A sport inspired kabaddi game optimizer for accurate parameter estimation of solar photovoltaic models
Abstract
This paper proposes a Kabaddi Game Optimizer (KGO), a sport-inspired metaheuristic for accurate solar photovoltaic (PV) modelling. KGO models Kabaddi strategies (Dubki and Akraman), adaptive weights and weak-player replacement to balance exploration and exploitation. Its performance is first validated on the CEC 2017 benchmark set against seven well-known optimizers, where KGO consistently attains the best average rank. KGO is then coupled with the Newton–Raphson method to estimate parameters of single, double, and triple diode PV models and a PWP-201 PV module. Using RTC France cell and module data, KGO achieves RMSE values of 7.729857E−04, 7.43146E−04, 7.3771E−04, and 2.0529E−03 for the single-, double-, and triple-diode models, and the PV module, respectively, demonstrating accurate, robust, and fast PV parameter estimation.
Fields of Study & Subjects
Photovoltaic System Optimization Techniques
Solar Radiation and Photovoltaics
Solar Thermal and Photovoltaic Systems
Publication details
- Journal / source
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Volume
- 16
- Issue
- 1
- Pages
- 2677–2677
- Publication date
- 21 January 2026
- Language
- EN