The apparent velocity of the incident wave is an important parameter for simulating rotational ground motion with theoretical methods, but it is difficult to estimate effectively when there is only a single record. Th...The apparent velocity of the incident wave is an important parameter for simulating rotational ground motion with theoretical methods, but it is difficult to estimate effectively when there is only a single record. This paper discusses a P-SV ratio method based on elastodynamic theory in a multi-layer isotropic elastic half space. The apparent velocities of four earthquakes in the SMART1 array are calculated with this method. The result is close to a method that uses travel time analysis. Furthermore, the factors that impact the apparent velocity and equivalent incident angle are considered according to records from the Chi-Chi earthquake. There is no obvious relationship between the equivalent incident angle and epicenter distance. However, the equivalent incident angle is obviously dependent on the site conditions.展开更多
Remote monitoring of transmission lines of a power system is significant for improved reliability and stability during fault conditions and protection system breakdowns.This paper proposes a smart backup monitoring sy...Remote monitoring of transmission lines of a power system is significant for improved reliability and stability during fault conditions and protection system breakdowns.This paper proposes a smart backup monitoring system for detecting and classifying the type of transmission line fault occurred in a power grid.In contradiction to conventional methods,transmission line fault occurred at any locality within power grid can be identified and classified using measurements from phasor measurement unit(PMU)at one of the generator buses.This minimal requirement makes the proposed methodology ideal for providing backup protection.Spectral analysis of equivalent power factor angle(EPFA)variation has been adopted for detecting the occurrence of fault that occurred anywhere in the grid.Classification of the type of fault occurred is achieved from the spectral coefficients with the aid of artificial intelligence.The proposed system can considerably assist system protection center(SPC)in fault localization and to restore the line at the earliest.Effectiveness of proposed system has been validated using case studies conducted on standard power system networks.展开更多
基金the National Science Foundation of China Under Grant No.90815026 and 50638010the National Seismic Project Under Grant No.200808074
文摘The apparent velocity of the incident wave is an important parameter for simulating rotational ground motion with theoretical methods, but it is difficult to estimate effectively when there is only a single record. This paper discusses a P-SV ratio method based on elastodynamic theory in a multi-layer isotropic elastic half space. The apparent velocities of four earthquakes in the SMART1 array are calculated with this method. The result is close to a method that uses travel time analysis. Furthermore, the factors that impact the apparent velocity and equivalent incident angle are considered according to records from the Chi-Chi earthquake. There is no obvious relationship between the equivalent incident angle and epicenter distance. However, the equivalent incident angle is obviously dependent on the site conditions.
文摘Remote monitoring of transmission lines of a power system is significant for improved reliability and stability during fault conditions and protection system breakdowns.This paper proposes a smart backup monitoring system for detecting and classifying the type of transmission line fault occurred in a power grid.In contradiction to conventional methods,transmission line fault occurred at any locality within power grid can be identified and classified using measurements from phasor measurement unit(PMU)at one of the generator buses.This minimal requirement makes the proposed methodology ideal for providing backup protection.Spectral analysis of equivalent power factor angle(EPFA)variation has been adopted for detecting the occurrence of fault that occurred anywhere in the grid.Classification of the type of fault occurred is achieved from the spectral coefficients with the aid of artificial intelligence.The proposed system can considerably assist system protection center(SPC)in fault localization and to restore the line at the earliest.Effectiveness of proposed system has been validated using case studies conducted on standard power system networks.
