Comprehensive and innovative method for dynamic phasor and frequency estimation

2015 ◽  
Author(s):  
Mohsen Tajdinian ◽  
Mehdi Zareian Jahromi ◽  
Mojtaba Jalalpour ◽  
Shahram Montaser Kouhsari
Keyword(s):  
Frequency Estimation ◽  
Innovative Method ◽  
Dynamic Phasor

scholarly journals An Extended Kalman Filter Approach for Accurate Instantaneous Dynamic Phasor Estimation

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 2918 ◽  
Author(s):  
Matilde de Apráiz ◽  
Ramón Diego ◽  
Julio Barros
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Extended Kalman Filter ◽  
Phase Angle ◽  
Frequency Estimation ◽  
Dynamic Compliance ◽  
Phasor Estimation ◽  
Filter Approach ◽  
Harmonic Components ◽  
Dynamic Phasor

This paper proposes the application of a non-linear Extended Kalman Filter (EKF) for accurate instantaneous dynamic phasor estimation. An EKF-based algorithm is proposed to better adapt to the dynamic measurement requirements and to provide real-time tracking of the fundamental harmonic components and power system frequencies. This method is evaluated using dynamic compliance tests defined in the IEEE C37.118.1-2011 synchrophasor measurement standard, providing promising results in phasor and frequency estimation, compliant with the accuracy required in the case of off-nominal frequency, amplitude and phase angle modulations, frequency ramps, and step changes in magnitude and phase angle. An important additional feature of the method is its capability for real-time detection of transient disturbances in voltage or current waveforms using the residual of the filter, which enables flagging of the estimation for suitable processing.

REALIZATION OF IDEAS OF ARTIFICIAL INTELLIGENCE FOR THE FINDING OF HIERARCHY OF MOTIVES OF TRAINING

2018 ◽  
pp. 12-19
Author(s):  
M. G. Koliada ◽  
T. I. Bugayova
Keyword(s):  
Artificial Intelligence ◽  
Hierarchical System ◽  
Productive Activity ◽  
Large Role ◽  
Educational Work ◽  
Intelligent Search ◽  
Dynamic Mechanisms ◽  
Innovative Method ◽  
Effectiveness Of Training ◽  
Probabilistic Nature

The hierarchy of learning motives plays an extremely important role for a management of productive activity of learners, their activity and purposefulness. In the process of educational work, such a motivational hierarchy is formed, where some motives are dynamic mechanisms of other motives that are very difficult to identify at the intuitive level, especially considering the influence of each of them. Therefore, to determine the most significant hierarchical sequence of motives, an innovative method was proposed which is based on the ideas of artificial intelligence. As an example, the search was implemented based on the so-called algorithm of imitation roasting, which is capable to take into account the probabilistic nature of motivational indicators. The article highlights the main leading educational motives of students, on the basis of which the “mechanism” of finding their optimal hierarchical system is shown, and one that simultaneously takes into account the multifactorial influence of their driving causes, taking into account their interconnection, interaction and dynamism. A step-by-step realization of construction of such a hierarchical system of main educational motives in combination with casual, minor motives which are difficult for expecting or providing in advance is shown. Given their unpredictability and probabilistic nature of occurrence, the proposed system of intelligent search allows you to select exactly those sequences of motives that provide the highest productivity and effectiveness of training. The value of the proposed algorithm of imitation roasting is that the accuracy of the result is sacrificed, but the number of iteration cycles decreases, which plays a large role in processing a significant number of motivational indicators.

Off-Grid Frequency Estimation with Random Measurements

2017 ◽  
Vol E100.A (11) ◽  
pp. 2493-2497
Author(s):  
Xushan CHEN ◽  
Jibin YANG ◽  
Meng SUN ◽  
Jianfeng LI
Keyword(s):  
Frequency Estimation ◽  
Random Measurements

Improvement of Jain’s algorithm for frequency estimation

2020 ◽  
Vol 65 (1) ◽  
pp. 115-122
Author(s):  
Andrea Amalia Minda
Keyword(s):  
Frequency Estimation ◽  
The Real ◽  
Real Frequency

In this paper we propose a procedure to correct Jain's algorithm, which in certain situations fails in correctly estimating the frequency by indicating frequency values that are very far from the real frequency. It happens because the two points considered for the method proposed by Jain are not on the same lobe. Thus, a method is proposed according to which these points are chosen so that the results are improved.

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