Variations in tidal currents and suspended sediment concentration of the upper part of the North Channel of Changjiang Estuary over the past 10 years

The tidal current duration （TCD） and velocity （TCV） and suspended sediment concentration （SSC） were measured in the dry season in December, 2011 and in the flood season in June, 2012 at the upper part of the North Channel of Changjiang Estuary. They were assimilated with the measured data in 2003, 2004, 2006 and 2007, using the tidal range＇s proportion conversion. Variations in TCD and TCV, preferential flow and SSC have been calculated. Influences of typical engineering projects such as Qingcaosha fresh water reservoir, Yangtze River Bridge, and land reclamation on the ebb and flood TCD, TCV and SSC in the North Channel for the last 10 years are discussed. The results show that： （1） currently, in the upper part of North Channel, the ebb tide dominates; after the construction of the typical projects, ebb TCD and TCV tends to be larger and the vertical average ebb and flood SSC decrease during the flood season while SSC increases during the dry season; （2） changes in the vertical average TCV are mainly contributed by seasonal runoff variation during the flood season, which is larger in the flood season than that in the dry season; the controlling parameters of increasing ebb TCD and TCV are those large-scale engineering projects in the North Channel; variation in SSC may result mainly from the reduction of basin annual sediment loads, large-scale nearshore projects and so on.

An Intrusion Detection Method for Advanced Metering Infrastructure System Based on Federated Learning

An advanced metering infrastructure(AMI)system plays a key role in the smart grid(SG),but it is vulnerable to cyberattacks.Current detection methods for AMI cyberattacks mainly focus on the data center or a distributed independent node.On one hand,it is difficult to train an excellent detection intrusion model on a self-learning independent node.On the other hand,large amounts of data are shared over the network and uploaded to a central node for training.These processes may compromise data privacy,cause communication delay,and incur high communication costs.With these limitations,we propose an intrusion detection method for AMI system based on federated learning(FL).The intrusion detection system is deployed in the data concentrators for training,and only its model parameters are communicated to the data center.Furthermore,the data center distributes the learning to each data concentrator through aggregation and weight assignments for collaborative learning.An optimized deep neural network(DNN)is exploited for this proposed method,and extensive experiments based on the NSL-KDD dataset are carried out.From the results,this proposed method improves detection performance and reduces computation costs,communication delays,and communication overheads while guaranteeing data privacy.

PMU based adaptive zone settings of distance relays for protection of multi-terminal transmission lines

This paper proposes Phasor Measurement Unit(PMU)based adaptive zone settings of distance relays(PAZSD)methodology for protection of multi-terminal transmission lines(MTL).The PAZSD methodology employs current coefficients to adjust the zone settings of the relays during infeed situation.These coefficients are calculated in phasor data concentrator(PDC)at system protection center(SPC)using the current phasors obtained from PMUs.The functioning of the distance relays during infeed condition with and without the proposed methodology has been illustrated through a four-bus model implemented in PSCAD/EMTDC environment.Further,the performance of the proposed methodology has been validated in real-time,on a laboratory prototype of Extra High Voltage multi-terminal transmission lines(EHV MTL).The phasors are estimated in PMUs using NI cRIO-9063 chassis embedded with data acquisition sensors in conjunction with LabVIEW software.The simulation and hardware results prove the efficacy of the proposed methodology in enhancing the performance and reliability of conventional distance protection system in real-time EHV MTLs.