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考虑电流限制、惯性和阻尼效应的构网型变流器暂态稳定性综合评估

Comprehensive Assessment of Transient Stability for Grid-forming Converters Considering Current Limitations, Inertia and Damping Effects

语言:

中文摘要

本文定量评估了考虑电流限制、惯性和阻尼效应的构网型变流器暂态稳定性。首先,分析了电压跌落下受电流限制的变流器暂态稳定性,当跌落超过临界阈值时,系统出现失稳,其严重程度受摇摆方程中惯性和阻尼系数影响。其次,基于相平面模型方法,系统评估了惯性和阻尼对临界清除时间(CCT)与临界清除角(CCA)的影响,并利用相轨迹数据构建人工神经网络(ANN)模型实现CCT与CCA的精确预测。相比基于等面积准则的保守评估,该方法可延长故障下的实际运行时间,充分挖掘系统的低电压穿越(LVRT)与故障穿越(FRT)能力。理论分析与评估方法通过PSCAD/EMTDC仿真验证。

English Abstract

This paper presents a quantitative assessment of the transient stability of grid-forming converters,considering current limitations,inertia,and damping effects.The contributions are summarized in two main aspects:First,the analysis delves into transient stability under a general voltage sag scenario for a converter subject to current limitations.When the voltage sag exceeds a critical threshold,transient instability arises,with its severity influenced by the inertia and damping coefficients within the swing equation.Second,a comprehensive evaluation of these inertia and damping effects is conducted using a model-based phase-portrait approach.This method allows for an accurate assessment of critical clearing time(CCT)and critical clearing angle(CCA)across varying inertia and damping coefficients.Leveraging data obtained from the phase portrait,an artificial neural network(ANN)method is presented to model CCT and CCA accurately.This precise estimation of CCT enables the extension of practical operation time under faults compared to conservative assessments based on equal-area criteria(EAC),thereby fully exploiting the system's low-voltage-ride-through(LVRT)and fault-ride-through(FRT)capabilities.The theoret-ical transient analysis and estimation method proposed in this paper are validated through PSCAD/EMTDC simulations.
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SunView 深度解读

该研究对阳光电源ST系列储能变流器和PowerTitan大型储能系统的构网型控制具有重要应用价值。文章提出的基于相平面和ANN的暂态稳定评估方法,可精确预测电流限制下的CCT/CCA,相比传统等面积准则更准确,能有效提升产品LVRT/FRT能力。该方法可直接应用于ST系列的虚拟同步机控制参数优化,通过定量评估惯性和阻尼系数对暂态稳定的影响,实现控制参数自适应调节。结合iSolarCloud平台的智能诊断功能,可实时监测电网故障并预判穿越能力,充分挖掘储能系统在弱电网环境下的运行裕度,提升产品在高比例新能源电网中的适应性和竞争力。