Transient Instability Prediction Using Decision Tree Technique

被引：136

作者：

Amraee, Turaj ^{[1
]}

Ranjbar, Soheil ^{[2
]}

机构：

[1] KN Toosi Univ Technol, Dept Elect Engn, Tehran 1431714191, Iran

[2] Islamic Azad Univ, Sci & Res Branch, Tehran, Iran

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 2013年 / 28卷 / 03期

关键词：

Decision tree; out-of-step; power swing; prediction; transient stability; SUPPORT VECTOR MACHINES;

D O I：

10.1109/TPWRS.2013.2238684

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents a decision tree based method for out-of-step prediction of synchronous generators. For distinguishing between stable and out-of-step conditions, a series of measurements are taken under various fault scenarios including operational and topological disturbances. The data of input features and output target classes are used as the input-output pairs for decision tree induction and deduction. The merit of decision tree based detection of transient instability lies in robust classification of new unseen samples. The performance of the proposed method is verified on two test cases including a 9-bus dynamic network and the practical 1696-bus Iran national grid. The simulation results are presented for various input features and learning parameters.

引用

页码：3028 / 3037

页数：10

共 50 条

[31] Prosody Phrase Break Prediction in Vietnamese Using Decision Tree
Kui, Liping
Yang, Jian
Cheng, Yang
He, Bin
PROCEEDINGS OF THE 31ST CHINESE CONTROL CONFERENCE, 2012, : 3733 - 3736
[32] Prediction of thyroid disease using decision tree ensemble method
Dhyan Chandra Yadav
Saurabh Pal
Human-Intelligent Systems Integration, 2020, 2 (1-4) : 89 - 95
[33] The analysis of simulated sow herd datasets using decision tree technique
Kirchner, K
Tölle, KH
Krieter, J
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2004, 42 (02) : 111 - 127
[34] Intrusion detection using decision tree classifier with feature reduction technique
Raza, Syed Atir
Shamim, Sania
Khan, Abdul Hannan
Anwar, Aqsa
MEHRAN UNIVERSITY RESEARCH JOURNAL OF ENGINEERING AND TECHNOLOGY, 2023, 42 (02) : 30 - 37
[35] Bad data detection in state estimation using Decision Tree technique
Zakerian, A.
Maleki, A.
Mohammadnian, Y.
Amraee, Turaj
2017 25TH IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING (ICEE), 2017, : 1037 - 1042
[36] Expectation of Radar Returns from Ionosphere Using Decision Tree Technique
Basha, G. Ameer
Gupta, K. Lakshmana
Ramakrishna, K.
ADVANCES IN DATA SCIENCE AND MANAGEMENT, 2020, 37 : 209 - 214
[37] Prediction of Learning Disabilities in School Age Children Using Decision Tree
Julie, M. David
Kannan, Balakrishnan
RECENT TRENDS IN NETWORKS AND COMMUNICATIONS, 2010, 90 : 533 - +
[38] Classification prediction of the foot disease pattern using decision tree model
Choi, Jung-Kyu
Won, Yonggwan
Kim, Jung-Ja
Lecture Notes in Electrical Engineering, 2015, 339 : 785 - 791
[39] Prediction of Students Programming Performance Using Naive Bayesian and Decision Tree
Sivasakthi, M.
Padmanabhan, K. R. Anantha
SOFT COMPUTING FOR SECURITY APPLICATIONS, ICSCS 2022, 2023, 1428 : 97 - 106
[40] Prediction of biopharmaceutical facility fit issues using decision tree analysis
Yang, Yang
Farid, Suzanne S.
Thornhill, Nina F.
23 EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, 2013, 32 : 61 - 66

← 1 2 3 4 5 →