A Hybrid Artificial Ecosystem Optimizer and Incremental-Conductance Maximum-Power-Point-Tracking-Controlled Grid-Connected Photovoltaic System

Abstract

When tracking the peak power point in PV systems, incremental conductance is the most common technique used. This approach preserves the first trap in the local peak power point, but it is unable to quickly keep up with the ever-changing peak power point under varying irradiance and temperature conditions. In this paper, the authors propose a hybrid algorithm, combining an artificial ecosystem optimizer and an incremental-conductance-based MPPT to solve these issues of traditional MPPT under varying irradiance and temperature conditions. The proposed hybrid algorithm has been applied to three scenarios, namely the constant irradiance condition, the varying irradiance condition, and the varying temperature condition. Under the constant irradiance condition, the PV array is maintained at a temperature of 25 °C and an irradiance of 1000 W/m2. The voltage of the DC link of the neutral-pointed-clamped inverter is maintained at 1000 V. Under the varying irradiance condition, the irradiance of the PV array is increased from 400 W/m2 to 1000 W/m2with a step size of 0.2 s. The same step size is maintained while decreasing the irradiance level from 1000 W/m2 to 400 W/m2, with a step change of 0.2 s. However, the temperature is maintained at 25 °C. Under the varying temperature condition, the temperature of the PV array varies from 35 °C, 25 °C, 15 °C, 10 °C, 15 °C, 25 °C, and 35 °C with a step size of 0.2 s, and the irradiance is maintained at 1000 W/m2. The DC link voltage in all three conditions is maintained at 1000 V, which confirms that the hybrid algorithm has been able to vary the duty cycle of the pulse wave modulation generator in such a manner that the variable DC voltage produced by the PV array has been changed by the flyback converter into a stable DC voltage. The simulation results show that the total harmonic distortion (THD) under all the simulated scenarios is within 5%, which agrees with IEEE standards. In the future, this algorithm may be compared with other types of available MPPTs under partial shading.

Improving Power Quality in Grid-Connected Photovoltaic Systems: A Comparative Analysis of Model Predictive Control in Three-Level and Two-Level Inverters

“…The IC-MPPT algorithm is based on the concept of utilising the incremental conductance of the PV panel to determine the slope of the power curve. By ensuring that the incremental conductance matches its instantaneous value, the MPPT algorithm effectively tracks the maximum power point [ 24 , 25 ]. Figure 9 provides a visual representation of the flowchart for the IC-MPPT algorithm.…”

Maximum Power Point Tracking of Photovoltaic Generation System Using Improved Quantum-Behavior Particle Swarm Optimization

“…To date, several MPPT methodologies have been proposed, such as the perturb and observe (P and O) technique [8][9][10], the hill climbing approach [11,12], and the incremental conductance method [13,14], among others. Despite their simple calculations, these methods may fail to accurately reach the MPP and achieve a balance between tracking speed and steady-state oscillation.…”