TELKOMNIKA Telecommunication, Computing, Electronics and Control
Performance assessment of an optimization strategy proposed for power systems
Dublin Core
Title
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Performance assessment of an optimization strategy proposed for power systems
Performance assessment of an optimization strategy proposed for power systems
Subject
Artificial neural network, Newton Raphson, Optimization, Power system
Description
In the present article, the selection process of the topology of an artificial neural network (ANN) as well as its configuration are exposed. The ANN was adapted to work with the Newton Raphson (NR) method for the calculation of power flow and voltage optimization in the PQ nodes of a 10-node power system represented by the IEEE 1250 standard system. The purpose is to assess and compare its results with the ones obtained by implementing ant colony and genetic algorithms in the optimization of the same system. As a result, it is stated that the voltages in all system nodes surpass 0,99 p.u., thus representing a 20% increase in the optimal scenario, where the algorithm took 30 seconds, of which 9 seconds were used in the training and validation processes of
the ANN.
the ANN.
Creator
Harold Puin, Cesar Hernandez
Source
DOI: 10.12928/TELKOMNIKA.v18i5.14396
Publisher
Universitas Ahmad Dahlan
Date
October 2020
Contributor
Sri Wahyuni
Rights
ISSN: 1693-6930
Relation
http://journal.uad.ac.id/index.php/TELKOMNIKA
Format
PDF
Language
English
Type
Text
Coverage
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Files
Collection
Citation
Harold Puin, Cesar Hernandez, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Performance assessment of an optimization strategy proposed for power systems,” Repository Horizon University Indonesia, accessed October 31, 2025, https://repository.horizon.ac.id/items/show/4068.
Performance assessment of an optimization strategy proposed for power systems,” Repository Horizon University Indonesia, accessed October 31, 2025, https://repository.horizon.ac.id/items/show/4068.