In this work, a hybrid system is comprised of wind turbines (WT) and photovoltaic (PV) panels to generate green Hydrogen via water electrolysis. Consideration is given to the influence of five electrical power generation scenarios on system performance and Hydrogen production cost. This study adopts the solar radiation, wind speed, and ambient temperature for Mersa-Matruh in Egypt. The system performance is studied using MATLAB-Simulink over one year. The winter months have high wind speed and low sun radiation compared to other months, whereas additional months have high solar radiation and lower wind speed than the winter months. The findings show that the amount of Hydrogen produced for all scenarios varies from 12,340 m3 to 13,748 m3 per year. The system efficiency and LCOH are 7.974% and 3.67 USD/kg, 9.56%, and 3.97 USD/kg, 10.7% and 4.12 USD/kg, 12.08%, and 4.3 USD/kg, and 16.23% and 4.69 USD/kg for scenarios 1 to 5, respectively. Finally, the introduced system can reduce CO2 emissions by 345 tons over the lifetime and gain about 13,806 USD.

Accurate power sharing in islanded microgrids (MGs) is essential to preserve the system stability and deliver the required load power. However, the distinct ratings of feeders result in disparate voltage drops and, therefore, varying output voltages from distributed generators (DGs). So, this work proposes a distributed adaptive virtual complex impedance to achieve accurate power sharing of loads between DG units with minimum control loops. The controller dynamically adjusts its parameters based on the system parameters, allowing it to adapt to various conditions. Unlike previous controllers, the proposed controller can work effectively with multiple connected DGs in the system. The designed approach accounts for complex components of the feeders’ impedances, with actual ratios between the complex components to enhance the system performance and the point of common coupling voltage. Based on that, the decoupling between the active and reactive power is achieved. The proposed controller’s effectiveness, including two and multiple DGs, is verified and compared to conventional control methods. For two DGs, the proposed controller proved its superiority over previous methods and proved its scalability in the DG system. The proposed controller is capable of achieving accurate reactive power sharing, reducing active power oscillations, enhancing the point of common coupling (PCC) voltage, synchronizing system currents, and minimizing circulating currents within the system. This is demonstrated through different scenarios. The first scenario is through a 2-DG system and comparing the results with conventional droop control and conventional virtual impedance. The second scenario involves statistically comparing the proposed controller with those in the literature, focusing on the controller percentage overshoot, response time, and PCC voltage level. The third scenario is conducted to prove the ability of the proposed controller to be extended for multiple connected DGs in the MG system.

Global warming and rising energy demands have increased renewable energy (RE) usage globally. Wind energy has become the most technologically advanced renewable energy source. Wind turbines (WTs) must ride through faults to ensure power system stability. On the flip side, permanent magnet synchronous generators (PMSG)-based wind turbine power plants (WTPPs) are susceptible to grid voltage fluctuations and require extra regulations to maintain regular operations. Due to recent changes in grid code standards, it has become vital to explore alternate fault ride-through (FRT) methods to ensure their capabilities. This research will ensure that FRT solutions available via the Web of Science (WoS) database are vetted and compared in hardware retrofitting, internal software control changes, and hybrid techniques. In addition, a bibliometric analysis is provided, which reveals an ever-increasing volume of works dedicated to the topic. After that, a literature study of FRT techniques for PMSG WTs is carried out, demonstrating the evolution of these techniques over time. This paper concludes that additional research is required to enhance FRT capabilities in PMSG wind turbines and that further attention to topics, such as machine learning tools and the combination of FRT and wind power smoothing approaches, should arise in the following years.