Monitoring data show that many landslides in the Three Gorges region,China,undergo step-like displacements in response to the managed,quasi-sinusoidal annual variations in reservoir level.This behavior is consistent w...Monitoring data show that many landslides in the Three Gorges region,China,undergo step-like displacements in response to the managed,quasi-sinusoidal annual variations in reservoir level.This behavior is consistent with motion initiating when the reservoir water level falls below a critical level that is intrinsic to each landslide,with the subsequent displacement rate of the landslide being proportional to the water depth below that critical level.Most motion terminates when the water level rises back above the critical level,so the annual step size is the time integral of the instantaneous displacement rate.These responses are incorporated into a differential equation that is easily calibrated with monitoring data,allowing prediction of landslide movement from actual or anticipated reservoir level changes.Model successes include(1)initiation and termination of the annual sliding steps at the critical reservoir level,producing a series of steps;(2)prediction of variable step size,year to year;and(3)approximate prediction of the shape and size of each annual step.Annual rainfall correlates poorly with step size,probably because its effect on groundwater levels is dwarfed by the 30 m annual variations in the level of the Three Gorges Reservoir.Viscous landslide behavior is suggested.展开更多
Transient stability assessment(TSA) is of great importance in power systems. For a given contingency, one of the most widely-used transient stability indices is the critical clearing time(CCT), which is a function of ...Transient stability assessment(TSA) is of great importance in power systems. For a given contingency, one of the most widely-used transient stability indices is the critical clearing time(CCT), which is a function of the pre-fault power flow.TSA can be regarded as the fitting of this function with the prefault power flow as the input and the CCT as the output. In this paper, a data-driven TSA model is proposed to estimate the CCT. The model is based on Mahalanobis-kernel regression,which employs the Mahalanobis distance in the kernel regression method to formulate a better regressor. A distance metric learning approach is developed to determine the problem-specific distance for TSA, which describes the dissimilarity between two power flow scenarios. The proposed model is more accurate compared to other data-driven methods, and its accuracy can be further improved by supplementing more training samples.Moreover, the model provides the probability density function of the CCT, and different estimations of CCT at different conservativeness levels. Test results verify the validity and the merits of the method.展开更多
基金the National Key R&D Program of China(Nos.2018YFC1507200,2017YFC1501304)the National Science Fund for Excellent Young Scholars of China(No.41922055)。
文摘Monitoring data show that many landslides in the Three Gorges region,China,undergo step-like displacements in response to the managed,quasi-sinusoidal annual variations in reservoir level.This behavior is consistent with motion initiating when the reservoir water level falls below a critical level that is intrinsic to each landslide,with the subsequent displacement rate of the landslide being proportional to the water depth below that critical level.Most motion terminates when the water level rises back above the critical level,so the annual step size is the time integral of the instantaneous displacement rate.These responses are incorporated into a differential equation that is easily calibrated with monitoring data,allowing prediction of landslide movement from actual or anticipated reservoir level changes.Model successes include(1)initiation and termination of the annual sliding steps at the critical reservoir level,producing a series of steps;(2)prediction of variable step size,year to year;and(3)approximate prediction of the shape and size of each annual step.Annual rainfall correlates poorly with step size,probably because its effect on groundwater levels is dwarfed by the 30 m annual variations in the level of the Three Gorges Reservoir.Viscous landslide behavior is suggested.
基金supported by National Key R&D Program of China (No.2018YFB0904500)State Grid Corporation of China。
文摘Transient stability assessment(TSA) is of great importance in power systems. For a given contingency, one of the most widely-used transient stability indices is the critical clearing time(CCT), which is a function of the pre-fault power flow.TSA can be regarded as the fitting of this function with the prefault power flow as the input and the CCT as the output. In this paper, a data-driven TSA model is proposed to estimate the CCT. The model is based on Mahalanobis-kernel regression,which employs the Mahalanobis distance in the kernel regression method to formulate a better regressor. A distance metric learning approach is developed to determine the problem-specific distance for TSA, which describes the dissimilarity between two power flow scenarios. The proposed model is more accurate compared to other data-driven methods, and its accuracy can be further improved by supplementing more training samples.Moreover, the model provides the probability density function of the CCT, and different estimations of CCT at different conservativeness levels. Test results verify the validity and the merits of the method.
