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This paper presents the novel islanding detection technique that depends on the piezoelectric sensors for distributed generation sources (DGs) in the grid-integrated operation mode. The islanding detection method employs a piezoelectric sensor for the detection of the frequency variations during grid disruptions. The designed diaphragm-based sensor has a natural frequency as that of the fundamental frequency of the system frequency signal. Any further deviations from the natural frequency due to the disturbances will be sensed by the sensor and a control signal is being sent to the associated circuit breaker for suitable action. The sensor structure is modeled using the finite element method and implemented in the Phase-Locked Loop (PLL) of the grid-integrated DGs. The proposed circular diaphragm-based sensor structure will have the bandwidth in the range of natural frequency with the tolerance rate of ±1% and uses the input signal received from the PLL controller outer loop. The proposed islanding detection technique's performance and reliability for grid-integrated DG are validated using the real-time hardware in the loop test-bed platform. The HIL virtual simulated responses show that the method can be proposed effectively for islanding detection in the event of frequency variations in the grid-integrated DG systems. [ABSTRACT FROM AUTHOR]

Offshore wind farms equipped with Direct Drive Permanent Magnet Synchronous Generators (DD-PMSG) are drawing increased attention due to their advantage over other variable speed technologies. VSC-HVDC links are considered the most suitable option for transferring power to the onshore system. The integration of VSC-HVDC connected DD-PMSG based offshore wind farms into multi-machine systems is explored in this paper. A novel approach for power flow and initial condition calculations is proposed to facilitate dynamic analysis of the system. For three cases of the most commonly specified quantities of the wind farm, efficient methods have been described. The cases comprise combinations of data like the total output of the wind farm, the number of wind turbines, the wind speed, or the output of individual wind turbine, which are frequently given in literature. This approach enables the user to build the dynamic model of the system in any basic graphical dynamic modeler and numerical computational software without requiring power system toolboxes or electromagnetic transient packages. The proposed methods are highly effective for studies focusing primarily on the dynamic aspects and controls of the system. Case studies and simulations are conducted to verify the proposed technique. [ABSTRACT FROM AUTHOR]