## 4 Discussion  
The analysis of the literature in the field of PQ improvement using FCSs highlights the potential of fuzzy logic in solving complex problems of modern power systems, including frequency, voltage, reactive power, harmonic distortion, and voltage unbalance control issues. Next, we focus on relevant solutions to solve these issues and future directions. Frequency control is an essential aspect of modern power systems and is closely related to connecting distributed generation units to the grid, operating isolated microgrids, and interconnecting different areas of power systems. Isolated microgrids that contain fluctuating generation sources (such as PV, wind, and hydro) and energy storage systems (EESs) often experience frequency fluctuations. To address this issue, researchers have used fuzzy logic to control EESs and loads, as demonstrated in [68; 129; 141]. Simple multiple type-1 fuzzy controllers were applied in [129; 141]. Indeed, the authors of [141] use four FLCs to control the battery, dump load, load, and whole system, while [129] proposes two FLCs for active power and reactive power control, respectively. [PERSON] in [68] improved the proposed fuzzy-PID controller by tuning the PID parameters using a harmony search algorithm. These studies prove the effectiveness of FCSs through simulations by employing MATLAB [129; 141] and DlgSILENT PowerFactory [129]. Efficiency is demonstrated by comparisons with other literature solutions [141], including simple PID [68] and robust control [129]. The comparison with the other methods showed that the fuzzy approach does not give frequency ripples as the robust control [129], \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Reference** & **Description** & **Efficacy** & **Efficiency** \\ \hline
[63] & Frequency control using optimized type-2 fuzzy & Simulations & _Comparison with type-1 fuzzy and PI controller_ \\ \hline
[130] & LFC in power systems with wind-generation units using robust fuzzy controller & Simulations & _Development and comparison of a simple type-1 fuzzy controller with the proposed hybrid fuzzy controller_ \\ \hline
[64] & Online frequency regulation using fractional-order type-2 fuzzy & Simulations & _The proposed method vs. three methods_ \\ \hline
[135] & AFF controlled by hybrid (inverted error deviation) fuzzy controller for decrease in harmonics & Simulations and experiments & _Development of both fuzzy controllers (type-1 fuzzy and hybrid) and comparison with a classic PI controller_ \\ \hline
[136] & Frequency control in a microgrid with multiple types of distributed generation using hybrid type-2 fuzzy PI & Simulations & _The proposed method vs. conventional PI and classic type-1 fuzzy PI controller_ \\ \hline
[137] & Frequency deviations and flicker issues solved using a hybrid (genetic algorithm optimizer) FLC that controls the generators & Simulations & _Results obtained with the proposed method compared with the results obtained without control_ \\ \hline
[138] & SVC is controlled using fuzzy-PI and grey theory to improve voltage fluctuation issues & Simulations & _Comparison with the classic type-1 fuzzy and without the control system_ \\ \hline
[139] & D-STATCOM controlled by different topologies of FLC for decrease in THD & Simulations & _Comparison between PI-like fuzzy controller, PI gain scheduled fuzzy controller, and hybrid fuzzy-PI controller_ \\ \hline
[140] & Fuzzy load frequency control with auto-tuned membership functions and fuzzy control rules & Simulations & _Comparison with the classic PI controller and a hybrid fuzzy controller (FLC + particle swam optimization)_ \\ \hline
[55] & Direct adaptive fuzzy logic control for load frequency regulation in multi-area power system & Simulations & _The proposed method’s results compared with a classic PID and a type-2 fuzzy controller_ \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Relevant papers assessing and improving the efficiency of the proposed FLCs.