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Showing 1 results for RANJBAR
Dr Soheil Ranjbar,
Volume 10, Issue 1 (3-2023)
Abstract
This paper presents a new online scheme of estimating power system transient voltage instability of interconnected synchronous generators using intelligent Bayesian theory based on wide area signals from WAMS data. For this purpose, by using online measurement of the system oscillatory signals gathered from WAMS technology and developing them as a series of input-output pairs data, the system dynamic category (stable/unstable) are achieved and used for Bayesian training. The proposed scheme is an online non-model-based technique with the ability of estimating binary decisions among the power system dynamic signals. In the case of evaluating effectiveness of the developed algorithm, by using an IEEE 39 test system, different fault events with the potential of transient voltage instabilities are investigated. In this case, considering two sampling data at pre-fault and post-fault occurrence moments, the system dynamic statues are estimated. Results present ability of the proposed scheme for fast and secure estimations of the system transient voltage instability.
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| نشریه سامانههای غیرخطی در مهندسی برق در خصوص اصول اخلاقی انتشار مقاله، از توصیههای «کمیته بینالمللی اخلاق نشر» موسوم به COPE و «منشور و موازین اخلاق پژوهش» مصوب معاونت پژوهش و فناوری وزارت علوم، تحقیقات و فناوری تبعیت میکند. |
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