actions, and be the cause of equipment failure. Unfortunately, for wide-area oscillations, the location, frequency, and amplitude of these forced oscillations may be hard to determine. Recently, a data-driven maximum-likelihood-based method was proposed to perform source localization in transmission grids under wide-area response scenarios. However, this method relies on full PMU coverage and all buses having inertia and damping. Here, we extend this method to realistic scenarios which includes buses without inertia or damping, such as passive loads and inverter-based generators. Incorporating Kron reduction directly into the maximum likelihood estimator, we are able to identify the location and frequency of forcing applied at both traditional generators and loads.
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SunView 深度解读

该强迫振荡源定位技术对阳光电源储能和光伏并网系统具有重要应用价值。文章针对含逆变型电源(无惯性节点)的电网场景,通过克朗降阶扩展最大似然估计方法,可精准识别振荡源位置与频率。这直接适用于阳光电源ST系列储能变流器和SG系列光伏逆变器的并网控制优化:1)在PowerTitan大型储能系统中集成振荡源监测功能,提升电网支撑能力;2)为构网型GFM和跟网型GFL控制策略提供振荡抑制依据,避免逆变器误跳闸;3)在iSolarCloud平台增加广域振荡预警模块,实现预测性维护。该技术可增强新能源设备在弱电网环境下的稳定运行能力,符合高比例新能源接入需求。