Online Identification of Low-Frequency Oscillation in Power System based on Fuzzy Filter and Prony Algorithm

2006 ◽  
Author(s):  
Da Li ◽  
Yijia Cao ◽  
Guang Wang
Keyword(s):  
Power System ◽  
Low Frequency ◽  
Fuzzy Filter ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Online Identification ◽  
Prony Algorithm

Online Identification and Suppression of Low Frequency Oscillation in Power System Based on WAMS

2014 ◽  
Vol 513-517 ◽  
pp. 2855-2861 ◽  
Author(s):  
Bo Qu ◽  
Jun Yong Wu ◽  
Hong Ke Ai ◽  
Yan Heng Zhou
Keyword(s):  
Power System ◽  
New England ◽  
Low Frequency ◽  
Area Measurement ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Wide Area Measurement System ◽  
Online Identification ◽  
Prony Algorithm ◽  
System Stabilizer

With the assistance of Wide Area Measurement System (WAMS), this paper proposes a method based on Prony algorithm to identify Low Frequency Oscillation (LFO) online and apply Power System Stabilizer (PSS) for rapid suppression. WAMS monitors the power system in real time with high precision. When LFO occurs in the system, applying Prony algorithm to analyze the power angle, it can identify all kinds of LFO modes online. For each mode, PSS would be rapidly configured and applied into the system. When some LFO modes are successfully suppressed, the corresponding PSSs exit. Taking the 10-generator-39-bus system of New England for example, it verifies the correctness and effectiveness of the proposed approach.

The New Identification Method for Low Frequency Oscillation Mode in Power System Based on Prony Algorithm and Neural Network

2013 ◽  
Vol 321-324 ◽  
pp. 1400-1404 ◽  
Author(s):  
Ying Jie Tang ◽  
Ying Jun Tang ◽  
Xin Liang Xie
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Power System ◽  
High Reliability ◽  
Oscillation Mode ◽  
Low Frequency ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Mode Identification ◽  
Prony Algorithm

This paper presented a new improved Prony algorithm based on neural network to train weights.The algorithm solved some problems that difficulty and low precision during matrix inversion in Prony method. According to real-time transform characteristics of low frequency oscillation in power system, the algorithm used limited data windows in on-line parameter estimation and pattern recognition, and improved pattern recognition precision. The simulation results proved that this proposal algorithm has some features of directly ,effective, high reliability, less calculation amount and minor error when it be used to analysis oscillation characteristics and mode identification. So it is suitable for identification of low frequency oscillation mode in power system.

scholarly journals Householder-based Prony Method for Identification of Low-frequency Oscillation in Power System

2019 ◽  
Vol 118 ◽  
pp. 02073
Author(s):  
Simin Zhang ◽  
Guangye Liu ◽  
Yaxin Li ◽  
Jiangang Yao
Keyword(s):  
Power System ◽  
Oscillation Mode ◽  
Low Frequency ◽  
Large Error ◽  
Analysis Tool ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Prony Method ◽  
Prony Algorithm ◽  
Actual Operation

In this paper, the Prony analysis tool with the software used in the actual operation has a large error. The improved Prony method is used to identify the low-frequency oscillation mode of the power system. The traditional Prony algorithm has the problem of insensitivity to parameter error estimation in low frequency oscillation, which affects the accuracy and accuracy of the least squares calculation. Therefore, this paper proposes a Prony method power system low frequency oscillation method using Householder transform to make the calculation more Accurate and proven to be more efficient and reliable.

A Self-Tuning Power System Stabilizer Design

2013 ◽  
Vol 385-386 ◽  
pp. 1104-1107
Author(s):  
Ping Chen ◽  
Hui Lan Jiang ◽  
Kai Zeng
Keyword(s):  
Power System ◽  
Low Frequency ◽  
Power System Stabilizer ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Operating Modes ◽  
Prony Algorithm ◽  
Self Tuning ◽  
System Stabilizer ◽  
System Operating

The traditional power system stabilizer (PSS) usually configures parameters in off-line circumstances and can’t adapt to the variations of power system operating modes well. Based on the prony algorithm, this paper presents a parameter self-tuning PSS. After identifying the system reduced model, it recognizes the real-time low frequency oscillation characteristics of system based on the online prony and uses the dominant mode frequency to complete self-tuning parameters of PSS. The simulation results in IEEE 4-11 system show that the self-tuning PSS based on prony algorithm can adapt to the variations of power system operating modes and restrain low frequency oscillation system better, then improve the stability of the system.

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