COMPARISON AND EVALUATION OF CURRENT REFERENCE GENERATION STRATEGIES FOR ACTIVE POWER FILTERS IN THREE-PHASE FOUR-WIRE SYSTEMS

For three phase four-wire active power filters （APFs）, several typical power theories and corresponding current reference generation strategies are induced, p-q, d-q, unify power factor （UPF） and instantaneous active current （IAC） methods are analyzed and compared with each other. The interpretation of active and reactive currents in non-sinusoidal and unbalanced three-phase four-wire systems is given based on the generalized instantaneous reactive power theory. The performance and the characteristic are evaluated, and the application conditions of current reference generation strategies are concluded. Simulation results under different source voltages and loads verify the evaluation result.

IoT-Enabled Plant Monitoring System with Power Optimization and Secure Authentication

Global food security is a pressing issue that affects the stability and well-being of communities worldwide.While existing Internet of Things(IoT)enabled plant monitoring systems have made significant strides in agricultural monitoring,they often face limitations such as high power consumption,restricted mobility,complex deployment requirements,and inadequate security measures for data access.This paper introduces an enhanced IoT application for agricultural monitoring systems that address these critical shortcomings.Our system strategically combines power efficiency,portability,and secure access capabilities,assisting farmers in monitoring and tracking crop environmental conditions.The proposed system includes a remote camera that captures images of surrounding plants and a sensor module that regularly monitors various environmental factors,including temperature,humidity,and soil moisture.We implement power management strategies to minimize energy consumption compared to existing solutions.Unlike conventional systems,our implementation utilizes the Amazon Web Services(AWS)cloud platform for reliable data storage and processing while incorporating comprehensive security measures,including Two-Factor Authentication(2FA)and JSON Web Tokens(JWT),features often overlooked in current agricultural IoT solutions.Users can access this secure monitoring system via a developed Android application,providing convenient mobile access to the gathered plant data.We validate our system’s advantages by implementing it with two potted garlic plants on Okayama University’s rooftop.Our evaluation demonstrates high sensor reliabil-ity,with strong correlations between sensor readings and reference data,achieving determination coefficients(R2)of 0.979 for temperature and 0.750 for humidity measurements.The implemented power management strategies extend battery life to 10 days on a single charge,significantly outperforming existing systems that typically require daily recharging.Furthermore,our dual-layer security implementation utilizing 2FA and JWT successfully protects sensitive agricultural data from unauthorized access.

Three-Phase Unbalance Prediction of Electric Power Based on Hierarchical Temporal Memory

The difference in electricity and power usage time leads to an unbalanced current among the three phases in the power grid.The three-phase unbalanced is closely related to power planning and load distribution.When the unbalance occurs,the safe operation of the electrical equipment will be seriously jeopardized.This paper proposes a Hierarchical Temporal Memory(HTM)-based three-phase unbalance prediction model consisted by the encoder for binary coding,the spatial pooler for frequency pattern learning,the temporal pooler for pattern sequence learning,and the sparse distributed representations classifier for unbalance prediction.Following the feasibility of spatial-temporal streaming data analysis,we adopted this brain-liked neural network to a real-time prediction for power load.We applied the model in five cities(Tangshan,Langfang,Qinhuangdao,Chengde,Zhangjiakou)of north China.We experimented with the proposed model and Long Short-term Memory(LSTM)model and analyzed the predict results and real currents.The results show that the predictions conform to the reality;compared to LSTM,the HTM-based prediction model shows enhanced accuracy and stability.The prediction model could serve for the overload warning and the load planning to provide high-quality power grid operation.

Electrical characteristics of new three-phase traction power supply system for rail transit

A novel three-phase traction power supply system is proposed to eliminate the adverse effects caused by electric phase separation in catenary and accomplish a unifying manner of traction power supply for rail transit.With the application of two-stage three-phase continuous power supply structure,the electrical characteristics exhibit new features differing from the existing traction system.In this work,the principle for voltage levels determining two-stage network is dissected in accordance with the requirements of traction network and electric locomotive.The equivalent model of three-phase traction system is built for deducing the formula of current distribution and voltage losses.Based on the chain network model of the traction network,a simulation model is established to analyze the electrical characteristics such as traction current distribution,voltage losses,system equivalent impedance,voltage distribution,voltage unbalance and regenerative energy utilization.In a few words,quite a lot traction current of about 99%is undertaken by long-section cable network.The proportion of system voltage losses is small attributed to the two-stage three-phase power supply structure,and the voltage unbal-ance caused by impedance asymmetry of traction network is less than 1‰.In addition,the utilization rate of regenerative energy for locomotive achieves a significant promotion of over 97%.

Predictive direct power control of three-phase PWM rectifier based on TOGI grid voltage sensor free algorithm

In predictive direct power control(PDPC)system of three-phase pulse width modulation(PWM)rectifier,grid voltage sensor makes the whole system more complex and costly.Therefore,third-order generalized integrator(TOGI)is used to generate orthogonal signals with the same frequency to estimate the grid voltage.In addition,in view of the deviation between actual and reference power in the three-phase PWM rectifier traditional PDPC strategy,a power correction link is designed to correct the power reference value.The grid voltage sensor free algorithm based on TOGI and the corrected PDPC strategy are applied to three-phase PWM rectifier and simulated on the simulation platform.Simulation results show that the proposed method can effectively eliminate the power tracking deviation and the grid voltage.The effectiveness of the proposed method is verified by comparing the simulation results.

Three-Phase Optimal Power Flow for Study of PV Plant Distributed Impact on Distribution Systems

This paper presents a TOPF （three-phase optimal power flow） model that represents photovoltaic systems. The PV plant is modeled in the TOPF as active and reactive power source. Reactive power can be generated or absorbed using the available capacity and the adjustable power factor of the inverter. The reduction of unbalance voltage and losses in the distribution systems is obtained by actions of reactive power control of the inverter. The TOPF is formulated by current balance equations and the PV systems are modeled via an equivalent circuit. The primal-dual interior point method is used to obtain the optimal operating points for the systems for different scenarios of solar irradiance and temperature, thus providing a detailed view of the impact of photovoltaic distributed generation.

罗克韦尔自动化Power Monitor II电力监控器

介绍了一种集检测、分析、记录、控制、通信于一体的PowerMonitorII电力监控器的结构、功能及相关的监控管理软件 ,和以其为主组成的电力质量管理系统的功能。

Power Line Monitoring Data Transmission Using Wireless Sensor Network

The WSN used in power line monitoring is long chain structure, and the bottleneck near the Sink node is more obvious. In view of this, A Sink nodes’ cooperation mechanism is presented. The Sink nodes from different WSNs are adjacently deployed. Adopting multimode and spatial multiplexing network technology, the network is constructed into multi-mode-level to achieve different levels of data streaming. The network loads are shunted and the network resources are rationally utilized. Through the multi-sink nodes cooperation, the bottlenecks at the Sink node and its near several jump nodes are solved and process the competition of communication between nodes by channel adjustment. Finally, the paper analyzed the method and provided simulation experiment results. Simulation results show that the method can solve the funnel effect of the sink node, and get a good QoS.

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 Feature Weighted Mixed Naive Bayes Model for Monitoring Anomalies in the Fan System of a Thermal Power Plant

With the increasing intelligence and integration,a great number of two-valued variables(generally stored in the form of 0 or 1)often exist in large-scale industrial processes.However,these variables cannot be effectively handled by traditional monitoring methods such as linear discriminant analysis(LDA),principal component analysis(PCA)and partial least square(PLS)analysis.Recently,a mixed hidden naive Bayesian model(MHNBM)is developed for the first time to utilize both two-valued and continuous variables for abnormality monitoring.Although the MHNBM is effective,it still has some shortcomings that need to be improved.For the MHNBM,the variables with greater correlation to other variables have greater weights,which can not guarantee greater weights are assigned to the more discriminating variables.In addition,the conditional P(x j|x j′,y=k)probability must be computed based on historical data.When the training data is scarce,the conditional probability between continuous variables tends to be uniformly distributed,which affects the performance of MHNBM.Here a novel feature weighted mixed naive Bayes model(FWMNBM)is developed to overcome the above shortcomings.For the FWMNBM,the variables that are more correlated to the class have greater weights,which makes the more discriminating variables contribute more to the model.At the same time,FWMNBM does not have to calculate the conditional probability between variables,thus it is less restricted by the number of training data samples.Compared with the MHNBM,the FWMNBM has better performance,and its effectiveness is validated through numerical cases of a simulation example and a practical case of the Zhoushan thermal power plant(ZTPP),China.

Massive Power Device Condition Monitoring Data Feature Extraction and Clustering Analysis using MapReduce and Graph Model

Effective storage,processing and analyzing of power device condition monitoring data faces enormous challenges.A framework is proposed that can support both MapReduce and Graph for massive monitoring data analysis at the same time based on Aliyun DTplus platform.First,power device condition monitoring data storage based on MaxCompute table and parallel permutation entropy feature extraction based on MaxCompute MapReduce are designed and implemented on DTplus platform.Then,Graph based k-means algorithm is implemented and used for massive condition monitoring data clustering analysis.Finally,performance tests are performed to compare the execution time between serial program and parallel program.Performance is analyzed from CPU cores consumption,memory utilization and parallel granularity.Experimental results show that the designed framework and parallel algorithms can efficiently process massive power device condition monitoring data.

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.

A graphic monitoring method for electric power of VVVF hydraulic system

In order to online monitor the running state of variable voltage and variable frequency(VVVF)hydraulic system,this paper presents a graphic monitoring method that fuses the information of variable frequency electric parameters.This paper first analyzes how the voltage and current of the motor stator change with the operation conditions of VVVF hydraulic system.As a result,we draw the relationship between the electric parameters(voltage and current)and power frequency.Then,the signals of the voltage and current are fused as dynamic figures based on the idea of Lissajous figures,and the values of the electric parameters are related to the features of the dynamic figures.Rigorous theoretical analysis establishes the function between the electric power of the variable frequency motor(VFM)and the features of the plotted dynamic figures including area of diagram,area of bounding rectangle,tilt angle,etc.Finally,the effectiveness of the proposed method is verified by two cases,in which the speed of VFM and the load of VVVF hydraulic system are changed.The results show that the increase of the speed of VFM enhances its three-phase electric power,but reduces the tilt angle of the plotted dynamic figures.In addition,as the load of VVVF hydraulic system is increased,the three-phase electric power of VFM and the tilt angle of the plotted dynamic figures are both increased.This paper provides a new way to online monitor the running state of VVVF hydraulic system.

Optically powered gas monitoring system using single-mode fibre for underground coal mines

We present an optically powered,intrinsically safe gas monitoring system to measure four essential environmental gases(CH_(4),CO_(2),CO and O_(2)),together with ambient temperature and pressure,for underground mines.The system is based on three key technologies developed at UNSW:(1)power-over-fbre(PoF)at 1550 nm using a single industry-standard,low-cost single-mode fbre(SMF)for both power delivery and information transmission,(2)liquid–crystal-based optical transducers for optical telemetry,and(3)ultra-low power consumption design of all electronics.Together,this approach allows each gas monitoring station to operate with less than 150 mW of optical power,meeting the intrinsic safety requirements specifed by the IEC60079-28 standard.A 2-month feld trial at BMA’s Broadmeadow underground mine proved the cabling compatibility to the mine’s existing optical network and the stability of the system performance.Compared with conventional electrically powered gas sensors,this technology bypasses the usual roadblocks of underground gas monitoring where electrical power is either unsafe or unavailable.Furthermore,using one fbre for both power delivery and communication enables longer distance coverage,reduces optical cabling and increases multiplexing possibilities and data throughput for better awareness of underground environment.

Instantaneous frequency measurement using two parallel I/Q modulators based on optical power monitoring

A scheme for instantaneous frequency measurement(IFM)using two parallel I/Q modulators based on optical power monitoring is proposed.The amplitude comparison function(ACF)can be constructed to establish the relationship between the frequency of radio frequency(RF)signal and the power ratio of two optical signals output by two I/Q modulators.The frequency of RF signal can be derived by measuring the optical power of the optical signals output by two I/Q modulators.The measurement range and measurement error can be adjusted by controlling the delay amount of the electrical delay line.The feasibility of the scheme is verified,and the corresponding measurement range and measurement error of the system under different delay amounts of the electrical delay line are given.Compared with previous IFM schemes,the structure of this scheme is simple.Polarization devices,a photodetector and an electrical power meter are not used,which reduces the impact of the environmental disturbance on the system and the cost of the system.In simulation,the measurement range can reach 0 GHz-24.5 GHz by adjusting the delay amount of the electrical delay lineτ=20 ps.The measurement error of the scheme is better at low frequency,and the measurement error of low frequency 0 GHz-9.6 GHz can reach-0.1 GHz to+0.05 GHz.

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.

Monitoring and control technology of solar photovoltaic power generation system

In view of characteristics of solar photovoltaic (PV) power station such as the decentralized layout and massive monitoring and control information, a solar PV power generation monitoring and control system has been designed. The system is designed into three layers namely the sensor and actuator layer, the PLC field monitoring and control layer and the remote network monitoring and control layer. Through ZigBee wireless network, PROFIBUS and GPRS wireless network, the system makes the three layers exchange information rapidly, and the system supervises not only various operational parameters of the power generating system but also weather changes as a way to change the solar tracking strategy of the PV power generating system and reduce the operating energy consumption of the system. Through the hardware redundant design of PLC central controller and the upper computer, the solar PV power station can be more secure and reliable when running.

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.

BP-Neural-Network-Based Tool Wear Monitoring by Using Wav elet Decomposition of the Power Spectrum

In a drilling process, the power spectrum of the drilling force is related tothe tool wear and is widely applied in the monitoring of tool wear. But the feature extraction andidentification of the power spectrum have always been an unresolved difficult problem. This papersolves it through decomposition of the power spectrum in multilayers using wavelet transform andextraction of the low frequency decomposition coefficient as the envelope information of the powerspectrum. Intelligent identification of the tool wear status is achieved in the drilling processthrough fusing the wavelet decomposition coefficient of the power spectrum by using a BP (BackPropagation) neural network. The experimental results show that the features of the power spectrumcan be extracted efficiently through this method, and the trained neural networks show highidentification precision and the ability of extension.

Design of Millimeter-Wave High-Power Power Monitoring Miter Bend Based on Aperture-Coupling

A directional coupler in a miter bend was designed to monitor the microwave power of the transmission line in an electron cyclotron resonance heating（ECRH） system. It is based on aperture-coupling theory and simulation of an electromagnetic（EM） field to design and optimize the 140 GHz high-power directional coupler. In addition, we simulated the double-aperture directional coupler by using three-dimensional（3D） EM simulation software, in which the central frequency is 140 GHz, coupling factor is about –70 dB, and directivity is greater than 17 dB. The results show that such a coupler is a viable tool for power measurement in high-power transmission systems.