Improvement of maximum power point tracking (MPPT) efficiency using grey wolf optimization (GWO) algorithm in photovoltaic (PV) system

Abstract

Photovoltaics are becoming very popular, because the system does not produce pollution and can be installed anywhere, including in remote areas. However, in the use of photovoltaic found some common problems, it is difficult to get maximum and stable power. Therefore, to overcome these problems using Maximum Power Point Tracking method. On a photovoltaic system it is necessary to determine which converter will be used to increase the power output of the photovoltaic. The design of MPPT using gray wolf optimization algorithm that can track the output power quickly and reduce the oscillation in photovoltaic system. The result of the maximum power tracker using the gray wolf optimization algorithm is better than the incremental conductance algorithm of up to 0,4 s. Converters are used using soft - switching buck converter method to overcome the power losses that often arise in PV systems. The result of power output using soft-switching buck converter is greater than using buck converter. When comparing the efficiency of photovoltaic systems using the gray wolf optimization algorithm increases from using the incremental conductance algorithm.

Improved power quality based PVDG system using different optimised MPPT controllers

“…Modified Grey Wolf Optimization (MGWO) is an optimization algorithm inspired by the behavior of grey wolves when they are on the hunt for their food,which is shown in figure 8. These wolves commonly hunt their prey in three steps encircling the prey, hunting the prey, and attacking their prey [25]. Encircling: These wolves randomly encircle between the limits and dimensions of wolves and their positions during the hunting process are derived from equation (15) and equation (16).…”

HRES Integrated DSTATCOM Using High Gain Sepic-Zeta Based WOA Optimized ANFIS-MPPT Controller for PQ Issues

“…The THD waveform for the proposed system is demonstrated in Figure 19, which is examined that the developed technique attains 0.72% of THD value. GWO [24] 98% WOA [25] 98.82%…”

An Efficient Honey Badger Optimization Based Solar MPPT Under Partial Shading Conditions

“…For past decades, various swarm intelligence methods are implemented for tracking GMPP. Some of the popular SI methods in MPPT are particle swarm optimization (PSO) [7], artificial bee colony (ABC) algorithm [8], firefly algorithm (FA) [9], bat algorithm [10], Grey Wolf Optimization (GWO) algorithm [11] and so on. Because of the design simplicity and easy implementation, the SI based methods are applied mostly for GMPP tracking in PV systems.…”