Parameter extraction of solar photovoltaic cells and modules using current–voltage characteristics

ABSTRACT

The significance of bio-inspired evolutionary algorithms has attracted many applications for obtaining best solutions to their optimisation problems in the past decades. This paper is about the application of one of these algorithms, namely, quantum particle swarm optimisation algorithm for parameter extraction of solar photovoltaic cells using current–voltage (I–V) characteristics. This algorithm has been used here to extract five parameters, namely, photocurrent, saturation current, series resistance, shunt resistance and ideality factor that influence the I–V relationship of single diode model solar photovoltaic cells. This approach has been validated for a cell and a module. Simulations using Matlab software have shown that the simulated I–V characteristics obtained using the extracted parameters have good agreement with the experimental I–V values. The reason for the interest taken in undertaking this work is to suggest a good and an accurate simulator for solar system designers.

KEYWORDS:

• Solar photovoltaic cells
• parameter extraction
• evolutionary algorithms

Disclosure statement

No potential conflict of interest was reported by the authors.