Parameter Estimation of Organic Photovoltaic Cells - A Three-Diode Approach Using Wind-Driven Optimization Algorithm

Derick Mathew, J. Prasanth Ram, Dhanup S. Pillai*, Young Jin Kim*, D. Elangovan, Antonino Laudani, Apel Mahmud

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Modeling a reliable electrical equivalent circuit to simulate the output I-V characteristics of organic solar PV (OPV) cells still prevails as a challenging task. This is because, estimating unknown parameters from the transcendental current equation determining the nonlinear OPV characteristics is extremely difficult. More importantly, predicting the parameters for dynamic changes in irradiation profile demands reliable optimization-based models. Therefore, this article proposes the application of adaptive wind-driven optimization (WDO) algorithm for a three-diode electrical equivalent model to estimate the OPV circuit parameters. Application of WDO algorithm has produced precise PV parameters to reproduce the exact I-V characteristics. In particular, the ability to replicate the kink effect in OPV characteristics is a noticeable improvement. Compared to its counterparts, various factors that enable WDO to enhance its compatibility towards nonlinear OPV modeling are: i) unique velocity update strategy via Coriolis and Gravitational forces, ii) excellent tradeoff between exploration and exploitation of control variables, iii) adaptive capability to maintain solutions within the search space even if the limits are breached, and iv) easiness in parameter tuning. For the validation, extensive testing has been conducted to reproduce the widely used characteristics of nav100 OPV cell at various operating conditions. Quantitatively, WDO method showcases excellent accuracy with an individual absolute error value in the order of 10-6 and convergence within the first 50 iterations itself, demonstrating its supremacy to solve OPV parameter identification problem.

Original languageEnglish
Pages (from-to)327-336
Number of pages10
JournalIEEE Journal of Photovoltaics
Volume12
Issue number1
Early online date13 Dec 2021
DOIs
Publication statusPublished - 1 Jan 2022
Externally publishedYes

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