One of the problems with the doubly-fed induction generator (DFIG) is its high vulnerability to network perturbations, notably voltage dips, because of its stator windings being coupled directly to the network. As the DFIG’s stator and rotor are electromagnetically mated, the stator current peak occurs during a voltage dip causing an inrush current to the critical converter back-to-back and an overload of the DC-link capacitor. For this purpose, a series of researchers have achieved a linear and non-linear controller with a crowbar-based protection scheme. With this type of protection, the Rotor Side Converter (RSC) is disconnected momentarily, and consequently, its control of both the active and reactive output power of the stator is totally lost, leading to incorrect power quality at the point of common coupling (PCC). In this document, a robust nonlinear controller by Advanced Backstepping with Integral Action Control (ABIAC) is initially employed to monitor the rotor and the network side converters under normal network operations. In the presence of a network fault, an improved protection scheme (IPS) is tacked on to the robust nonlinear control to help enforce the behavior of the DFIG system to be able to overcome the fault. The IPS, which is formed by a crowbar and an RL series circuit, is typically located in the space between the rotor coils and the RSC converter. Compared to a standard crowbar, the developed scheme is successful to limit the rotor transient current and DC-link voltage, also an RSC disengagement to rotor windings can be prevented during the fault. Furthermore, the controllers of both the RSC and the Network Side Converter (NSC) are modified to boost the supply voltage at the PCC. A comparative study is also performed between the IPS without and with modification of the reactive power control loops. The simulation results mean that with the modified controllers during the fault, the amount of reactive power sustainment with ABIAC at the PCC is optimized to 17.5 MVAr instead of 15 MVAr with proportional-integral control (PIC). Therefore, the voltage at the PCC is fort increased in order to comply with the voltage requirements of the farm and absolutely to maintain the connection to the network in case of voltage dip.

The present work consists of developing a new hybrid FL-INC optimization algorithm for the solar water pumping system (SWPS) through a SEPIC converter whose objective is to improve these performances. This technique is based on the combination of the fuzzy logic of artificial intelligence and the incremental conductance (INC) technique. Indeed, the introduction of fuzzy logic to the INC algorithm allows the extraction of a maximum amount of power and an improvement in the efficiency of the SWPS. The performance of the system through the SEPIC converter is compared with those of the direct coupling to show the interest of the indirect coupling, which requires an adaptation stage driven by an optimal control algorithm. In addition, a comparative analysis between the proposed hybrid algorithm and the conventional optimization techniques, namely, P&O and INC Modified (M-INC), was carried out to confirm improvements related to the SWPS in terms of efficiency, tracking speed, power quality, tracking of the maximum power point under different weather changes, and pumped water flow.

This paper investigates enhancing the efficiency of solar water pumping systems (SWPS) by implementing a Maximum Power Point Tracking technique based on the Bat Metaheuristic Optimizer (MPPT-bat) for the photovoltaic generator (PVG) side, coupled with Direct Torque Control (DTC) for the induction motor powering the pump. Unlike traditional techniques, which make no compromise between tracking speed, oscillation and robustness. The integration of the MPPT-bat represents a significant advance, making it possible to improve PVG performance whatever the weather conditions. The main objective remains to improve the energy efficiency of this type of application by maximizing the electrical power allocated to the SWPS. At the same time, a DTC controller applied to the pump motor aims to optimize the use of the energy generated by the MPPT-bat. This intelligent approach adjusts the motor power according to the power extracted from the PVG, thus avoiding inappropriate profiles for the pumping system. The study confirms that optimizing SWPS using this approach based on MPPT-bat and DTC, significantly improves overall performances in terms of tracking error, oscillations, tracking speed and robustness, promotes more efficient pump rotation and, consequently, increases the flow rate of pumped water, and that these improvements persist under different climate conditions.

Maximum power point tracking (MPPT) is considered one of the important factors in minimizing the installation costs and improving the efficiency of any photovoltaic water pumping system. The MPPT controller is specifically used to extract the maximum available power from the photovoltaic (PV) array. The maximum power can be achieved by using a specific algorithm. This work aims to raise awareness among farmers about the energy benefits available in the region of Meknes in Morocco, the economic gain and the environmental impact applied to the solar pumping system so that it can be generalized. To obtain the maximum power at each moment, a direct current (DC) water pump (SQF 0-6-2) powered by the solar panels (REC_330NP) through a buck converter was adapted. In addition, this study illustrates the theory of operation of the perturb and observe (P&O) algorithm and simulates the evaluation of this algorithm under different operating conditions (temperature and solar irradiation), and showed the advantages of this system that can operate at the optimal power regardless of disturbances.

The doubly fed induction generator (DFIG) is vulnerable to grid faults due to its direct stator connection, causing issues like excess stator current during voltage dips. Consequently, sensitive inverters suffer from increased currents, and the DC-link capacitor undergoes overcharging. This document examines two protection strategies employing a proportional–integral (PI) controller to manage the transient rotor current and mitigate DC-link overcharging, thereby optimizing DFIG behavior during network faults. One option combines a classic crowbar circuit with a DC-chopper, while the other is a modified protection scheme (MPS) that includes an impedance with passive elements and a crowbar. The impedance forms a resistance R_p parallel with an inductance L_p. Both configurations, situated between the rotor coils and the rotor-side converter (RSC), augment the capacity for low-voltage ride-through (LVRT). MATLAB/SIMULINK simulations of the two schemes demonstrate successful rotor current reduction at 2.9 kA and 3.4 kA, and DC-link tension reduction below and at 1.4 KV. In addition, the conventional crowbar and MPS configurations efficiently restrict the RSC current to levels below 0.21 kA and 2.94 kA, while absorbing up to 2.52 kA and 1.52 kA, respectively. The key difference lies in the fact that fine-tuning the parameters in the MPS design prevents rotor disconnection when faced with a balanced fault. This enhancement enhances machine performance and enables full stator power control via the RSC.