The renewable energy systems are going to take over most of the non-renewable energy systems, so many scientific efforts are being made to ensure the stability and reliability of the renewable energy systems. This paper is concerned about the wind energy systems and ensuring their behavior and performance during and after the abnormalities like fault ride-through. Two complete models of a grid connected wind systems are going to be simulated in the MATLAB software program, the first one will be a grid connected wind turbine driving a three-phase squirrel-cage induction generator (SCIG) and the other model will be a grid connected wind turbine driving a three-phase doubly-fed induction generator (DFIG). The frequency of each system will be displayed and compared to the frequency of the other system upon fault ride-through (three-phase short-circuit fault) and under the effect of the PID controller which is tuned by genetic algorithm technique. The different responses of both generators are going to be analyzed graphically and compared to each other upon the ride-through fault and under the effect of the designed controller (genetic algorithm PID controller).Â
The rising energy independence and environmental concerns are key drivers in the growing popularity of plug-in hybrid electric vehicles (PHEVs). Because of the intermittent nature of the renewable energy sources, this may cause a high-frequency oscillation of the power system. From another aspect, all the PHEVs have in common the batteries, which provide the storage capability that can be effectively harnessed when the vehicles are integrated into the grid. Such a storage capability can effectively integrate wind power into the grid and all indicators signalize that the PHEVs are the most promising technology of the future transportation system. In this paper, different case studies are applied on one area power system to show the effect of the high wind energy penetration on the power system frequency and how the PHEVs can play an effective role in mitigating the power system frequency oscillation and supporting the more penetration of the wind energy into smarter electrical grids. In addition, an advanced controller has been designed to improve the frequency response and to compensate the delay of the system. The designed controller is a genetic algorithm (GA) based PID (proportional-integral-derivative) controller, it has been proposed for tuning optimized PID parameters. The results show that the controller has played an effective role in decreasing the response overshoot and settling time when used with the PHEVs. The used variable load, the thermal power plant parameters, and the wind turbine parameters are the same for the five case studies.
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