A Genetic Algorithm Approach for Identifying Synchronous Generator Parameters from Excitation Disturbance Test

Talebi, M. A.; Rahimpour, Mohammad Reza; Gholami, Alireza; Vahedi, A.; Shayanfar, Heidar Ali

doi:10.1109/pes.2007.385552

Cited by 6 publications

(2 citation statements)

References 16 publications

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“…There have been efforts to overcome the aforementioned limitations. In [14] it was proposed an improved online procedure based on a genetic algorithm for synchronous machine parameter estimation. Reference [15] proposed a complete modeling which takes into account the existence of dampers and use the least-squares algorithm to obtain the machine model reactances and time constants.…”

Section: Introductionmentioning

confidence: 99%

A Novel Prony Approach for Synchronous Generator Parameter Estimation

SANTANA¹

2015

ELECTROTECHNICAL REVIEW

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In this paper we propose to use a novel Prony's approach, relying on suitable time-segmentation of current oscillograms and proper model order choice, to estimate transient and sub-transient parameters of synchronous generators associated to sudden three-phase short-circuit tests. Comparison between the proposed approach and a traditional graphical method, described in the IEEE-115 standard, has been performed. The current data used here have been generated from characteristic equations of short-circuit armature current. Based on these results, we conclude that the Prony's algorithm is a suitable alternative to the graphical method for parameter estimation in synchronous machines, providing more accurate estimates than the later approach. Streszczenie. W artykule zaproponowano system, bazujący na algorytmie Prony, służący do analizy stanów przejściowych w generatorze synchronicznym poddanym testom trójfazowego zwarcia. Porównano tę metodę z tradycyjną metodą bazującą na normie IEEE-115. Algorytm wykorzystujący metodę Prony był bardzie dokładny. Nowa metoda bazująca na algorytmie Prony do określania parametrów generatora synchronicznego

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Section: Introductionmentioning

confidence: 99%

A Novel Prony Approach for Synchronous Generator Parameter Estimation

SANTANA¹

2015

ELECTROTECHNICAL REVIEW

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“…3) преобразование Хартли [13]; 4) метод наименьших квадратов [14][15][16][17][18][19]; 5) методы искусственного интеллекта [20][21][22][23][24][25][26][27][28][29][30][31]; 6) псевдослучайная двоичная последовательность [32,33]; 7) анализ переходных процессов при двухфазном КЗ [34] и пуске [35];…”

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Overview of Methods for Determining Parameters of Synchronous Generators

Бердин¹,

Мойсейченков²,

Коваленко³

et al. 2020

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A synchronous generator is one of the key elements of any power system, having a significant impact on the stability and reliability of consumers’ power supply. Nowadays, the power systems emergency and operational control issues are being solved using computational models, the parameters whereof are determined using the reference data, or the data obtained during testing. High dependence of the models’ parameters on various external factors leads to a significant decrease in the accuracy of solving the issues of emergency and operational control. Identification based on the traditional telemetry systems or synchrophasor measurements is used to improve the accuracy of parameters of the power systems’ computational models. The purpose of this research lies in a meta-analysis of the available studies aimed at developing a methodology for determining parameters of a synchronous generator on the basis of measurement data. Russian and foreign studies were analyzed and grouped to achieve this goal. After that, for each group, advantages, disadvantages, and the area of application were identified. As a result, it is shown that the existing methods for determining parameters of synchronous generators based on measurement data cannot adapt to the source dataset and also require significant computing power. As a way to overcome these shortcomings, an adaptive model of a synchronous machine is proposed.

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Intelligent power system stabilizer design using adaptive fuzzy sliding mode controller

Farahani

Ganjefar

2017

Neurocomputing

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A Genetic Algorithm Approach for Identifying Synchronous Generator Parameters from Excitation Disturbance Test

Cited by 6 publications

References 16 publications

A Novel Prony Approach for Synchronous Generator Parameter Estimation

A Novel Prony Approach for Synchronous Generator Parameter Estimation

Overview of Methods for Determining Parameters of Synchronous Generators

Intelligent power system stabilizer design using adaptive fuzzy sliding mode controller

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