Flower pollination based solar PV parameter extraction for double diode model

J. Prasanth Ram, Dhanup S. Pillai, N. Rajasekar*, V. Kumar Chinnaiyan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

Abstract

Due to the environmental threat toward pollution and continuous depletion in fossil fuels, the world has found its alternate source of energy generation through pollution-free solar energy. Due to the scope in solar PV systems, the research interest has considerably increased. In solar PV research thrusts, the accurate modeling of solar I-V characteristics is given prior importance. In this article, the authors have proposed a new FPA-based solar PV parameter extraction. To appreciate the accuracy in the computation, two diode models are preferred. The authors have used RTC France data to experiment with the effectiveness of FPA. Further, the computed root mean square error and relative error for the designed model is compared with the existing Simulated Annealing (SA), Pattern Search (PS), Harmony Search (HS), and Artificial Bee Swarm Optimization (ABSO) techniques.

Original languageEnglish
Title of host publicationIntelligent Computing Techniques for Smart Energy Systems - Proceedings of ICTSES 2018
EditorsAkhtar Kalam, Khaleequr Rehman Niazi, Amit Soni, Shahbaz Ahmed Siddiqui, Ankit Mundra
PublisherSpringer
Pages303-312
Number of pages10
ISBN (Print)9789811502132
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event1st International conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2018 - Jaipur, India
Duration: 22 Dec 201823 Dec 2018

Publication series

NameLecture Notes in Electrical Engineering
Volume607
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference1st International conference on Intelligent Computing Techniques for Smart Energy Systems, ICTSES 2018
Country/TerritoryIndia
CityJaipur
Period22/12/1823/12/18

Keywords

  • Artificial bee swarm optimization
  • Flower pollination algorithm
  • Harmony search
  • Pattern search
  • Photovoltaic

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