Field Current Waveform-Based Method for Estimation of Synchronous Generator Parameters Using Adaptive Black Widow Optimization Algorithm

• Published in: IEEE access Vol. 8; pp. 207537 - 207550
• Main Authors: Micev, Mihailo, Calasan, Martin, Petrovic, Dragan S., Ali, Ziad M., Quynh, Nguyen Vu, Abdel Aleem, Shady H. E.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive algorithms; Black widow optimization algorithm; Circuits; Current measurement; Estimation; field current waveform; Generators; Graphical methods; Heuristic methods; Hydroelectric plants; Hydroelectric power; Optimization; Optimization algorithms; Optimization techniques; Parameter estimation; Parameter identification; Shock absorbers; Short circuit testing; synchronous generator; Synchronous generators; Waveforms; Windings
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.3037510

This article presents a novel method for identification of synchronous generator parameters that is based on sudden short-circuit test data and a novel metaheuristic algorithm, called the adaptive black widow optimization algorithm. Unlike traditional methods defined by IEEE and International Electrotechnical Commission (IEC) standards, which rely on the armature current oscillogram, the method proposed in this article uses the field current waveform during the short-circuit test. Moreover, the standard graphical method for extraction of the generator parameters is replaced by an effective metaheuristic algorithm. The proposed algorithm tends to minimize the normalized sum of squared errors (NSSE) between simulation and experimental results. The applicability and accuracy of the proposed optimization technique are verified using experimentally obtained results from a 100-MVA synchronous generator at the Bajina Basta hydropower plant.