LOW VOLTAGE RIDE THROUGH CAPABILITY IMPROVEMENT OF GRID-CONNECTED PHOTOVOLTAIC POWER PLANTS

Abstract

Among the world of renewable energy sources, solar energy is growing powerfully and robustly. There are many advantages for the photovoltaic (PV) systems including small installation time, easy circuitry, long life of operation, and low maintenance requirements. The solar power plants are connected to the electric grid on large scale. PV systems prices were continuously decreasing during the last decade.

It is essential to model the PV module to use it in the PV system simulation process, this model plays an important role through the dynamic analysis of these systems and helps to predict their behavior under different operating conditions. The mathematical model of the PV module is a nonlinear I-V characteristic including several unknown parameters as the PV manufacturers’ data are not sufficient. The equivalent circuit models used to describe the non-linear I-V relationship are: single, double and three diode models. The three models are introduced to achieve higher level of accuracy. The parameter extraction problem of the three different models is formulated as a search optimization problem. The fitness function is evaluated by minimizing the Root-Mean-Square error between calculated current and measured current experimental data through adjusting parameters of the PV models. This optimization is executed through a new nature-inspired meta-heuristic optimization technique known as the Whale Optimization Algorithm (WOA).