In recent years,with increasing amounts of renew-able energy sources connecting to power grids,sub-/super-syn-chronous oscillations(SSOs)occurred more frequently.Due to the time-variant nature of SsO magnitudes and fr...In recent years,with increasing amounts of renew-able energy sources connecting to power grids,sub-/super-syn-chronous oscillations(SSOs)occurred more frequently.Due to the time-variant nature of SsO magnitudes and frequencies,as well as the mutual interferences among SsO modes with close frequencies,the accurate parameter estimation of SsO has be-come a particularly challenging topic.To solve this issue,this paper proposes an improved spectrum analysis method by im-proving the window function and a spectrum correction method to achieve higher precision.First,by aiming at the sidelobe characteristics of the window function as evaluation criteria,a combined cosine function is optimized using a genetic algorithm(GA).Furthermore,the obtained window function is self-con-volved to extend its excellent characteristics,which have better performance in reducing mutual interference from other SSO modes.Subsequently,a new form of interpolated all-phase fast Fourier transform(IpApFFT)using the optimized window func-tion is proposed to estimate the parameters of SsO.This meth-od allows for phase-unbiased estimation while maintaining algo-rithmic simplicity and expedience.The performance of the pro-posed method is demonstrated under various conditions,com-pared with other estimation methods.Simulation results vali-date the effectiveness and superiority of the proposed method.展开更多
基金supported in part by Science and Technology Project of State Grid Corporation of China(No.5108-202299269A-1-0-ZB).
文摘In recent years,with increasing amounts of renew-able energy sources connecting to power grids,sub-/super-syn-chronous oscillations(SSOs)occurred more frequently.Due to the time-variant nature of SsO magnitudes and frequencies,as well as the mutual interferences among SsO modes with close frequencies,the accurate parameter estimation of SsO has be-come a particularly challenging topic.To solve this issue,this paper proposes an improved spectrum analysis method by im-proving the window function and a spectrum correction method to achieve higher precision.First,by aiming at the sidelobe characteristics of the window function as evaluation criteria,a combined cosine function is optimized using a genetic algorithm(GA).Furthermore,the obtained window function is self-con-volved to extend its excellent characteristics,which have better performance in reducing mutual interference from other SSO modes.Subsequently,a new form of interpolated all-phase fast Fourier transform(IpApFFT)using the optimized window func-tion is proposed to estimate the parameters of SsO.This meth-od allows for phase-unbiased estimation while maintaining algo-rithmic simplicity and expedience.The performance of the pro-posed method is demonstrated under various conditions,com-pared with other estimation methods.Simulation results vali-date the effectiveness and superiority of the proposed method.
