The expanding use of photovoltaics (PV) as a green energy resource has been rising in these years, mostly due to the possibility of being incorporated with traditional power systems, to meet the world’s energy needs and reduce carbon emissions. However, providing green electricity from this renewable generator is frequently vulnerable to power quality (PQ) disruptions resulting from the PV’s intermittent nature and other factors associated with the electric grid, power converters, and linked loads. These disruptions need to be reduced to keep the investigated system’s PQ from deteriorating. The investigated system includes PV, DC-DC, and DC-AC converters, filter, power grid, and control schemes. If the DC-DC converter is not managed, a deviation from the maximum power point (MPP) extrapolated from the PV system will take place. In order to maximize the energy harvested from the PV system by managing the DC-DC converter, this research developed two MPP tracking (MPPT) algorithms: artificial neural networks (ANN) and cuckoo search (CS). Additionally, a design and implementation for a shunt active power filter (LCL) using genetic algorithm and GRG is provided to lower the injected total harmonic distortion (THD) and thereby enhance the PQ. To achieve the smallest size of the LCL components, the generalized reduced gradient (GRG) was the best compared to genetic algorithms GA. The results of the simulation showed that ANN performed better at tracking maximum power than CS. With the designed LCL, the THD is reduced by 99.78% compared to without a filter. To verify the simulation’s findings, a practical configuration is implemented.

In recent modern power systems, the number of renewable energy systems (RESs) and nonlinear loads have become more prevalent. When these systems are connected to the electricity grid, they may face new difficulties and issues such as harmonics and non-standard voltage. The proposed study suggests the application of a whale optimization algorithm (WOA) based on a fractional-order proportional-integral controller (FOPIC) for unified power quality conditioner (UPQC) and STATCOM tools. These operate best with the help of their improved control system, to increase the system’s reliability and fast dynamic response, and to decrease the total harmonic distortion (THD) for enhancing the power quality (PQ). In this article, three different configurations are studied and assessed, namely: (C₁) WOA-based FOPIC for UPQC, (C₂) WOA-based FOPIC for STATCOM, and (C₃) system without FACTS, i.e., base case, to mitigate the mentioned drawbacks. C₃ is also considered as a base case to highlight the main benefits of C₁ and C₂ in improving the PQ by reducing the %THD of the voltage and current system and improving the systems’ voltage waveforms. With C₂, voltage fluctuation is decreased by 98%, but it nearly disappears in C₁ during normal conditions. Additionally, during the fault period, voltage distortion is reduced by 95% and 100% with C₂ and C₁, respectively. Furthermore, when comparing C₁ to C₂ and C₃ under regular conditions, the percentage reduction in THD is remarkable. In addition, C₁ eliminates the need for voltage sag, and harmonic and current harmonic detectors, and it helps to streamline the control approach and boost control precision. The modeling and simulation of the prepared system are performed by MATLAB/Simulink. Finally, it can be concluded that the acquired results are very interesting and helpful in the recovery to the steady state of wind systems and nonlinear loads, thereby increasing their grid connection capabilities.

In recent times, renewable energy systems (RESs) such as Photovoltaic (PV) and wind turbine (WT) are being employed to produce hydrogen. This paper aims to compare the efficiency and performance of PV and WT as sources of RESs to power polymer electrolyte membrane electrolyzer (PEMEL) under different conditions. The study assessed the input/output power of PV and WT, the efficiency of the MPPT controller, the calculation of the green hydrogen production rate, and the efficiency of each system separately. The study analyzed variable irradiance from 600 to 1000 W/m² for a PV system and a fixed temperature of 25°C, while for the WT system, it considered variable wind speed from 10 to 14 m/s and zero fixed pitch angle. The study demonstrated that the applied controllers were effective, fast, low computational, and highly accurate. The obtained results showed that WT produces twice the PEMEL capacity, while the PV system is designed to be equal to the PEMEL capacity. The study serves as a reference for designing PV or WT to feed an electrolyzer. The MATLAB program validated the proposed configurations with their control schemes.