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Current mutation and phase differential fault identification algorithm based on supply area sampling calibration method for active distribution network

机译:基于电源区采样校准方法的电流突变与相位差分故障识别算法

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More distributed energy resource (DER), regarded as clean energy source, become accessed into the distribution power system. However, it brings different influence on the judgement of protection act and fault location as before. This paper mainly focus on how to use these clean energy sources more effectively and to ensure safe operation of power system without the introducing of other facility. This paper proposes unified-sampling calibration method in which data of all the interconnected feeders in supply area is collected. Without changing the original network topology, the concept of “directed graph” is introduced to carry out of current direction calibration. With the results of such sampling calibration method, current mutation is to be the startup condition to locate the fault precisely. Through local communication in distributed FA and GPS time synchronization, current wave data is transferred between adjacent FA controllers. Fault identification algorithm based on current mutation and phase differential is proposed.
机译:更加分布式的能源(Der)被视为清洁能源,进入分配电力系统。但是,它对如前所述对保护行为和故障位置的判断产生了不同的影响。本文主要侧重于如何更有效地使用这些清洁能源,并确保电力系统的安全运行而不引入其他设施。本文提出了统一采样校准方法,其中收集了供应区中所有互连进料器的数据。在不改变原始网络拓扑的情况下,引入了“定向图”的概念以执行当前方向校准。随着这种采样校准方法的结果,电流突变是精确定位故障的启动条件。通过分布式FA和GPS时间同步的本地通信,在相邻的FA控制器之间传输电流波数据。提出了基于电流突变和相位差的故障识别算法。

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