In order to detect and estimate faults in discrete lin-ear time-varying uncertain systems, the discrete iterative learning strategy is applied in fault diagnosis, and a novel fault detection and estimation algorithm i...In order to detect and estimate faults in discrete lin-ear time-varying uncertain systems, the discrete iterative learning strategy is applied in fault diagnosis, and a novel fault detection and estimation algorithm is proposed. And the threshold limited technology is adopted in the proposed algorithm. Within the chosen optimal time region, residual signals are used in the proposed algorithm to correct the introduced virtual faults with iterative learning rules, making the virtual faults close to these occurred in practical systems. And the same method is repeated in the rest optimal time regions, thereby reaching the aim of fault diagnosis. The proposed algorithm not only completes fault detection and estimation for discrete linear time-varying uncertain systems, but also improves the reliability of fault detection and decreases the false alarm rate. The final simulation results verify the validity of the proposed algorithm.展开更多
With the global energy transition,the proportion of renewable energy power generation in total electricity production has exceeded 30%and continues to rise,even the ratio is higher in China.Multi-terminal high-voltage...With the global energy transition,the proportion of renewable energy power generation in total electricity production has exceeded 30%and continues to rise,even the ratio is higher in China.Multi-terminal high-voltage direct-current(MT-HVDC)transmission systems have advantages of integration of distributed renewable energy sources,dynamic grid interconnections,and reliable islanding operation capabilities,being critical for next-generation power grid.Current limiting technologies are pivotal in maintaining grid safety and stability,especially for HVDC systems without natural zero-crossing point in fault currents.In this perspective,a superconducting fault current limiter(SFCL)with combination of resistance and inductance is necessary and more effective solution in protecting MT-HVDC transmission systems.展开更多
基金supported by the National Natural Science Foundation of China(61100103)
文摘In order to detect and estimate faults in discrete lin-ear time-varying uncertain systems, the discrete iterative learning strategy is applied in fault diagnosis, and a novel fault detection and estimation algorithm is proposed. And the threshold limited technology is adopted in the proposed algorithm. Within the chosen optimal time region, residual signals are used in the proposed algorithm to correct the introduced virtual faults with iterative learning rules, making the virtual faults close to these occurred in practical systems. And the same method is repeated in the rest optimal time regions, thereby reaching the aim of fault diagnosis. The proposed algorithm not only completes fault detection and estimation for discrete linear time-varying uncertain systems, but also improves the reliability of fault detection and decreases the false alarm rate. The final simulation results verify the validity of the proposed algorithm.
文摘With the global energy transition,the proportion of renewable energy power generation in total electricity production has exceeded 30%and continues to rise,even the ratio is higher in China.Multi-terminal high-voltage direct-current(MT-HVDC)transmission systems have advantages of integration of distributed renewable energy sources,dynamic grid interconnections,and reliable islanding operation capabilities,being critical for next-generation power grid.Current limiting technologies are pivotal in maintaining grid safety and stability,especially for HVDC systems without natural zero-crossing point in fault currents.In this perspective,a superconducting fault current limiter(SFCL)with combination of resistance and inductance is necessary and more effective solution in protecting MT-HVDC transmission systems.
