Research Progress of On-line Monitoring Technology for Electromagnetic Environment of Power Transmission and Transformation Projects

Based on the collection of relevant literature and cases,the research and application status of on-line monitoring technology for electromagnetic environment of power transmission and transformation projects at home and abroad were introduced.Moreover,the problems existing in the on-line monitoring of electromagnetic environment were expounded,and the development prospect was forecasted.

Compliance verification and probabilistic analysis of state-wide power quality monitoring data

This paper introduces the implementation and data analysis associated with a state-wide power quality monitoring and analysis system in China. Corporation specifications on power quality monitors as well as on communication protocols are formulated for data transmission. Big data platform and related technologies are utilized for data storage and computation. Compliance verification analysis and a power quality performance assessment are conducted, and a visualization tool for result presentation is finally presented.

A Remote Real-Time Monitoring System for Power Quality

An introduction is made to the composition, design method and engineering application of a remote real time monitoring system of power quality in substations based on internet. With virtual instrument and network technique adopted, this system is characterized by good real time property, high reliability, plentiful functions, and so on. It also can be used to monitor the load of a substation, such as electric locomotives.

On-line monitoring of dissolved gas-in-oil with FTIR spectra

To overcome the disadvantages of conventional DGA (dissolved gas-in-oil)analysis using gas chromatography and other electrochemical sensors, initial researches werecompleted to realize on-line monitoring of dissolved gas-in-oil of power transformers using FTIR(Fourier Transform InfraRed) spectroscopy. Gas cell method is used to determine the characteristicabsorption peaks of each diagnostic gas; simple and novel devices and procedures were designed inorder to get measurable samples and spectra of mixed diagnostic gases with known concentration aretaken using long optical path gas cell. The range of wavelength is estimated to be 3.0-13.9 mum fromexperimental spectra data. Hence the corresponding sampling frequency range should be in 536-4288Hz and usable optical materials are suggested. It is concluded that a resolution of 10 cm^(-1) maywell satisfy the monitoring of all diagnostic gases and water content except hydrogen, and thelowest detection limit may be as low as 2Xl0^(-8) to acetylene with a 2.4-meter-long optical length.

Using Grey Target Theory for Power Quality Evaluation Based on Power Quality Monitoring Data

Smart grid puts forward higher requirements for power quality.Power quality evaluation can provide a decision-making basis for quality improvement.Based on power quality monitoring data,a grey target method is proposed for power quality evaluation.The grey target is composed of power quality evaluation standard and power quality monitoring data to be evaluated.Combining with the characteristics of each power quality evaluation index,the target center of the whole grey target system is found.Then,the power quality monitoring data to be evaluated and the power quality standard mode are compared and analyzed to construct the power quality grey correlation difference information space.Finally,the target center coefficient and target degree of power quality are calculated to realize the comprehensive evaluation of power quality,and the evaluation grade of power quality monitoring data to be evaluated is obtained.Compared with the evaluation results of the existing literature,the effectiveness of the proposed method is verified,which shows that grey target theory is reasonable in the comprehensive evaluation of power quality.

A power-quality monitoring and assessment system for high-speed railways based on train-network-data center integration

In recent years,with the rapid development of high-speed railways(HSRs),power interruptions or disturbances in traction power supply systems have become increasingly dangerous.However,it is often impossible to detect these faults immediately through single-point monitoring or collecting data after accidents.To coordinate the power quality data of both traction power supply systems(TPSSs)and high-speed trains(HSTs),a monitoring and assessing system is proposed to access the power quality issues on HSRs.By integrating train monitoring,traction substation monitoring and data center,this monitoring system not only realizes the real-time monitoring of operational behaviors for both TPSSs and HSTs,but also conducts a comprehensive assessment of operational quality for train-network systems.Based on a large number of monitoring data,the field measurements show that this real-time monitoring system is effective for monitoring and evaluating a traction-network system.

Remote Visualization of High-Speed Rail Power Quality Monitoring

The visualization techniques were explored for power quality monitoring.And remote visualization solutions were proposed for highspeed rail power quality monitoring.Taking the Beijing-Shanghai highspeed rail power monitoring as a study case,a remote visualization client,based on our proposed solutions,was developed for high-speed rail power quality monitoring to efficiently support power quality data analysis of the electricity business.The solutions collected data from monitoring stations deployed along the high-speed rail route and visualized the data set with a variety of visualization technologies to alert the specific stations of catastrophic events.The proposed solutions have been proved to be effective in supporting decision-making for the railway power scheduling and providing diagnosis information for quickly spotting any possible runtime failure in operation.

The New Brazilian Power Quality Standard and a Low Cost Device Meter

This paper presents an overview about the new Brazilian Power Quality Standard and provides a low cost device PQ meter, developed and implemented to assist the national campaign to assess the Brazilian power quality indices, unknown until now. This work contributes with the search of a low cost devices PQ meter for a cost sensitive market, and introduces the new Brazilian Power Quality Standard to the international community.

The Research to Quality Supervision and Management of Power Enterprises

Intensive in-depth development of resources, centralized purchasing and gradually expand under the category of environment, this paper studies how to use information technology tools to construction quality supervision and management system that focuses on the quality of supervision and project management, quality control process management, quality monitoring statistics report management, platform management-related content in four areas. Through the construction quality supervision and management system, to better enhance the quality of electric power enterprise management level, to ensure that the material quality, quantity of time and supplies. strengthening quality supervision and management can not only effectively reduce material procurement costs, but also enhance the competitiveness of enterprises.

Economic Implications of Poor Power Quality

Poor power quality is really becoming an increasing phenomenon. Studies revealed that most companies, particularly multinationals in Nigeria, do not pay enough attention to the effects of poor power quality on their plant and equipment, and let the economic implications alone. The result is high production and maintenance cost. Findings also revealed that these companies loose an average of $50,000 annually owing to equipment damage （such as variable speed drives） caused by poor power quality. This paper focuses on the need for continuous monitoring and management of poor power quality disturbance parameters and the cost for economic implications of no addressing power quality issues.

基于Powerlogic的船舶电力监视系统

本文结合船舶电力系统控制实验室,利用PowerLogic软件实现对船舶电力系统的电力参数监测。介绍了船舶电力监视系统的构成与软件设计,在交流380V/50Hz电力实验室环境下进行了运行,分析了船舶电力系统运行的谐波情况,该系统可以有效地监视船舶电力系统的一些参数,提高了船舶电站电能质量的管理能力。

VPLS Based Quality and Cost Control for Tennessee Eastman Process

Product quality and operation cost control obtain increasing emphases in modern chemical system engineering. To improve the fault detection power of the partial least square (PLS) method for quality control, a new QRPV statistic is proposed in terms of the VP (variable importance in projection) indices of monitored process variables, which is significantly advanced over and different from the conventional Q statistic. QRPV is calculated only by the residuals of the remarkable process variables (RPVs). Therefore, it is the dominant relation between quality and RPV not all process variables (as in the case of the conventional PLS) that is monitored by this new VP-PLS (VPLS) method. The combination of QRPV and T2 statistics is applied to the quality and cost control of the Tennessee Eastman (TE) process, and weak faults can be detected as quickly as possible. Consequently, the product quality of TE process is guaranteed and operation costs are reduced.

Analysis of Condition-Based Maintenance for High-Valtage Electric Power

The development process of high-voltage electric power equipment maintenance was introduced. It is pointed out that the trend of high-voltage electric power equipment maintenance is so called condition-based maintenance. With the development of computer technology and sensors, on-line monitoring of high-voltage electric power equipment has developed rapidly. By introducing the main principle of Schering bridge to measure tanδ, the way of on-line monitoring of high-voltage electric power equipment was explained. Difference methods of on-line monitoring of insulation parameters for 35 kV substation were discussed. Finally, the shortcomings as well as its tendency of on-line monitoring were analyzed.

Site Characterization Index for Continuous Power Quality Monitoring Based on Higher-order Statistics

The high penetration of distributed generation(DG)has set up a challenge for energy management and consequently for the monitoring and assessment of power quality(PQ).Besides,there are new types of disturbances owing to the uncontrolled connections of non-linear loads.The stochastic behaviour triggers the need for new holistic indicators which also deal with big data of PQ in terms of compression and scalability so as to extract the useful information regarding different network states and the prevailing PQ disturbances for future risk assessment and energy management systems.Permanent and continuous monitoring would guarantee the report to claim for damages and to assess the risk of PQ distortions.In this context,we propose a measurement method that postulates the use of two-dimensional(2D)diagrams based on higher-order statistics(HOSs)and a previous voltage quality index that assesses the voltage supply waveform in a continous monitoring campaign.Being suitable for both PQ and reliability applications,the results conclude that the inclusion of HOS measurements in the industrial metrological reports helps characterize the deviations of the voltage supply waveform,extracting the individual customers’pattern fingerprint,and compressing the data from both time and spatial aspects.The method allows a continuous and robust performance needed in the SG framework.Consequently,the method can be used by an average consumer as a probabilistic method to assess the risk of PQ deviations in site characterization.

Protecting Water Quality and Public Health Using a Smart Grid

After the attacks on September 11, 2001 and the follow-up risk assessments by utilities across the United States, securing the water distribution system against malevolent attack became a strategic goal for the U.S. Environmental Protection Agency. Following 3 years of development work on a Contamination Warning System (CWS) at the Greater Cincinnati Water Works, four major cities across the United States were selected to enhance the CWS development conducted by the USEPA. One of the major efforts undertaken was to develop a process to seamlessly process “Big Data” sets in real time from different sources (online water quality monitoring, consumer complaints, enhanced security, public health surveillance, and sampling and analysis) and graphically display actionable information for operators to evaluate and respond to appropriately. The most significant finding that arose from the development and implementation of the “dashboard” were the dual benefits observed by all four utilities: the ability to enhance their operations and improve the regulatory compliance of their water distribution systems. Challenge: While most of the utilities had systems in place for SCADA, Work Order Management, Laboratory Management, 311 Call Center Management, Hydraulic Models, Public Health Monitoring, and GIS, these systems were not integrated, resulting in duplicate data entry, which made it difficult to trace back to a “single source of truth.” Each one of these data sources can produce a wealth of raw data. For most utilities, very little of this data is being translated into actionable information as utilities cannot overwhelm their staffs with manually processing the mountains of data generated. Instead, utilities prefer to provide their staffs with actionable information that is easily understood and provides the basis for rapid decision-making. Smart grid systems were developed so utilities can essentially find the actionable needle in the haystack of data. Utilities can then focus on rapidly evaluating the new information, compare it known activities occurring in the system, and identify the correct level of response required. Solution: CH2M HILL was engaged to design, implement, integrate, and deploy a unified spatial dashboard/smart grid system. This system included the processes, technology, automation, and governance necessary to link together the disparate systems in real time and fuse these data streams to the GIS. The overall solution mapped the business process involved with the data collection, the information flow requirements, and the system and application requirements. With these fundamentals defined, system integration was implemented to ensure that the individual systems worked together, eliminating need for duplicate data entry and manual processing. The spatial dashboard was developed on top of the integration platform, allowing the underlying component data streams to be visualized in a spatial setting. Result: With the smart grid system in place, the utilities had a straightforward method to determine the true operating conditions of their systems in real time, quickly identify a potential non-compliance problem in the early stages, and improve system security. The smart grid system has freed staff to focus on improving water quality through the automation of many mundane daily tasks. The system also plays an integral role in monitoring and optimizing the utilities’ daily operations and has been relied on during recovery operations, such as those in response to recent Superstorm Sandy. CH2M HILL is starting to identify the processes needed to expand the application of the smart grid system to include real-time water demands using AMI/AMR and real-time energy loads from pumping facilities. Once the smart grid system has been expanded to include Quality-Quantity-Energy, CH2M HILL can apply optimization engines to provide utility operations staffs with a true optimization tool for their water systems.

基于特征集重构与多标签分类模型的谐波源定位方法

传统基于谐波状态估计的谐波源定位方法需要专门的同步相量量测装置,工程应用受到限制。为此,基于电能质量监测装置所采集的非同步量测数据,提出了基于特征集重构与多标签分类模型的谐波源定位方法。利用监测数据的充分统计量来挖掘量测时段的谐波信息,同时利用标签特定特征学习算法重构特征集,从而消除冗余特征以及无关特征对于谐波源定位精度的影响;提出基于邻接矩阵以及灵敏度分析的测点配置方法,结合电路网络拓扑信息实现测点的优化配置;提出基于改进极限学习机的谐波源定位方法,该方法以重构特征集为输入,建立多标签分类模型,实现谐波源定位。通过仿真与算例分析,验证了所提方法的可行性及有效性。

基于DBSCAN聚类和区间回归的多谐波责任划分

在背景谐波阻抗变化和背景谐波电压波动的情况下,传统谐波责任划分方法难以适用于现有的统计型谐波监测数据,提出一种背景谐波变化下基于监测数据的多谐波责任划分方法。首先,构建谐波监测数据区间样本集,并建立背景谐波变化下的多谐波源区间谐波责任划分数学模型;其次,利用基于密度的聚类算法(DBSCAN)将采集到的统计型谐波数据集以簇为评价周期进行场景划分,并采用滑窗动态相关性分析方法筛选出满足线性关系阈值要求的数据;最后,利用基于参数化回归算法(PM)的区间线性进行方程参数计算并获取最佳样本划分方案,在构造的区间谐波责任划分基础上计算中长期时间范畴的谐波责任。利用实际电网中的谐波监测数据对所提方法进行验证,验证了该方法能利用现有的统计型谐波监测数据在背景谐波变化的情况下对每个谐波源进行合理时间尺度的谐波责任划分,可为实际电力系统运行过程中的多谐波责任划分提供一种新的思路。

基于多源数据的馈线谐波频谱估计方法

随着分布式电源和非线性负荷的投运规模不断增加,电网谐波污染愈加严重和复杂,有必要对各馈线谐波电流进行监测。但基于经济性考虑,对变电站所有馈线均进行谐波电流监测并不可行。针对上述问题,提出了基于多源数据的馈线谐波频谱估计方法。该方法基于电网现有电能质量监测系统、调度系统、营销业务应用系统等多源数据,只需对母线谐波电压和进线谐波电流开展监测,即可估计出变电站所有馈线的谐波电流情况。首先,根据馈线谐波电流的相量运算关系和功率关系构建馈线谐波频谱估计的目标函数。其次,基于多源数据利用改进粒子群算法求解目标函数,进而得到各馈线的各次谐波电流含有率及馈线谐波电流间的相角差,实现了各馈线谐波电流频谱的估计。最后,通过仿真算例和实测算例验证了方法的可行性。算例表明该方法仅需在变电站母线处安装一台电能质量监测终端,结合现有业务系统的基本电气数据等信息,可实现馈线谐波频谱的估计,有助于节约变电站监测装置的配置成本。

基于层次分析法的微电网并网运行电能质量安全监测模型

为了满足日益增长的电力能源需求,微电网并网运行是电力系统的主要发展趋势,其虽然能够提升电力能源的供应,但难以保证供电质量,不利于电力系统的后续发展。该现象的产生主要是由于分布式电源出力具有随机性与不稳定性,会对供电质量造成直接影响。对此,提出基于层次分析法的微电网并网运行电能质量安全监测模型构建研究。深入分析电能质量干扰源,以此为基础,选取适当的电能质量安全监测指标,应用层次分析法计算电能质量安全监测指标权重数值,确定电能质量安全监测模型,制定电能质量安全判定规则,从而实现电能质量安全的准确监测。实验数据显示:构建模型应用后,电能质量安全监测指标完整度最大值为96%,电能质量安全监测结果与实际结果一致,充分证实了构建模型具备更好的电能质量安全监测效果。

基于PROFINET通讯的WK电铲智能电力监测系统

为了能够实时监测供电电能质量,在电铲上增加了智能电力监测系统。介绍了电力监测系统的硬件构成及软件设计。该系统以PLC控制技术为基础,通过西门子PROFINET通讯技术实时采集供电电源的数据,对数据进行分析和诊断,并在上位机上显示,从而实现了对WK电铲的智能电力监测。