Repository logo
Communities & Collections
All of DSpace
  • English
  • العربية
  • বাংলা
  • Català
  • Čeština
  • Deutsch
  • Ελληνικά
  • Español
  • Suomi
  • Français
  • Gàidhlig
  • हिंदी
  • Magyar
  • Italiano
  • Қазақ
  • Latviešu
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Српски
  • Svenska
  • Türkçe
  • Yкраї́нська
  • Tiếng Việt
Log In
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Sanseverinatti, Carlos I."

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Results Per Page
  • Sort Options
  • Thumbnail Image
    Item
    Protection location in distribution networks using particle swarm optimization
    (VII ARGENCON, 2024-09-20) Loyarte, Ariel S.; Manassero, Ulises; Sanseverinatti, Carlos I.; Rossi, Lautaro D.
    Circuit breakers in radial topology distribution networks protect the system against short circuits. In addition, other switching devices are usually used to reconfigure the network in post-fault scenarios, thus reducing the number of affected users. This strategy is intended to reduce the loss of profits for the distribution company, as well as the economic penalties it must face due to the energy not supplied (ENS) under these conditions. This work proposes the implementation of a particle swarm optimization algorithm (PSO) to determine the best location of new protection circuit breakers to be incorporated in the system, in order to minimize the total annual ENS, without violating usual operational constraints. For this purpose, it is combined with other procedures designed to simulate faults on a mathematical model of the network, determine the operating protection and the best possible reconfiguration. The applications are tested on a network in the province of Santa Fe (Argentina), from which it is shown that an inadequate location of the new protections may result in counterproductive situations in terms of the obtained ENS. On the other hand, the tests show that the developed methodology converges to the optimal solution with substantially lower computation times than those demanded by other evaluated alternatives, such as direct search solutions and Monte Carlo simulations. To improve the performance of the PSO, it is combined with a clustering technique that divides the solution space into smaller subdomains, thus enabling a more effective exploration by the algorithm.

 

UTN | Rectorado

Sarmiento 440

(C1041AAJ)

Buenos Aires, Argentina

+54 11 5371 5600

SECRETARÍAS
  • Académica
  • Administrativa
  • Asuntos Estudiantiles
  • Ciencia y Tecnología
  • Consejo Superior
  • Coordinación Universitaria
  • Cultura y Extensión Universitaria
  • Igualdad de género y Diversidad
  • Planeamiento Académico y Posgrado
  • Políticas Institucionales
  • Relaciones Internacionales
  • TIC
  • Vinculación Tecnológica
  • Comité de Seguridad de la Información
ENLACES UTN
  • DASUTeN
  • eDUTecNe
  • APUTN
  • ADUT
  • FAGDUT
  • FUT
  • SIDUT
ENLACES EXTERNOS
  • Secretaría de Educación
  • CIN
  • CONFEDI
  • CONEAU
  • Universidades