Bibliographic citations
Ataupillco, Á., (2019). Aplicación de algoritmos genéticos para la reconfiguración de redes de distribución eléctrica para la minimización de pérdidas de potencia activa [Tesis, Universidad Nacional de Ingeniería]. http://hdl.handle.net/20.500.14076/18463
Ataupillco, Á., Aplicación de algoritmos genéticos para la reconfiguración de redes de distribución eléctrica para la minimización de pérdidas de potencia activa [Tesis]. PE: Universidad Nacional de Ingeniería; 2019. http://hdl.handle.net/20.500.14076/18463
@misc{renati/710356,
title = "Aplicación de algoritmos genéticos para la reconfiguración de redes de distribución eléctrica para la minimización de pérdidas de potencia activa",
author = "Ataupillco Maldonado, Ángeles",
publisher = "Universidad Nacional de Ingeniería",
year = "2019"
}
The efficient operation of electrical systems is currently an issue on which companies that manage and operate them are focused to achieve quality standards hand in hand with sustainable development, generating benefits for all the actors involved. So, part of this approach is the reduction of losses that occur in the distribution power grids and one of the ways to achieve this goal is the reconfiguration of the radial topology of these systems that lead them to optimal topologies for this purpose, complying with restrictions and characteristics of radial networks. In the present work, the Genetic Algorithms (AG) method is used as an optimization tool on the topology of the primary electric distribution networks for the minimization of active power losses. The genetic algorithms will allow us to express the electrical equations in their complete form avoiding simplifications that distance the results of the absolute values; likewise, in a complementary way, Prim Algorithm will be addressed as a tool for the formation of radial topologies and also the Complex Direct Load Flow method which is developed for its application in distribution networks. The developed methodology will be applied on the test systems of 16, 33 and 84 - bus to verify the validity of the results and then on real systems from which additional conclusions will be obtained highlighting the benefits.
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