Opposite Normalized Trust-Region Reflective (ONTRR): A New Algorithm for Parameter Extraction of Single, Double and Triple Diode Solar Cell Models

• Published in: Applied sciences Vol. 13; no. 14; p. 8199
• Main Authors: Gao, Xiankun, Hou, Qingwen, Yao, Sen, Zhou, Kaiyuan
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.07.2023
• Subjects: Algorithms; Analysis; Diodes; Methods; min-max normalization; opposition-based learning; parameter extraction; Photovoltaic cells; solar cell model; trust-region reflective

To accurately, efficiently and reliably extract the parameters of single, double and triple diode solar cell models, this paper proposes a randomly initialized opposite normalized trust-region reflective (ONTRR) algorithm. The novelty of ONTRR lies primarily in two amendments to the standard TRR sea...