Parameter Estimation of a Single-Diode PV Model Using a Hybrid Charged System Search Algorithm

Abstract

The single-diode equivalent circuit is the most commonly used physical model for estimating photovoltaic (PV) power output. There are five parameters such as the generated photocurrent, the diode ideality, the reverse saturation current, the series resistance and the shunt resistance in the single-diode model that affect PV power output. Theses parameters recommended by the manufacturer have a nonlinear relationship with power output and may vary as facilities age after running for a few years. Parameters for PV modules must be estimated to ensure accurate simulation in a micro-grid system. To allow finer and more accurate estimation for PV power output, the five parameters of the single-diode model are transformed into 13 parameters under various weather conditions. A hybrid charged system search (HCSS) algorithm is then used to estimate the parameter settings for PV modules using actual measurement data. The proposed method is applied to a 32 kWp PV power generation system and the results show that the proposed method determines the optimal parameter settings for PV modules that allow accurate simulation and implementation for a micro-grid system.