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A Two-Stage Fault Location Identification Method in Multiarea Power Grids Using Heterogeneous Types of Data

机译:基于异构数据的多区域电网两阶段故障位置识别方法

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摘要

This paper proposes a two-stage fault location method for multiarea power systems. It utilizes available heterogeneous types of data consisting of status data (i. e., discrete data) and analog data (i. e., continues data). A distributed casual model-based diagnosis method using P-invariant Petri nets is proposed that utilizes status data to find faulted sections. Each subsystem/area of multiarea power systems has its own diagnostic model and determines the diagnosis solution based on its local net, the local manifestations, and limited information exchange with the neighboring subsystems/areas. Once a short list of possible fault sections is determined, the second stage further improves the estimated fault location using analog data. The actual fault location is estimated by comparing the measured analog data with their associated calculated values in computer programs using short-circuit analysis algorithms. Simulation results demonstrate that the proposed distributed fault locationmethod can diagnose faults inmultiarea power systems accurately.
机译:提出了多区域电力系统的两阶段故障定位方法。它利用了由状态数据(即离散数据)和模拟数据(即连续数据)组成的可用异构类型的数据。提出了一种利用P不变Petri网的基于分布休闲模型的诊断方法,该方法利用状态数据查找故障断面。多区域电力系统的每个子系统/区域都有其自己的诊断模型,并基于其本地网络,本地表现形式以及与相邻子系统/区域的有限信息交换来确定诊断解决方案。一旦确定了可能的故障部分的简短列表,第二阶段将使用模拟数据进一步改善估计的故障位置。通过使用短路分析算法在计算机程序中将测得的模拟数据与其关联的计算值进行比较,可以估算出实际的故障位置。仿真结果表明,所提出的分布式故障定位方法能够准确诊断多区域电力系统的故障。

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