مدلی هوشمند بر پایه تحلیل فضای فاز برای دسته‌بندی خطا در خطوط انتقال تک‌مداره

نوع مقاله : مقاله برق

نویسندگان

1 مهندسی برق قدرت-دانشکده مهندسی برق و کامپیوتر-دانشگاه صنعتی جندی شاپور-دزفول

2 دانشکده مهندسی برق و کامپیوتر - دانشگاه صنعتی جندی شاپور – دزفول-ایران

10.22075/jme.2019.17886.1725

چکیده

از جمله ملاحظات مهم در حفاظت مدرن خطوط انتقال، سرعت و دقت در دسته‌بندی نوع خطا است‌‌که تاثیر زیادی بر مدت زمان پاک شدن خطا و دقت تشخیص خطا توسط رله دیستانس، دارد. هدف از این مطالعه، استفاده از تحلیل فضای فاز و الگوریتم یادگیری درخت تصمیم‌ برای دسته‌بندی نوع خطا در خطوط انتقال تک‌مداره بوده است. بر این اساس، الگوریتمی طراحی شده است‌که در آن، ابتدا سیگنال‌های جریان و ولتاژ سه‌فاز در یک سمت خط انتقال اندازه‌گیری و نمونه‌برداری می‌شوند. سپس، پس از تحلیل فضای فاز نمونه‌های جریان و ولتاژ، بردار ویژگی‌های آماری خروجی تحلیل مذکور محاسبه می‌گردد. در پایان، بردار ویژگی به مدل هوشمند از قبل آموزش داده شده، برای تعیین نوع خطای رخ داده، اعمال می‌شود. الگوریتم پیشنهادی بر روی شبکه نمونه و در شرایط مختلف وقوع خطا شامل مقادیر مختلف مقاومت خطا، لحظه وقوع خطا، میزان توان انتقالی بر روی خط انتقال و مکان‌ وقوع خطا بررسی و مورد آزمایش واقع شده است. نتایج نشان می‌دهند که مدل هوشمند پیشنهادی می‌تواند نوع خطا را با طول پنجره داده پس از وقوع خطای کمتر از 2 میلی‌ثانیه و دقت 100 درصد تعیین نماید.

کلیدواژه‌ها


عنوان مقاله [English]

An Intelligent Model Based on Phase Space Analysis for Fault Classification in Single Circuit Transmission Lines

نویسندگان [English]

  • Mostafa Sarlak 1
  • Daryoush Farhadi 2
1 Ele. & Com. Eng. Department, Jondi-shapur university of technology-Dezful-Iran.
2 Jundi-Shapur University of Technology, Dezful, Iran
چکیده [English]

Two important issues in the modern transmission lines protection are the speed and accuracy of the fault type classification, which have a great impact on the duration of fault clearing time and the accuracy of fault detection by the distance relay. The purpose of this study was to use the phase space analysis and decision tree-learning algorithm to classify the fault type in single circuit transmission lines. Accordingly, an algorithm is developed in which the three-phase current and voltage signals are measured and sampled on one side of the transmission line, firstly. Then, after the phase space analyzing of the current and voltage samples, the statistical feature vector of the output of the analysis is calculated. In the end, the feature vector is fed to the pre-trained intelligent model, to determine the type of fault occurred. The proposed algorithm has been investigated and tested on the sample network in different fault conditions, including different values of fault resistance, fault inception time, the amount of the transferred power on the transmission line, and the fault location. The results show that the proposed algorithm can determine the fault type with a length of post-fault data window less than 2 ms and accuracy of 100 percent.

کلیدواژه‌ها [English]

  • Single circuit transmission lines
  • Transmission line protection
  • Intelligent model
  • Fault classification
  • Phase space analysis
  • Decission tree
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