Enhanced Parameters Extraction Procedure of PV Module Using Electrical Fish Optimization

Abstract

Effective fault detection procedures are vital for maintaining the proper functioning of photovoltaic (PV) systems. To achieve this, employing a dependable model is a key step and a fundamental tool for monitoring and overseeing the system in question. In this study, the unknown parameters of the one diode model (ODM) in outdoor conditions are precisely determined using an enhanced methodology. The proposed approach integrates an innovative translation technique to adjust the I-V curves to standard reference conditions, along with analytical expressions to calculate the relevant parameters under varying irradiance and temperature conditions. For determining the five unknown parameters at standard test conditions, an optimization algorithm namely the electrical fish optimization (EFO) is used. Using the extracted parameters, the behavior of the maximum power point (MPP) was modeled and simulated in comparison to measurements from a real grid-connected MPP system. The obtain results demonstrate the effectiveness of the proposed strategy.