پیش‌بینی هوشمند ناپایداری گذرا پس از وقوع اغتشاش با استفاده از سیستم اندازه‌گیری ناحیه گسترده

نویسندگان

دانشکده مهندسی برق و کامپیوتر - دانشگاه صنعتی جندی شاپور

چکیده

در این مقاله حل مسئله پیش‌بینی ناپایداری گذرا پس از یک اغتشاش با استفاده از سیستم اندازه‌گیری ناحیه گسترده مدنظر است. در طرح ارائه‌شده، ابتدا با استفاده از اندازه فازورهای ولتاژ دریافتی از سوی واحدهای اندازه‌گیری فازور، لحظه وقوع اغتشاش تشخیص داده می‌شود. در مرحله دوم، مبتنی بر داده‌های ارسال‌شده پس از وقوع اغتشاش شامل اندازه فازور ولتاژ، فرکانس و مشتق فرکانس، تصمیم اولیه در خصوص وضعیت پایداری گذرا توسط سه طبقه‌بندی‌کننده از قبل آموزش داده‌شده ماشین بردار پشتیبان به‌صورت مجزا صورت می‌پذیرد. در پایان، سه تصمیم اولیه با استفاده از روش بیز، ترکیب و تصمیم نهایی در خصوص وضعیت پایداری گذرا اعلام می‌گردد. طرح مذکور بر روی شبکه استاندارد 39 باسه IEEE پیاده‌سازی شده است. نتایج نشان می‌دهند الگوریتم پیشنهادی قادر به پیش‌بینی ناپایداری گذرا در مدت زمان کمتر از سه سیکل پس از وقوع اغتشاش و با دقت قابل‌قبول در شرایط حضور و عدم حضور نویز در داده‌های واحدهای اندازه‌گیری فازور است.

کلیدواژه‌ها


عنوان مقاله [English]

Intelligent Post-Disturbance Transient Instability Prediction using Wide Area Measurement System

نویسندگان [English]

  • S. Afshari
  • M. Sarlak
Faculty of Electrical and Computer Engineering, Jundi Shapur University of Technology, Dezful, Iran
چکیده [English]

In this paper, the solution of the post-disturbance transient instability prediction problem using the wide area system is considered. In the proposed scheme, at first, the disturbance initiation is detected based on the magnitudes of voltage phasors received from phasor measurement units (PMUs). In the second step, a primary assessment of the transient stability is made according to the post-disturbance magnitudes of voltage phasors, frequency, and differential frequency and by three trained support vector machines (SVMs) classifiers, separately. Finally, the outputs of the classifiers are combined employing the Naive Bayes (NB) algorithm to make the final decision. The proposed algorithm was implemented on the IEEE New England 39-bus system. According to the results obtained, proposed algorithm can predict the transient instability as early as three cycles after the disturbance initiation using noise-free and noisy PMU data.

کلیدواژه‌ها [English]

  • Phasor measurement units
  • wide area measurement system
  • transient instability
  • support vector machine
  • combination of classifiers
  • bayes method
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