Parameter extraction of solar cells using particle swarm optimization

✍ Scribed by Ye, Meiying; Wang, Xiaodong; Xu, Yousheng

• Book ID: 121716308
• Publisher: American Institute of Physics
• Year: 2009
• Tongue: English
• Weight: 476 KB
• Volume: 105
• Category: Article
• ISSN: 0021-8979
• DOI: 10.1063/1.3122082

✦ Synopsis

In this article, particle swarm optimization (PSO) was applied to extract the solar cell parameters from illuminated current-voltage characteristics. The performance of the PSO was compared with the genetic algorithms (GAs) for the single and double diode models. Based on synthetic and experimental current-voltage data, it has been confirmed that the proposed method can obtain higher parameter precision with better computational efficiency than the GA method. Compared with conventional gradient-based methods, even without a good initial guess, the PSO method can obtain the parameters of solar cells as close as possible to the practical parameters only based on a broad range specified for each of the parameters.