Your browser doesn't support javascript.
loading
Adaptive RAO ensembled dichotomy technique for the accurate parameters extraction of solar PV system.
Ashwini Kumari, P; Basha, C H Hussaian; Fathima, Fini; Dhanamjayulu, C; Kotb, Hossam; ELrashidi, Ali.
Afiliación
  • Ashwini Kumari P; School of Electrical and Electronics Engineering, Reva University, Bangalore, India.
  • Basha CHH; NITTE Meenakshi Institute of Technology (Autonomous), Bengaluru, India.
  • Fathima F; Mar Baselios Christian College of Engineering & Technology, Kuttikkanam, Kerala, India.
  • Dhanamjayulu C; School of Electrical Engineering, Vellore Institute of Technology, Vellore, India. dhanamjayulu.c@vit.ac.in.
  • Kotb H; Department of Electrical Power and Machines, Faculty of Engineering, Alexandria University, Alexandria, 21544, Egypt.
  • ELrashidi A; Electrical Engineering Department, University of Business and Technology, Ar Rawdah, 23435, Jeddah, Saudi Arabia. a.elrashidi@ubt.edu.sa.
Sci Rep ; 14(1): 12920, 2024 Jun 05.
Article en En | MEDLINE | ID: mdl-38839866
ABSTRACT
The parameter extraction process for PV models poses a complex nonlinear and multi-model optimization challenge. Accurately estimating these parameters is crucial for optimizing the efficiency of PV systems. To address this, the paper introduces the Adaptive Rao Dichotomy Method (ARDM) which leverages the adaptive characteristics of the Rao algorithm and the Dichotomy Technique. ARDM is compared with the several recent optimization techniques, including the tuna swarm optimizer, African vulture's optimizer, and teaching-learning-based optimizer. Statistical analyses and experimental results demonstrate the ARDM's superior performance in the parameter extraction for the various PV models, such as RTC France and PWP 201 polycrystalline, utilizing manufacturer-provided datasheets. Comparisons with competing techniques further underscore ARDM dominance. Simulation results highlight ARDM quick processing time, steady convergence, and consistently high accuracy in delivering optimal solutions.
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