The aim of this research is to manage the voltage of an active distribution grid with a low X/R ratio and multiple Photovoltaic Distributed Generators (PVDGs) operating under varying conditions. This is achieved by providing a methodology for coordinating three voltage-based controllers implementing an Adaptive Neuro-Fuzzy Inference System (ANFIS). The first controller is for the On-Line Tap Changer (OLTC), which computes its adequate voltage reference. Whereas the second determines the required Active Power Curtailment (APC) setpoint for PVDG units with the aim of regulating the voltage magnitude and preventing continuous tap operation (the hunting problem) of OLTC. Finally, the last component is an auxiliary controller designed for reactive power adjustment. Its function is to manage voltage at the Common Coupling Point (CCP) within the network. This regulation not only aids in preventing undue stress on the OLTC but also contributes to a modest reduction in active power generated by PVDGs. The algorithm coordinating between these three controllers is simulated in MATLAB/SIMULINK and tested on a modified IEEE 33-bus power distribution grid (PDG). The results revealed the efficacy of the adopted algorithm in regulating voltage magnitudes in all buses compared to the traditional control method.

This research presents a new voltage regulation philosophy that enhances the voltage magnitude in a power distribution network where distributed generation (DG) is prevalent. Voltage regulation in power distribution networks relies heavily on the On-Load Tap-Changer (OLTC) installed in power transformers. Since it was designed for networks without DG, the OLTC's current voltage regulation scheme uses a fixed reference voltage and hence cannot regulate voltage in a distribution network. Therefore, the proposed novel system-based Fuzzy logic will compute a new set point voltage that the OLTC must follow to mitigate the undesirable DG impact on the voltage profile. The suggested system is evaluated on Morocco's MATLAB/Simulink-built 20kV distribution network.

Voltage control scheme to enhance the stability for current distribution networks connecting with distributed generation (DG). The increasing demand of energy in recent years transformed traditional distribution grids, which have unidirectional power flow to Active Distribution Networks (ADN), including significant penetration of renewable distributed generators (DGs), such as photovoltaic (PV) modules where the power flow became bidirectional due to the high excess DGs active power that reverses to the power grid. Therefore, this ADN comes with a significant challenge, which is voltage regulation problem. To interconnect PV Generators into distribution systems a robust control approach needs to be adopted, there are different Voltage control scheme can be carried out in variety of methods, such as control by using On Load Tap changers (OLTC), using PV inverters reactive power injection/absorption, real power curtailment process, storage batteries and more. This article proposed a reactive power compensation by PV inverters based on fuzzy logic for voltage control along with the feeders. The control approach was tested and simulated, and it was observed that it can guarantee of maintaining the voltage profile of the distribution network within acceptable range. The MATLAB and Simulink platforms are used to model the system.

The increasing integration of renewable energy sources (RES) is accelerating the shift from traditional synchronous machine-based power systems to inverter-dominated grids. This transition poses significant frequency stability challenges, as power electronic interfaces lack the inherent kinetic energy storage of conventional generators, resulting in low system inertia. To address these challenges, this study proposes an adaptive virtual inertia control system based on fuzzy logic, which offers notable advancements in frequency dynamics. The proposed controller dynamically adjusts the virtual inertia constant in real-time by leveraging inputs such as frequency and the rate of change of frequency (RoCoF). This adaptive approach overcomes the limitations of fixed inertia systems, ensuring improved frequency stability and superior transient performance during load disturbances. Simulation results validate the system's effectiveness, showing reduced frequency overshoots, minimized deviations, and faster recovery to nominal frequency compared to conventional fixed inertia methods. By rapidly damping oscillations and enhancing transient stability, the proposed system significantly outperforms traditional techniques. Moreover, the study reviews current virtual inertia strategies, control topologies, and explores future research directions for integrating advanced virtual inertia into modern grids. These findings demonstrate the robustness of fuzzy logic based adaptive inertia for stabilizing low-inertia microgrids with high RES penetration.