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Online Estimation of the Wide Area Voltage Transient Instability Using Bayesian Technique Based on WAMS Data
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SOHEIL RANJBAR *   |
| Velayat University , s.ranjbar@velayat.ac.ir |
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Abstract: (681 Views) |
| 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. |
Article number: 5 |
| Keywords: Transient Voltage Instability, Estimation, Data Mining, Bayesian Theory. |
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Full-Text [PDF 9655 kb]
(282 Downloads)
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Type of Study: Research |
Subject:
Electrical Power Systems (Operation, Control, Analysis, ...)
Received: 2022/12/19 | Accepted: 2023/08/15 | Published: 2023/12/12
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