Abstract
An appropriate model of a solar photovoltaic (SPV) cell is essential for control, operation, and prediction of SPV systems. Simultaneously, it is equally vital for determining as accurately as possible the parameters of that model. There are currently single-diode (SD), double-diode (DD) and triple-diode (TD) SPV cell models needing to be determined for various applications. A simple and effective approach is proposed for determining the parameters of SPV cell models through voltage and current measurements; as well as the transformation of the estimation problem into the optimization problem. Then, stochastic fractal search (SFS) algorithms with the benefits of finding the global optimal solution in a few generations and avoiding getting stuck in locally optimal solutions are proposed to apply for the above one. The achievements are compared to those by other existing algorithms such as a particle swarm optimization (PSO) and Chaos PSO algorithms to validate the proposals.
| Original language | English |
|---|---|
| Pages (from-to) | 267-277 |
| Number of pages | 11 |
| Journal | GMSARN International Journal |
| Volume | 18 |
| Issue number | 2 |
| Publication status | Published - Jun 2024 |
Keywords
- algorithm
- Parameter estimation
- SPV cell models
- SPV cell parameters
- Stochastic fractal search
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Environmental Science (miscellaneous)
- Energy Engineering and Power Technology
- Management, Monitoring, Policy and Law
