A Novel Hybrid Approach Based on Analytical and Metaheuristic Algorithms for Parameters and Dynamic Resistance Estimation of a PV Array

Abstract

Accurate parameters of photovoltaic (PV) arrays are essential for the modeling, analysis, and control of PV systems. Due to the lack of complete datasheets from manufacturers, different techniques have been introduced to extract the unknown parameters of PV modules. A novel approach based on one of the most recent metaheuristic (MH) optimization algorithms, the Flow Direction Algorithm, is developed in this paper to estimate the PV-modules parameters accurately. The proposed approach extracts the parameters for single-, double-, and three-diode models under different operating conditions. Comparative studies with state-of-the-art MH algorithms showed that the proposed approach is more accurate and robust and reduces the computational burden. Furthermore, a general formula is derived to obtain the dynamic resistance of different PV models. It is shown in this paper that inaccurate PV model parameters might negatively impact the steady-state and dynamic performance assessment of grid-connected PV systems under different operating conditions. Detailed time-domain simulations are presented to validate the analytical results and show the effectiveness of the proposed approach.