# Power Quality Enhancement in a Grid-Integrated Photovoltaic System Using Hybrid Techniques
## 2 Literature Review  
[PERSON] et al. [11] demonstrated a variable P&O MPPT algorithm that was implemented to track the MPP during sudden changes in irradiance. This technique includes three algorithms, namely, the current perturbation algorithm, the adaptive control algorithm, and the variable perturbation algorithm. The variable perturbation algorithm dynamically decreases the perturbation size, which is completely based on the polarity of the change in power, but it requires a large data storage area and extensive computation.  
[PERSON] et al. [12] presented the MPPT technique, implemented using a hybrid dynamical technique to model the PV generator. The designed MPPT algorithm for optimization of the PV chain production is used to monitor the functionality of each power conductor device. The designed MPPT structure uses a multicellular converter instead of a classic DC/DC converter to overcome the properties of its specific topology. The design of the MPPT algorithm is completely suitable for multiple-cell structures, but the same procedure was not followed when designing the N-cell structure.  
[PERSON] [13] demonstrated an intelligent Bayesian network (BN) method used for MPP tracking of a PV array under partial shading conditions (PSCs). This method achieves efficient performance in terms of robustness, tracking efficiency, and speed, which was demonstrated through different simulated scenarios. In the proposed method, the PV array is desired to operate at any time period. In this proposed algorithm, the additional computational burden on the processor is added, whereas an enormous number of particles is required to cover the entire system.  
[PERSON] et al. [14] presented a fuzzy controller for tracking the MPP to improve the PQ features. This research developed an optimal MPPT technique that was tested under varying climatic conditions. This method can supply the maximum possible power to a battery in an off-grid PV system using a fuzzy controller. The proposed technique uses simpler hardware setup throughout, where only one voltage sensor is utilized. A closed-loop MPPT technique was developed based on a conventional PI controller, although the fuzzy controllers used in the method are very expensive.  
[PERSON] et al. [15] demonstrated a new MPPT technique that implements a PV system based on the PSO algorithm and the Lagrange interpolation formula. Here, the proposed PSO shows better results because of its simple implementation and capability to achieve MPP in various environmental circumstances. An optimum number of iterations is required to achieve the MPP, but it is difficult to detect the resulting power loss and convergence issues.  
Several works are reported in the literature, as this area has attracted considerable interest from the research community compared to other optimization techniques, because it is more robust and exhibits faster convergence. Furthermore, it requires fewer parameters for adjustment and fewer operators compared to other evolutionary approaches, which is an advantage when a rapid design process is considered. After a thorough literature survey, it was observed that the hybrid combination of BPSO-GWO has not been exploited for designing an MPPT. Hence, this work attempted to exploit the BPSO-GWO for designing an MPPT to obtain efficient tracking performance of a PV system under various conditions.