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.

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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.

In this work, an Adaptive Fuzzy Logic Controller is studied to optimize the transfer of the power provided by a photovoltaic generator. The adaptation process is carried out online in two tasks: the adaptation of the rules consequences and the self-organization of the internal structure of the Fuzzy Controller. In comparison with two types of traditional controls, the performance of the controller studied is validated. The simulation results show that the controller studied makes it possible to reduce the response time by 3 % compared to the conventional controller, and minimizes the steady-state error by eliminating the phenomenon of oscillation around the PPM and that the proposed controller exhibits good behavior with a wide range of power.