Predictive Modeling of Total Real and Reactive Power Losses in Contingency Systems Using Function-Fitting Neural Networks with Graphical User Interface

Predictive Modeling of Total Real and Reactive Power Losses in Contingency Systems Using Function-Fitting Neural Networks with Graphical User Interface

Technical power losses in power systems are unavoidable, caused by factors such as transformer impedance, conductor resistance, equipment inefficiencies, line reactance, and phase imbalances. Reducing these losses is essential for improving system efficiency. This study introduces an innovative appr...

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Bibliographic Details
Main Authors: Alfredo Bonini Neto, Alexandre de Queiroz, Giovana Gonçalves da Silva, André Gifalli, André Nunes de Souza, Enio Garbelini
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Technologies
Subjects:
continuation method
artificial intelligence
technical power losses
estimation
loading margin
Online Access:https://www.mdpi.com/2227-7080/13/1/15
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