Fault classification in inverter based resources system using spherical coordinate system

Vivek Sahu, Pratim Kundu
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引用次数: 0

Abstract

Modern grid codes require renewable energy source (RES) plants to remain connected with the grid even during fault scenarios. Fault current being comparable to rated full-load output of RES plants, makes timely fault analysis a more challenging task. In this work, fault detection and classification on a network based fully on inverter-based resources (IBRs) is proposed. Discrete Fourier transformation is utilized to extract fundamental component of three-phase voltages and currents. Two separate indices for fault classification, based on Spherical Coordinate System (SCS)-based representation is proposed. Mathematical derivations form the underlying basis for simplistic threshold settings. Based on the indices, decision variables are set. Sign-based identification of faulty phase(s), without the need of prior fault-type identification, is done by a new category of power variables. Final decision is reached through a proposed trip logic. Timely response of fault analysis is identified to be within practical limits to suit industrial requirements. The methodology is tested on a modified IEEE 9-bus model using PSCAD/EMTDC. Different fault types, fault distance, inception angle and resistance are found to validate the threshold settings. Satisfactory performance during switching events like load, generator and line tripping ensures its robustness.
基于球坐标系的逆变器资源系统故障分类
现代电网规范要求可再生能源(RES)电厂即使在故障情况下也要与电网保持连接。故障电流与可再生能源电厂的额定满负荷输出相当,这使得及时进行故障分析变得更具挑战性。本文提出了一种完全基于逆变器资源(ibr)的网络故障检测与分类方法。利用离散傅里叶变换提取三相电压和电流的基元分量。提出了基于球坐标系统(SCS)表示的两种独立的故障分类指标。数学推导构成了简单阈值设置的基础。根据这些指标,设置决策变量。基于符号的故障相位识别不需要预先进行故障类型识别,而是通过一种新的功率变量来实现。最后的决定是通过一个建议的行程逻辑达成的。确定故障分析的及时响应在实际范围内,以满足工业要求。该方法在改进的IEEE 9总线模型上使用PSCAD/EMTDC进行了测试。找出不同的故障类型、故障距离、起始角和电阻,验证阈值设置。在负荷、发电机和线路跳闸等切换事件中令人满意的性能保证了其稳健性。
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CiteScore
2.10
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