Load Margin Assessment of Power Systems Using Artificial Neural Network and Genetic Algorithms

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Author(s):	Bento, Murilo E. C. Total Authors: 1
Document type:	Journal article
Source:	IFAC PAPERSONLINE; v. 55, n. 1, p. 5-pg., 2022-01-01.
Abstract
The power system load margin is an index that provides information on how far the system is from a case of instability. Usually, this load margin is calculated considering voltage stability requirements but low frequency oscillation modes with low damping rates, a field of study in small-signal stability, can also compromise the proper operation of power systems and so should be considered in calculating the load margin. This paper proposes a method based on artificial neural networks (ANN) using synchronized data provided by Phasor Measurement Units to monitor the load margin of systems meeting voltage stability and small-signal stability requirements. Furthermore, a Genetic Algorithm-based approach is used to select a reduced number of buses for the ANN input layer. Results of applications of the proposed method show the applicability for real-time monitoring of the load margin. Copyright (c) 2022. The Authors. This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). (AU)

FAPESP's process:	15/24245-8 - Fast Method for Dynamic Security Analysis of Power System Considering Small-Signal and Voltage Stability
Grantee:	Murilo Eduardo Casteroba Bento
Support Opportunities:	Scholarships in Brazil - Doctorate