Your browser doesn't support javascript.
loading
Multiobjective optimal TCSC placement using multiobjective grey wolf optimizer for power losses reduction.
Rao, Nartu Tejeswara; Kumar, Kalyana Kiran; Kumar, Polamarasetty P; Nuvvula, Ramakrishna S S; Mutharasan, A; Dhanamjayulu, C; Shaik, Mohammed Rafi; Khan, Baseem.
Afiliación
  • Rao NT; Department of Electrical and Electronics Engineering, Aditya Institute of Technology and Management, Tekkali, India.
  • Kumar KK; Department of Electrical and Electronics Engineering, Aditya Institute of Technology and Management, Tekkali, India.
  • Kumar PP; Department of Electrical and Electronics Engineering, GMR Institute of Technology, Rajam, India.
  • Nuvvula RSS; Department of Electrical and Electronics Engineering, NMAM Institute of Technology, NITTE (Deemed to Be University), Karnataka, 574110, India. ssramanuvvula@gmail.com.
  • Mutharasan A; Department of Electronics and Communication Engineering, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, Chennai, India.
  • Dhanamjayulu C; School of Electrical Engineering, Vellore Institute of Technology, Vellore, India. dhanamjayuluc6947@gmail.com.
  • Shaik MR; Department of Chemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia.
  • Khan B; Department of Electrical and Computer Engineering, Hawassa University, Hawassa, Ethiopia, 05. baseemkh@hu.edu.et.
Sci Rep ; 14(1): 21857, 2024 Sep 19.
Article en En | MEDLINE | ID: mdl-39300234
ABSTRACT
This study investigates the application of the multiobjective grey wolf optimizer (MOGWO) for optimal placement of thyristor-controlled series compensator (TCSC) to minimize power loss in power systems. Two conflicting objectives are considered (1) minimizing real and reactive power loss, and (2) minimizing real power loss and TCSC capital cost. The Pareto-optimal method is employed to generate the Pareto front for these objectives. The fuzzy set technique is used to identify the optimal trade-off solution, while the technique for order preference by similarity to the ideal solution suggests multiple optimal solutions catering to diverse utility preferences. Simulations on an IEEE 30 bus test system demonstrate the effectiveness of TCSC placement for power loss minimization using MOGWO. The superiority of MOGWO is confirmed by comparing its results with those obtained from a multiobjective particle swarm optimization algorithm. These findings can assist power system utilities in identifying optimal TCSC locations to maximize their performance.
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: India Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: India Pais de publicación: Reino Unido