A Review on Intelligent Detection and Classification of Power Quality Disturbances:Trends,Methodologies,and Prospects

With increasing global concerns about clean energy in smart grids,the detection of power quality disturbances(PQDs)caused by energy instability is becoming more and more prominent.It is well acknowledged that the PQD effects on power grid equipment are destructive and hazardous,which causes irreversible damage to underlying electrical/electronic equipment of the concerned intelligent grids.In order to ensure safe and reliable equipment implementation,appropriate PQDdetection technologiesmust be adopted to avoid such adverse effects.This paper summarizes the newly proposed and traditional PQD detection techniques in order to give a quick start to new researchers in the related field,where specific scenarios and events for which each technique is applicable are also clearly presented.Finally,comments on the future evolution of PQD detection techniques are given.Unlike the published review articles,this paper focuses on the new techniques from the last five years while providing a brief recap on traditional PQD detection techniques so as to supply researchers with a systematic and state-of-the-art review for PQD detection.

Conductor Arrangement and Phase Sequence Optimization Scheme for 500 kV Four-Circuit Transmission Lines on Same Tower

The four-circuit parallel line on the same tower effectively solves the problems faced by the line reconstruction and construction under the condition of the increasing shortage of transmission corridors.Optimizing the conductor and phase sequence arrangement of multiple transmission lines is conducive to improving electromagnetic and electrostatic coupling caused by electromagnetic problems.This paper uses the ATP-EMTP simulation software to build a 500 kV multi-circuit transmission line on the same tower.It stimulates the induced voltage and current values of different line lengths,tower spacing,vertical and horizontal spacing between different circuits,phase sequence arrangement,and nominal tower height.Moreover,use the BP neural network optimized by a genetic algorithm to predict the induced voltage and current under the unknown conductor and phase sequence arrangement.Finally,based on multi-objective particle swarm algorithm to construct the optimization model of conductor arrangement scheme of overhead transmission line,combined with electromagnetic environment control index,determine the optimal conductor arrangement scheme by the size of particle fitness function,a significant reduction in induced voltages and currents between transmission lines and the four-circuit conductor layout scheme meeting the requirements of the electromagnetic environment is obtained,which provides a reference for the tower design of the transmission station project.

云南省有色金属产业转型增效升级现状及绿色发展对策

云南省矿产资源丰富、禀赋佳、种类全,创造了辉煌的历史,素有"有色金属王国"之美称。随着新时代经济增长的新要求,国家陆续出台了一系列倡导环境保护和绿色矿业开发的政策法规,云南省有色金属产业转型增效升级的任务迫在眉睫,产业持续发展也面临严峻挑战。调研发现,云南省有色金属产业发展面临五大突出问题:有色矿种需求分化明显、资源综合利用和深加工技术创新乏力、高端技术人才匮乏与新兴战略资源产业发展缓慢、产业生产管理模式滞后与开发成本大幅提升、资源供需矛盾加剧与冶炼产能过剩等。面对云南省有色金属产业发展的新挑战和主要问题、矿产资源政策的新动向及其产业发展的新态势,本文提出了产业绿色发展的五大对策:资源开发与环境保护并重、增强产业科技创新驱动、优化生产管理模式、减轻企业负担、推动资源战略和增强产业核心竞争力等。

Set-Membership Filtering Subject to Impulsive Measurement Outliers:A Recursive Algorithm

This paper is concerned with the set-membership filtering problem for a class of linear time-varying systems with norm-bounded noises and impulsive measurement outliers.A new representation is proposed to model the measurement outlier by an impulsive signal whose minimum interval length(i.e.,the minimum duration between two adjacent impulsive signals)and minimum norm(i.e.,the minimum of the norms of all impulsive signals)are larger than certain thresholds that are adjustable according to engineering practice.In order to guarantee satisfactory filtering performance,a so-called parameter-dependent set-membership filter is put forward that is capable of generating a time-varying ellipsoidal region containing the true system state.First,a novel outlier detection strategy is developed,based on a dedicatedly constructed input-output model,to examine whether the received measurement is corrupted by an outlier.Then,through the outcome of the outlier detection,the gain matrix of the desired filter and the corresponding ellipsoidal region are calculated by solving two recursive difference equations.Furthermore,the ultimate boundedness issue on the time-varying ellipsoidal region is thoroughly investigated.Finally,a simulation example is provided to demonstrate the effectiveness of our proposed parameter-dependent set-membership filtering strategy.

Variance-Constrained Filtering Fusion for Nonlinear Cyber-Physical Systems With the Denial-of-Service Attacks and Stochastic Communication Protocol

In this paper,a new filtering fusion problem is studied for nonlinear cyber-physical systems under errorvariance constraints and denial-of-service attacks.To prevent data collision and reduce communication cost,the stochastic communication protocol is adopted in the sensor-to-filter channels to regulate the transmission order of sensors.Each sensor is allowed to enter the network according to the transmission priority decided by a set of independent and identicallydistributed random variables.From the defenders’view,the occurrence of the denial-of-service attack is governed by the randomly Bernoulli-distributed sequence.At the local filtering stage,a set of variance-constrained local filters are designed where the upper bounds(on the filtering error covariances)are first acquired and later minimized by appropriately designing filter parameters.At the fusion stage,all local estimates and error covariances are combined to develop a variance-constrained fusion estimator under the federated fusion rule.Furthermore,the performance of the fusion estimator is examined by studying the boundedness of the fused error covariance.A simulation example is finally presented to demonstrate the effectiveness of the proposed fusion estimator.