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.

Attaining highly secure and safe operation of the grid with acceptable voltage levels has become a difficult issue for electricity companies that must adopt remedial actions. The usage of a PV solar farm inverter as a static synchronous compensator (or PVSTATCOM device) throughout the night has recently been proposed as a way to enhance the system performance. In this article, the novel artificial rabbits’ optimization algorithm (AROA) is developed for minimizing both the daily energy losses and the daily voltage profile considering different 24 h loadings. The novel AROA is inspired from the natural surviving strategies of rabbits. The novel AROA is tested on a typical IEEE 33-node distribution network including three scenarios. Different scenarios are implemented considering PV/STATCOM allocations throughout the day. The effectiveness of the proposed AROA is demonstrated in comparison to differential evolution (DE) algorithm and golden search optimization (GSO). The PVSTATCOM is adequately allocated based on the proposed AROA, where the energy losses are greatly reduced with 54.36% and the voltage deviations are greatly improved with 43.29%. Moreover, the proposed AROA provides no violations in all constraints while DE fails to achieve these limits. Therefore, the proposed AROA shows greater dependability than DE and GSO. Moreover, the voltage profiles at all distribution nodes all over the daytime hours are more than the minimum limit of 95%.

The derivation of PV model parameters is crucial for the optimization, control, and simulation of PV systems. Although many parameter extraction algorithms have been developed to address this issue, they might have some limitations. This work presents an efficient hybrid optimization approach for reliably and effectively extracting PV parameters based on the hunter–prey optimizer (HPO) technique. The proposed HPO technique is a new population-based optimizer inspired by the behavior of prey and predator animals. In the proposed HPO mechanism, the predator attacks the prey that leaves the prey population. Accordingly, the position of a hunter is adjusted toward this distant prey, while the position of the prey is adjusted towards a secure place. The search agent’s position, which represents the best fitness function value, is considered a secure place. The proposed HPO technique worked as suggested when parameters are extracted from several PV models, including single-, double-, and triple-diode models. Moreover, a statistical error analysis was used to demonstrate the superiority of the proposed method. The proposed HPO technique outperformed other recently reported techniques in terms of convergence speed, dependability, and accuracy, according to simulation data.

This study explores the energy demand planning for university loads at the new Sohag University campus in Sohag Al Gadida City, Egypt. It assesses the feasibility of establishing a microgrid on a section of the campus to determine its practicality and potential benefits. The existing power distribution system is analyzed, and the suitability of various distributed generation sources, including photovoltaic, battery, and hydrogen-based microgrid, is evaluated. A techno-economic analysis is conducted to optimize microgrid sizing, using MATLAB R2023a (Optimization Toolbox) to implement a sizing algorithm for a hybrid microgrid system and HOMER Pro 3.14 for component sizing. The optimal microgrid configuration is verified based on the intended power supply potential while minimizing costs. The results demonstrate that the energy costs of the proposed hybrid microgrid system align with previously published values, confirming its feasibility. Additionally, economic analysis reveals that the proposed system not only reduces carbon emissions but also achieves cost savings of 20–30% over 20 years compared to conventional grid supply, with a payback period of 8–10 years.

Nuclear and renewables energies are the two variants for low-carbon energy and the evolving grid suggests possible synergies between them. Nuclear energy introduces supple operations based on power demand, while renewables such as PV and wind hybrid systems depend on the presence and strength of sunlight or wind. For grid stability, there is need to improve their performance in order to overcome the impact of this disadvantage. The paper is a step in this direction as it addresses a detailed comprehensive dynamic modeling and an efficient control of grid-connected energy sources such as PV or wind system to increase system reliability and to ensure the power quality and safe operation of critical demands. The behavior of the suggested hybrid system is tested at different climate circumstances such as variation of sun radiation and wind speed. The PV is equipped with a boost converter and a three-phase pulse width modulation (PWM) inverter. The wind energy comprises a doubly fed generator (DFIG) based on a variable-speed wind turbine. The two controllers’ rotor-side and grid-side converters of DFIG have the ability to generate and observe reactive power, to keep constant speed of the rotor and control the DC-link voltage. The proposed scheme was investigated using MATLAB software. The maximum power point tracking (MPPT) was used for two systems, PV and wind, in varying weather conditions. The simulation results prove that the voltage at the point of common coupling was constant. Furthermore, the injected current of the grid side was in sinusoidal form and was synchronized with grid side voltage. In addition, the injected power-to-utility grid was around power delivered by the hybrid PV and wind system.