A Deep Neural Network as a Strategy for Optimal Sizing and Location of Reactive Compensation Considering Power Consumption Uncertainties

A Deep Neural Network as a Strategy for Optimal Sizing and Location of Reactive Compensation Considering Power Consumption Uncertainties

This research proposes a methodology for the optimal location and sizing of reactive compensation in an electrical transmission system through a deep neural network (DNN) by considering the smallest cost for compensation. An electrical power system (EPS) is subjected to unexpected increases in loads...

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Bibliographic Details
Main Authors: Manuel Jaramillo, Diego Carrión, Jorge Muñoz
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Energies
Subjects:
multi-layer neural network
reactive compensation
electrical power system
deep learning
optimal location
optimal sizing
Online Access:https://www.mdpi.com/1996-1073/15/24/9367

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