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Journals / Istanbul University Journal of Electrical and Electronics Engineering / 2004 / Cilt: 4 - Sayı: 1

Optimization the regulation parameters of a synchronous generator by using artificial neural networks (ANN)

Mukden UĞUR
Osman Nuri UÇAN
Didem ERDOĞAN
Neriman ŞERİFOĞLU
Pages
1113–1117
Publication Date
2022-10-18
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

By measuring and recording the regulator terminal voltage continuously, some regulator parameters has been determined which finally help in optimizing the system stability by using Artificial Neural Networks.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Disturbances in electrical power system cause imbalances in electromechanical and mechanical torque of all machines.
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Key Findings & Data:These imbalances result in oscillations between synchronous generators.
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Conclusion & Impact:By measuring and recording the regulator terminal voltage continuously, some regulator parameters has been determined which finally help in optimizing the system stability by using Artificial Neural Networks.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Disturbances in electrical power system cause imbalances in electromechanical and mechanical torque of all machines. These imbalances result in oscillations between synchronous generators. In order to damp these oscillations, the stability analysis has been performed on a one machine system by using some regulator gain coefficients, which should eventually improve the recovery time after a system failure. The boundaries of the coefficients are initially defined and only some coefficients among all the calculated parameters are selected for test purposes. By measuring and recording the regulator terminal voltage continuously, some regulator parameters has been determined which finally help in optimizing the system stability by using Artificial Neural Networks.

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Cite This Article

UĞUR, M., UÇAN, O. N., ERDOĞAN, D., ŞERİFOĞLU, N. (2022). Optimization the regulation parameters of a synchronous generator by using artificial neural networks (ANN). Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 4 - Sayı: 1, 1113–1117. https://ajindex.com/articles/543868

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References (8)

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