A Two-Stage Fault Location Identification Method in Multiarea Power Grids Using Heterogeneous Types of Data
A Two-Stage Fault Location Identification Method in Multiarea Power Grids Using Heterogeneous Types of Data
复制标题
DOI：
10.1109/tii.2018.2885320
复制
发表时间：
2019-07
影响因子：
12.3
通讯作者：
Iman Kiaei;S. Lotfifard
中科院分区：
文献类型：
--
作者：
Iman Kiaei;S. Lotfifard
本文提出了一种适用于多区域电力系统的两阶段故障测距方法。它利用由状态数据（即，离散数据）和模拟数据（即，继续数据）。提出了一种基于P-不变Petri网的分布式因果模型诊断方法，该方法利用状态数据查找故障区段。多区域电力系统的每个子系统/区域都有自己的诊断模型，并根据其局部网络、局部表现以及与相邻子系统/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区段的短列表，第二阶段就使用模拟数据进一步改进估计的故障位置。实际的故障位置是通过比较测量的模拟数据与其相关的计算值在计算机程序中使用短路分析算法估计。仿真结果表明，提出的分布式故障定位方法可以准确地诊断多区域电力系统的故障。
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 location method can diagnose faults in multiarea power systems accurately.