Method for Real-Time Abnormal State Detection of a Distribution Network Based on Maximum and Minimum Eigenvalues

Yuzhu Wang,Huanna Niu,Jingxiang Zhao,Keyan Liu,Kaiyuan He

doi:10.1155/2017/4092701

Abstract

The state analysis method of a traditional distribution network operation is strictly dependent on the physical model of itself, but it varies as the geography changes, and it is difficult to find the abnormal state of a district network on real-time, especially the sudden change caused by the distributed energy and EV load. So, a method of the abnormal state detecting for the distribution network is proposed based on the maximum and minimum eigenvalues. Firstly, a high-dimensional random matrix is established by the big data from the distribution network management system to take abnormal state detection through a real-time sliding window. Then, the maximum and minimum eigenvalues of the distribution network are gained by calculating the sample covariance matrix of the random matrix and determining the maximum and minimum eigenvalues of the latter matrix. Finally, an 1177-node testing system was taken as an example, and the simulation results showed that the proposed method could detect the abnormal state in real-time without depending on the physical model and fault type of the grid.

Highlights

The state analysis of a traditional distribution network operation that uses a physical model to establish the mathematical model and carries on the numerical calculation has obtained very good application effects
The traditional method varies as the geography changes, and it is difficult to find the abnormal state of a district network on real-time, especially the sudden change caused by the distributed energy and EV load
Literature [2] proposed a strategy of operational status recognition based on FCM (Fuzzy C-Mean) and ANFIS (Adaptive Network Fuzzy Inference System) which constructs a kind of classifier based on ANFIS for the hierarchical fuzzy inference system and applies the FCM classification method to optimally initialize its parameters

Summary

Introduction

The state analysis of a traditional distribution network operation that uses a physical model to establish the mathematical model and carries on the numerical calculation has obtained very good application effects. Based on the RMT, this paper uses the MME method to analyze the operating state of the power system in realtime and to accurately detect the abnormal time. The results showed that the MME method had a good effect on application in the abnormal state detection of a power network, which provides a new idea for the application of large data real-time analysis technology in power network operation analysis.

Results

Conclusion