Virtual synchronous generators(VSGs)can provide voltage and frequency support to power systems due to their inertial and damping features.Unfortunately,power angle stability and fault current limitations are still cha...Virtual synchronous generators(VSGs)can provide voltage and frequency support to power systems due to their inertial and damping features.Unfortunately,power angle stability and fault current limitations are still challenging aspects of VSGs under large disturbances.Power angle stability and fault current limitations are indispensable for the safe operation of a VSG.However,in existing studies,these aspects are mostly solved as two independent problems.In this paper,the comprehensive transient stability enhancement(CTSE)control strategy for a VSG,considering power angle stability and fault current limitations is proposed.With a CTSE control,VSG's transient power angle stability is guaranteed.In addition,the steady-state and impulse components of the fault current are fully limited.Furthermore,CTSE control parameters adapted to different fault degrees are presented.Finally,simulation and experimental tests are performed to validate the performance of the proposed method.展开更多
Otoacoustic emissions (OAEs) has been considered as an excellent objective tool in clinics for diagnosing hearing loss. The signal-to-noise ratio (SNR) and correlation coefficient of OAEs are very important for the pu...Otoacoustic emissions (OAEs) has been considered as an excellent objective tool in clinics for diagnosing hearing loss. The signal-to-noise ratio (SNR) and correlation coefficient of OAEs are very important for the purpose of diagnosis. An adaptive signal enhancer (ASE) based on the Least Mean Square (LMS) algorithm is presented to detect transient evoked OAEs (TEOAEs). The TEOAEs detection results from 106 ears show that ASE reaches better estimation of TEOAEs than a conventional ensemble averaging (EA) technique. With the ASE, the improvement of SNR was increased faster than that with the EA and the number of sweeps required can be markedly reduced. The detection time with ASE could be shortened by about 50% in comparison with that of EA.展开更多
基金supported by the National Natural Science Foundation of China(51907057,52077072).
文摘Virtual synchronous generators(VSGs)can provide voltage and frequency support to power systems due to their inertial and damping features.Unfortunately,power angle stability and fault current limitations are still challenging aspects of VSGs under large disturbances.Power angle stability and fault current limitations are indispensable for the safe operation of a VSG.However,in existing studies,these aspects are mostly solved as two independent problems.In this paper,the comprehensive transient stability enhancement(CTSE)control strategy for a VSG,considering power angle stability and fault current limitations is proposed.With a CTSE control,VSG's transient power angle stability is guaranteed.In addition,the steady-state and impulse components of the fault current are fully limited.Furthermore,CTSE control parameters adapted to different fault degrees are presented.Finally,simulation and experimental tests are performed to validate the performance of the proposed method.
基金This work was supported by the National Natural Science Foundation of China (No.39870212)
文摘Otoacoustic emissions (OAEs) has been considered as an excellent objective tool in clinics for diagnosing hearing loss. The signal-to-noise ratio (SNR) and correlation coefficient of OAEs are very important for the purpose of diagnosis. An adaptive signal enhancer (ASE) based on the Least Mean Square (LMS) algorithm is presented to detect transient evoked OAEs (TEOAEs). The TEOAEs detection results from 106 ears show that ASE reaches better estimation of TEOAEs than a conventional ensemble averaging (EA) technique. With the ASE, the improvement of SNR was increased faster than that with the EA and the number of sweeps required can be markedly reduced. The detection time with ASE could be shortened by about 50% in comparison with that of EA.
