Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

Power supply arm protection scheme of high-speed railway based on wide-area current differential

When fault occurs on cross-coupling autotransformer(AT)power supply traction network,the up-line and down-line feeder circuit breakers in the traction substation trip at the same time without selectivity,which leads to an extended power failure.Based on equivalent circuit and Kirchhoff’s current law,the feeder current characteristic in the substation,AT station and sectioning post when T-R fault,F-R fault,and T-F fault occur are analyzed and their expressions are obtained.When the traction power supply system is equipped with wide-area protection measurement and control system,the feeder protection device in each station collects the feeder currents in other two stations through the wide-area protection channel and a wide-area current differential protection scheme based on the feeder current characteristic is proposed.When a short-circuit fault occurs in the power supply arm,all the feeder protection devices in each station receive the feeder currents with time stamp in other two stations.After data synchronous processing and logic judgment,the fault line of the power supply arm can be identified and isolated quickly.The simulation result based on MATLAB/Simulink shows that the power supply arm protection scheme based on wide-area current differential has good fault discrimination ability under different fault positions,transition resistances,and fault types.The verification of measured data shows that the novel protection scheme will not be affected by the special working conditions of the electrical multiple unit(EMU),and reliability,selectivity,and rapidity of relay protection are all improved.

Smart Grid Wide-Area Transmission System Visualization

The installation of vast quantities of additional new sensing and communication equipment, in conjunction with building the computing infrastructure to store and manage data gathered by this equipment, has been the fi rst step in the creation of what is generically referred to as the "smart grid" for the electric transmission system. With this enormous capital investment in equipment having been made, attention is now focused on developing methods to analyze and visualize this large data set. The most direct use of this large set of new data will be in data visualization. This paper presents a survey of some visualization techniques that have been deployed by the electric power industry for visualizing data over the past several years. These techniques include pie charts, animation, contouring, time-varying graphs, geographic-based displays, image blending, and data aggregation techniques. The paper then emphasizes a newer concept of using word-sized graphics called sparklines as an extremely eff ective method of showing large amounts of timevarying data.

MEC-Empowered Non-Terrestrial Network for 6G Wide-Area Time-Sensitive Internet of Things

In the upcoming sixth-generation(6G)era,the demand for constructing a wide-area time-sensitive Internet of Things(IoT)continues to increase.As conventional cellular technologies are difficult to directly use for wide-area time-sensitive IoT,it is beneficial to use non-terrestrial infrastructures,including satellites and unmanned aerial vehicles(UAVs).Thus,we can build a non-terrestrial network(NTN)using a cell-free architecture.Driven by the time-sensitive requirements and uneven distribution of IoT devices,the NTN must be empowered using mobile edge computing(MEC)while providing oasisoriented on-demand coverage for devices.Nevertheless,communication and MEC systems are coupled with each other under the influence of a complex propagation environment in the MEC-empowered NTN,which makes it difficult to coordinate the resources.In this study,we propose a process-oriented framework to design communication and MEC systems in a time-division manner.In this framework,large-scale channel state information(CSI)is used to characterize the complex propagation environment at an affordable cost,where a nonconvex latency minimization problem is formulated.Subsequently,the approximated problem is provided,and it can be decomposed into sub-problems.These sub-problems are then solved iteratively.The simulation results demonstrated the superiority of the proposed process-oriented scheme over other algorithms,implied that the payload deployments of UAVs should be appropriately predesigned to improve the efficiency of using resources,and confirmed that it is advantageous to integrate NTN with MEC for wide-area time-sensitive IoT.

Positioning with Wide-Area GNSS Networks: Concept and Application

The use of Global Navigation Satellite Systems (GNSS) for positioning has revolutionized the way location data is be- ing collected. The NAVigation System with Time And Ranging Global Positioning System (GPS), which is a principal component of the global navigation satellite system (GNSS);is a satellite-based radio navigation system that provides positions of points of interest and time information to users. GPS positional accuracy can be improved by using differential corrections obtained through a technique called Differential GPS (DGPS), which is known to provide the most accurate positioning results. Differential correction can be applied in real time at the data collection phase or in the of- fice, at the post-processing phase. DGPS is generally used for positioning purposes through static or kinematics GPS surveys. In static GPS surveys, one receiver is placed at a point whose coordinates are known and the other receiver is placed over a point whose coordinates are desired. In kinematic surveys, one receiver remains at one point (base station) normally with known coordinates, and the other receiver (rover) moves from point to point in the project area. Kinematic surveys in which points positions are computed on-the-fly (OTF) are known as real-time kinematic (RTK). RTK surveys provide real-time locations of points of interest needed in many applications. Positioning with wide-area GNSS networks is basically based on the DGPS and RTK concepts. Observables from a network of a finite number of GPS receivers over an area are processed by a server at a central location (network server) and made available to the users of the network later or in real-time through radio-based, satellite, or wireless communications. This article provides a review of the concept and application of positioning with wide-area GNSS networks.

Automatic measurement of three-phase contact angles in pore throats based on digital images

With the help of digital image processing technology, an automatic measurement method for the three-phase contact angles in the pore throats of the microfluidic model was established using the microfluidic water flooding experiment videos as the data source. The results of the new method were verified through comparing with the manual measurement data.On this basis, the dynamic changes of the three-phase contact angles under flow conditions were clarified by the contact angles probability density curve and mean value change curve. The results show that, for water-wetting rocks, the mean value of the contact angles is acute angle during the early stage of the water flooding process, and it increases with the displacement time and becomes obtuse angle in the middle-late stage of displacement as the dominant force of oil phase gradually changes from viscous force to capillary force. The droplet flow in the remaining oil occurs in the central part of the pore throats, without three-phase contact angle. The contact angles for the porous flow and the columnar flow change slightly during the displacement and present as obtuse angles in view of mean values, which makes the remaining oil poorly movable and thus hard to be recovered. The mean value of the contact angle for the cluster flow tends to increase in the flooding process, which makes the remaining oil more difficult to be recovered. The contact angles for the membrane flow are mainly obtuse angles and reach the highest mean value in the late stage of displacement, which makes the remaining oil most difficult to be recovered. After displacement, the remaining oils under different flow regimes are just subjected to capillary force, with obtuse contact angles, and the wettability of the pore throat walls in the microfluidic model tends to be oil-wet under the action of crude oil.

基于相对增益和改进粒子群算法的PSS与直流调制协调策略

现有电力系统稳定器(power system stabilizer,PSS)和直流调制多使用本地信号作为控制器反馈输入信号,控制器间的交互作用可能降低甚至破坏系统稳定性。提出了一种基于广域测量信号的PSS与直流调制协调策略,首先通过留数法选择对于振荡模态可观性较强的广域信号作为阻尼控制器备选反馈信号;其次通过相对增益方法选择使PSS和直流调制交互影响最小的备选信号作为最佳反馈信号;而后设计分散控制器,并运用基于混沌和差分进化的混合粒子群优化算法对PSS和直流调制控制器参数进行协调优化。最后,通过EPRI 36节点系统仿真验证了协调策略的正确性和有效性。

头穴丛刺配合蜡疗对痉挛型脑瘫患者运动功能的影响

目的观察头穴丛刺配合蜡疗对脑瘫患者运动功能的影响。方法将符合纳入标准的痉挛型脑瘫患者40例,随机分为对照组与观察组,每组20例。对照组采用头穴丛刺长留针疗法,并给予针对痉挛型脑瘫患者的上田法及各项常规康复训练;观察组在对照组的基础上配合蜡疗。每日1次,共治疗8星期。治疗前后采用粗大运动功能量表(GMFM-88)、改良Ashworth量表评分进行运动功能评定。结果两组组内治疗前后GMFM-88评分比较,差异均具有统计学意义(P<0.05);两组治疗后GMFM-88评分比较,差异有统计学意义(P<0.05)。观察组治疗前后改良Ashworth量表评分比较,差异有统计学意义(P<0.05);对照组治疗前后改良Ashworth量表评分比较,差异无统计学意义(P>0.05);两组治疗后改良Ashworth量表评分比较,差异有统计学意义(P<0.05)。结论在常规康复训练基础上,头穴丛刺配合蜡疗对痉挛型脑瘫患者的肌张力及运动功能的恢复效果明显,有益于促进脑瘫患者的正常发育。

多时滞广域测量电力系统稳定分析与协调控制器设计

根据电力系统存在时滞的差异性,将控制器信号分为本地无时滞控制输入信号和广域异地多时滞控制输入信号两部分,建立了多时滞电力系统的模型。运用Lyapunov-Krasovskii泛函理论推导出了含有时滞分量的线性多时滞电力系统稳定判据,将控制问题转换为线性矩阵不等式的可行性问题,并采用模型降阶方法对原系统进行降阶,实现了含有多个时滞的广域输出反馈控制,并计算出了能够使闭环电力系统稳定的最大时滞时间。讨论了系统稳定判据中时滞分量与广域控制器参数之间的关系,以及对区域间振荡的控制效果。最后以两区域四机系统为例,用时域仿真的结果说明了本文所提出的多时滞控制方法的有效性。

强迫功率振荡源的在线定位分析技术

强迫功率振荡源的在线定位对电网安全稳定运行具有至关重要的作用。基于相量测量装置(phasor measurement unit,PMU)的实测数据和同步发电机转子运动方程,给出振荡过程中发电机机械输入功率波动的计算方法。通过对振荡过程中发电机机械输入功率波动、电气输出功率波动、转速(频率)波动的相位关系的理论分析,给出强迫功率振荡的在线监测分析方法。如果原动机不是强迫扰动源,发电机组因响应外界扰动而处于振荡过程中时,机械功率的波动相位滞后于电气功率的波动相位。由于引进PMU实测数据,所提方法可实现各个发电机组独立分析、相互解耦,避免了引入全网模型带来的分析误差和可靠性降低,减少了在线监测分析的复杂程度。实际算例表明,所提方法能有效判断同步发电机是否为强迫功率振荡源,为低频振荡的分析、控制提供可靠参考。

Iterative Learning Disturbance Observer Based Attitude Stabilization of Flexible Spacecraft Subject to Complex Disturbances and Measurement Noises

To realize high-precision attitude stabilization of a flexible spacecraft in the presence of complex disturbances and measurement noises,an iterative learning disturbance observer(ILDO)is presented in this paper.Firstly,a dynamic model of disturbance is built by augmenting the integral of the lumped disturbance as a state.Based on it,ILDO is designed by introducing iterative learning structures.Then,comparative analyses of ILDO and traditional disturbance observers are carried out in frequency domain.It demonstrates that ILDO combines the advantages of high accuracy in disturbance estimation and favorable robustness to measurement noise.After that,an ILDO based composite controller is designed to stabilize the spacecraft attitude.Finally,the effectiveness of the proposed control scheme is verified by simulations.

An Internet of Energy Things Based on Wireless LPWAN

Under intense environmental pressure, the global energy sector is promoting the integration of renewable energy into interconnected energy systems. The demand-side management （DSM） of energy systems has drawn considerable industrial and academic attention in attempts to form new flexibilities to respond to variations in renewable energy inputs to the system. However, many DSM concepts are still in the experimental demonstration phase. One of the obstacles to DSM usage is that the current information infrastructure was mainly designed for centralized systems, and does not meet DSM requirements. To overcome this barrier, this paper proposes a novel information infrastructure named the lnternet of Energy Things （IoET） in order to make DSM practicable by basing it on the latest wireless communication technology： the low-power wide-area network （LPWAN）. The primary advantage of LPWAN over general packet radio service （GPRS） and area Internet of Things （loT） is its wide-area coverage, which comes with minimum power consumption and maintenance costs. Against this background, this paper briefly reviews the representative LPWAN tech- nologies of narrow-band Internet of Things （NB-IoT） and Long Range （LORa） technology, and compares them with GPRS and area IoT technology. Next, a wireless-to-cloud architecture is proposed for the IoET, based on the main technical features of LPWAN. Finally, this paper looks forward to the potential of IoET in various DSM application scenarios.

Power System Resiliency and Wide Area Control Employing Deep Learning Algorithm

The power transfer capability of the smart transmission gridconnected networks needs to be reduced by inter-area oscillations.Due to the fact that inter-area modes of oscillations detain and make instability of power transmission networks.This fact is more noticeable in smart grid-connected systems.The smart grid infrastructure has more renewable energy resources installed for its operation.To overcome this problem,a deep learning widearea controller is proposed for real-time parameter control and smart power grid resilience on oscillations inter-area modes.The proposed Deep Wide Area Controller(DWAC)uses the Deep Belief Network(DBN).The network weights are updated based on real-time data from Phasor measurement units.Resilience assessment based on failure probability,financial impact,and time-series data in grid failure management determine the norm H2.To demonstrate the effectiveness of the proposed framework,a time-domain simulation case study based on the IEEE-39 bus system was performed.For a one-channel attack on the test system,the resiliency index increased to 0.962,and inter-area dampingξwas reduced to 0.005.The obtained results validate the proposed deep learning algorithm’s efficiency on damping inter-area and local oscillation on the 2-channel attack as well.Results also offer robust management of power system resilience and timely control of the operating conditions.

Communication Networking Schemes for Wide Area Electric Vehicle Energy Service Network

Electric vehicles (EVs) are an emerging type of mobile intelligent power consumption devices in Smart Grid as new green transport tools. In order to provide a powerful automation and intelligence support for wide area electric vehicles energy service network, we analyze the network infrastructure and communications demands of various terminals, devices and monitoring systems distributed in wide area electric vehicle energy service network. According to interactive user services scenarios and energy operations intelligent monitoring, we propose multimode communication integration architecture for wide area electric vehicle energy service network by means of the fusion of the Internet of Things (IoT) technology. Then, we design different networking schemes in access networks and backbone transmission networks meeting multi-scene and multi-operation interaction requirements. The networking schemes will provide efficient technical support to implement intelligent, cross-regional, interactive energy services for electric vehicle users.

NOVEL METHOD OF MOVING TARGET DETECTION FOR DUAL-CHANNEL WAS RADAR BASED ON COMPRESSED SENSING

We propose a ground moving target detection method for dual-channel Wide Area Surveillance(WAS) radar based on Compressed Sensing(CS).Firstly,the method of moving target detection of the WAS radar is studied.In order to reduce the sample data quantity of the radar,the echo data is randomly sampled in the azimuth direction,then,the matched filter is used to perform the range direction focus.We can use the compressive sensing theory to recover the signal in the Doppler domain.At last,the phase difference between the two channels is compensated to suppress the clutter.The result of the simulated data verifies the effectiveness of the proposed method.

Environmental Radiation Measurement and Assessment of Natural Radioactivity in Soil, Water and Vegetation

Environmental radioactivity is produced by radioactive materials in the human environment. While some radioisotopes, such as strontium-90 (90Sr) and technetium-99 (99Tc), are only found on Earth as a result of human activity, and some, like potassium-40 (40K), are only present due to natural processes, a few isotopes, e.g. tritium (3H), result from both natural processes and human activities. The concentration and location of some natural isotopes, particularly uranium-238 (238U), can be affected by human activity because of the constant exposure of Human beings to radiation caused by terrestrial, extra-terrestrial and anthropogenic radio nuclides, it is necessary to determine and estimate the activity of various radio nuclides in environmental media such as vegetation, soil, and water. In the present research, the activities of 226Ra, 232Th and 40K are measured in soil, vegetation and water samples, collected from Yangdong District, Yangxi County, and Yangjiang County of Guangdong Province, China using an HPGe based gamma spectrometry system. The measured mean activity of 226Ra, 232Th and 40K in soil samples was found to be 31.19 ± 1.2, 47.00 ± 2.30 and 589.31 ± 17.52 Bqkg-1, respectively. The measured mean activity of these radionuclides in all water samples was found to be below minimum detectable activity. The measured mean activity of 226Ra, 232Th and 40K in vegetation samples was 19.92 ± 3.09, 25.36 ± 8.11 and 4982.94 ± 85.68 Bqkg-1, respectively. No anthropogenic 137Cs was detected in these environmental samples. Mean radium equivalent activity (Raeq), external radiation hazard index (Hex), internal radiation hazard index (Hin) and absorbed dose rate (D) for the area under study were determined as 142.92 Bqkg-1, 0.38, 0.47 and 66.47 nGyh-1, respectively. The annual effective dose equivalent (AEDE) varied in the range from 0.03 to 0.12 mSvy-1. It is concluded that the surveyed area do not pose any significant radiological risk to the population and environment.

PMU Based Monitoring and Estimation of Inter-area Power Oscillation for Singapore-Malaysia Interconnection Power System

This paper proposes a PMU （phasor measurement unit） based monitoring and estimation scheme of power system small-signal stability in Singapore-Malaysia interconnection power system through a 50-Hz and 500 kV transmission line. Two PMUs are installed in the power system interconnection network of Singapore-Malaysia. One PMU is located in Singapore and the other one in Malaysia （Penang）. Both PMUs measure the single-phase voltage phasor. The data filtering technique based on FFT （Fast Fourier Transform） is employed to extract oscillation data for single mode. Finally, some analysis results of monitoring and estimation of Singapore-Malaysia interconnected power system based on application practice of the CampusWAMS are presented and analyzed.

Dynamic user-centric multi-dimensional resource allocation for a wide-area coverage signaling cell based on DQN

The rapid development of communications industry has spawned more new services and applications.The sixth-generation wireless communication system(6G)network is faced with more stringent and diverse requirements.While ensuring performance requirements,such as high data rate and low latency,the problem of high energy consumption in the fifth-generation wireless communication system(5G)network has also become one of the problems to be solved in 6G.The wide-area coverage signaling cell technology conforms to the future development trend of radio access networks,and has the advantages of reducing network energy consumption and improving resource utilization.In wide-area coverage signaling cells,on-demand multi-dimensional resource allocation is an important technical means to ensure the ultimate performance requirements of users,and its effect will affect the efficiency of network resource utilization.This paper constructs a user-centric dynamic allocation model of wireless resources,and proposes a deep Q-network based dynamic resource allocation algorithm.The algorithm can realize dynamic and flexible admission control and multi-dimensional resource allocation in wide-area coverage signaling cells according to the data rate and latency demands of users.According to the simulation results,the proposed algorithm can effectively improve the average user experience on a long time scale,and ensure network users a high data rate and low energy consumption.

Enhancing the precision of phase estimation by weak measurement and quantum measurement reversal

The enhancement of the precision of phase estimation in quantum metrology is investigated by employing weak measurement （WM） and quantum measurement reversal （QMR）. We derive the exact expressions of the optimal quantum Fisher information （QFI） and success probability of phase estimation for an exactly solving model consisting of a qubit interacting with a structured reservoir. We show that the QFI can be obviously enhanced by means of the WM and QMR in different regimes. In addition, we also show that the magnitude of the decoherence involved in the WM and QMR can be a general complex number, which extends the applicable scope of the WM and QMR approach.

A Fundamental Study on Multi-agent Pedestrian Model Based on Risk Avoidance Behavior during Road Blockage and Evacuation Simulation of Regional Urban Disaster

Regional cities in Japan are at the risk of experiencing big fire accidents or earthquakes every day.However,neither the number nor the capacity of shelters has increased because local governments might not consider them owing to budget shortfall.By contrast,wide-area evacuation simulations can easily provide an antagonizing image of regional urban disasters.After a disaster,the city collapses and the evacuation routes are closed;consequently,evacuees feel anxious and they cannot move as usual.This anxiety behavior has not been considered in previous related studies and simulations.In this study,a wide-area evacuation simulation is developed;this model can not only calculate the possibility of blocking escape routes when the city is broken but also provide safe and more realistic evacuation plans before a disaster occurs by incorporating into the simulation the risk avoidance behaviors of evacuees from road blockage,such as“the route re-seeking behavior”and“the shelter re-selecting behavior”.