Voltage Current Transformers Research Articles

Electric Energy Metering Error Evaluation Method Based on Deep Learning

The measuring accuracy of the electric energy meter, voltage transformer and current transformer shows a dynamic state under the influence of its factors and external factors. The error of the voltage transformer and current transformer cannot be measured by traditional method. This paper establishes a multidimensional error analysis and fault diagnosis system for power metering based on Hadoop architecture and Spark memory calculation. The platform extracted the error signal from the measurement data and calculated the characteristic value of the error signal. Then, dependent cloud and dynamic time rules are used to estimate the transformer's and voltage transformer's continuity. Then, a half-step membership degree cloud generation algorithm is constructed to overcome the error bias randomness and fuzzy characteristics under the influence factors. Finally, the system uses the dynamic correction method to estimate the similarity of error timing and quantitative factors to realize the error calculation of the current transformer and voltage transformer. The power metering error processing system was built with the support of Hadoop and Spark. The timing increment is introduced in the process of data collection. Dependent cloud and dynamic time-repair methods can improve the accuracy of diagnosing errors in electric energy metering. The parallel optimization of big data platforms by belonging to the cloud and dynamic time-warping algorithm is verified.

A remote self-calibration design for three-phase power monitoring terminal

In view of the situation that the existing three-phase power metering device is prone to excessive error and inaccurate measurement during long-term operation, and the device must be removed for re-calibration, a self-calibration power monitoring terminal based on NB-IOT communication is proposed. The power monitoring terminal adopts an external voltage transformer and current transformer, and the input signal is mV and mA level AC small signal. The integrated design of single-chip microcomputer and metering chip is used in the power monitoring terminal. The single-chip microcomputer reads and writes the data collected by the metering chip and displays and transmits the power data. After the remote measurement instruction is issued, the three-phase sinusoidal signal generator chip inside the system is used to simulate the voltage signal and current model, and the external voltage and current input channel are switched with the analog signal channel through the analog switch to complete the internal self-verification work of the device. This scheme can significantly reduce the workload caused by dismantling, installing and verifying the instrument, ensure the measurement accuracy of the instrument for a long time, and has great practical value.

Aging of Oil-Impregnated Paper High Voltage Current Transformers: Long Duration Test and Lifespan Estimation

Aging of Oil-Impregnated Paper High Voltage Current Transformers: Long Duration Test and Lifespan Estimation

Research on low voltage current transformer power measurement technology in the context of cloud computing

Research on low voltage current transformer power measurement technology in the context of cloud computing

Low voltage current transformer defect detection method based on Hausdorff distance algorithm under charged state

Low voltage current transformer defect detection method based on Hausdorff distance algorithm under charged state

Исследование влияния магнитного поля на характеристики частичных разрядов

The paper is devoted to the study of the dependences of the characteristics of partial discharges on magnetic induction. The design of the experimental setup has been developed. It allows applying both high voltage and current comparable to the operating one. The setup includes a high voltage source (dielectric tester), a current flow circuit, a high voltage current transformer and a sample of XLPE insulated cable. The operation of the electrical circuit of the experimental setup is simulated using software. The modeling has shown that if the operational electrical strength of the current transformer insulation is present, the high-voltage potential cannot contact the current flow circuit. After this, modeling of the magnetic field inside the insulating layer is carried out. Based on the developed design, an experimental setup is created. To record partial discharges, an artificial defect is created in a cable sample. The results of magnetic field modeling made it possible to estimate the magnetic induction in the field of an artificial cable defect. Next, experimental studies are carried out to assess the influence of the magnetic field of the cable core current on the characteristics of partial discharges. The measurement results have showed a decrease in the average apparent charge of partial discharges and partial discharge power with increasing current. In addition, waveforms are compared, but no significant differences are found. The magnetic field of the current may influence the PD performance in the long term due to its possible influence on the direction of growth of the electrical tree structure.

Low voltage current transformer defect detection method based on Hausdorff distance algorithm under Charged state

Low voltage current transformer defect detection method based on Hausdorff distance algorithm under Charged state

Research on low voltage current transformer power measurement technology in the context of cloud computing

Research on low voltage current transformer power measurement technology in the context of cloud computing

The Research on the Improvement of the Zero-Sequence Relay for the Low Resistance Grounded Power Grid

In the low resistance grounded power grid, when a high-impedance grounding fault occurs at a distribution line, the zero-sequence fault current is not big enough to make the zero-sequence over-current relays trip because of the setting limitations, and thus the earth fault would exist for a long time with no alarm signal. As a result, there would be a hidden danger that the grounding fault might cause further faults or cause harm to personal safety. To solve the problem, in the paper, the characteristics of zero-sequence components when the high-impedance grounding fault occurs are analyzed, and the practicability and the deficiency of the directional zero-sequence over-current relay are pointed out. Based on the analysis, an improved zero-sequence relay with the resistance-capacitance ratio restriction is raised. The resistance-capacitance ratio restriction condition is based on the different structures of the resistant part and the capacitive part of zero-sequence currents, and the faulted line can be identified with the resistance-capacitance ratio criterion. The resistance-capacitance ratio criterion is not influenced by the polarity of the voltage transformer (VT) and current transformer (TA) and can avoid the influence caused by the reversed polarity of the exclusive zero-sequence TA. With the improved zero-sequence over-current relay with the resistance-capacitance ratio restriction, the ability to identify high-impedance grounding faults can be improved, and the fault area can be isolated quickly, to guarantee the reliability and safety of the operation in power grids.

Development of IoT-Based Portable Power Quality Monitoring on Microgrids by Enhancing Protection Features

The need for small-scale renewable energy generation is predicted to increase. Distributed energy production, in general, can be more profitable due to the cost of distribution and use of energy storage, especially from the microgrid. However, the utility and consumers face difficulties maintaining demand imbalance, frequent load-shedding, and a drop in power quality. To address this issue, a portable power quality meter and protection based on the Internet of Things (IoT) for low-voltage distribution are proposed. The proposed prototype has several advantages. First, the procedure for implementing a portable IoT-based power meter with power quality and protection features for residential networks. Compared to other devices, this type has the advantages of power quality measurement, such as power factor, frequency, and harmonics. Second, an approach is proposed device with a parallel function in maintaining network security and quality. This increases the advantage of monitoring loads connected to the grid. Third, perform IoT power monitoring devices that provide notifications in real-time. Fourth, an experiment using a power meter on a microgrid connected to renewable energy combines a LiFePO4 battery and methanol to get the maximum benefit from green energy. The test results found that the IoT model can work reliably, where access to monitoring can be done via the website. The smart meter consists of a voltage transformer, current transformer, and microcontroller unit with an embedded communication module. The existence of more affordable monitoring and protection tools can increase the user’s opportunity to gain profitability.

Finite Element Analysis of Thermal Performance Behavior in Medium Voltage Current Transformer

Current transformers reduce large current values to measurable current values in electrical systems and provide isolation of various measuring instruments and relays from the main electrical system. Voltage current transformers are produced according to the tests defined in national and international standards during the production phase. In order for the relays used for protection in electrical systems to work correctly, medium voltage current transformers must be within the verified operating range. For this reason, it becomes very important for current transformers to work correctly. In case the main current has a harmonic structure, the operating range of the protection type medium voltage current transformers can change significantly. In this paper, it the steady-state thermal performance behaviour in a medium voltage current transformer is studied and analysed. The study was carried out considering four different loads. The numerical results of the temperature distribution were obtained using a 2D finite element software package. The iron losses in the core region were calculated using the maximum flux density that was obtained with a 2D finite element software package. The numerical solutions were compared with measured experimental results that were obtained in tests. Some conclusions are remarked.

Thermal behaviour analysis of a high voltage inverted‐type current transformer

A high voltage current transformer of the inverted type is a commonly used measurement equipment in power grids. The thermal behaviour of the current transformer has a significant impact on its operating conditions and is directly related to its service life. The study presents a three-dimensional simulation model of a 220 kV inverted-type oil-immersed current transformer, and the fluid and temperature field are analysed by the finite volume method. The simulation results show that the hot-spot temperature under the rated load of the calculation model introduced in the study is 61.5°C, and located at the upper part of the core and the secondary winding. An experiment setup was designed to measure the temperature distribution inside a LVB-220W3-type current transformer. The temperature data measured under the rated load indicate that the simulation results agree well with the experimental results.

Duck curve leveling in renewable energy integrated grids using internet of relays

Power grids are undergoing deregulation, privatization, and decentralization worldwide. The smart grid allows the integration of clean power renewable energy technologies to the utility grid through mini, micro, and nano grids. Conventional centralized power grids used to rely on fossil fuel-fired power plants which are being replaced worldwide with solar, wind, small hydro, geothermal, biomass, wave, and alternative energy technologies. Installed solar and wind power generation capacity has surpassed 1300 GW in 2020. Solar and wind powers rise during the day and fall during the evening. Consumer demand increases steadily during the evening and peaks after sunset when solar generation becomes zero and wind power falls substantially. Decentralized smart grid faces duck curve limitation on the integration of renewable energy technologies as centralized utilities used to face the peak-hours issue. Smart grid operators have no effective solution of load peaking after sundown except keeping fossil fuel-fired plants on standby to ride through the duck curve. We present a solution to the duck curve problem by integrating smart load shedding devices in micro and nano grids to adjust their demand frugally during peak hours to support the national grid. Information and communication (ICT) technologies that enabled the internet of things (IoT) have been attempted to facilitate smart load shedding in nano grids. ICT enabled voltage transformers (VT) and current transformers (CT) supply signals to heuristic rules based multifunction smart relaying system. Smart meters, instrument transformers, and status monitoring field devices generate a massive amount of data. The research designed an IoT and LabVIEW based software platform to carry out demand-side management. Under frequency (UF) and under-voltage (UV) relaying functions were used to conduct load shedding in nano grids. This nanoscale demand-side management experiment paves the way to ride through utility-scale duck curve setback. This PT/CT data based economic solution performs at nanoscale same as ABB PML 630 load shedding controller. This UF and UV relaying based multifunction relay starts shedding loads when frequency falls below <1% and voltage below 10% of rated values. Our load shedding scheme has successfully functioned on nanoscale 5 kW system. The future study section proposes to integrate big data technologies in-home energy management system (HEMS) through extract, transform and load (ETL) pipeline to import data from PT/CT and circuit breakers (CB) integrated smart meter to transform it according to requirement by loading data into Hadoop “big data” processing platforms for utility-scale load management with help of day-ahead load and weather-dependent renewable power generation forecasting techniques.

Instrument Transformer Calibration and Robust Estimation of Transmission Line Parameters Using PMU Measurements

Instrument transformers (ITs) once installed in the field are seldom calibrated. We propose two tests to detect systematic errors in capacitive voltage transformers (CVTs) and current transformers (CTs). The first test, a direct test, compares the mid-point voltage estimated from both ends of a transmission line using PMU data. The second test, an indirect test, analyzes the deviation of the estimated positive sequence line parameter values from the design values. Subsequently, we propose a robust method to simultaneously determine the positive sequence line parameters and IT calibration factors. Special care is given to numerical sensitivity of the method to the noise in the data and we show by Monte Carlo simulations that the proposed approach is accurate and robust. A noteworthy feature of this paper are the case studies based on field PMU data for short, medium, and long length lines of 400 kV and 765 kV. It clearly demonstrates the stability of both line parameters and IT calibration factors and hence justifies the claims.

A novel complex current ratio-based technique for transmission line protection

With respect to sensitivity, selectivity and speed of operation, the current differential scheme is a better way to protect transmission lines than overcurrent and distance-based schemes. However, the protection scheme can be severely influenced by the Line Charging Capacitive Current (LCCC) with increased voltage level and Current Transformer (CT) saturation under external close-in faults. This paper presents a new UHV/EHV current-based protection scheme using the ratio of phasor summation of the two-end currents to the local end current, instead of summation of the two-end currents, to discriminate the internal faults. The accuracy and effectiveness of the proposed protection technique are tested on the 110 kV Western System Coordinating Council (WSCC) 9-bus system using PSCAD/MATLAB. The simulation results confirm the reliable operation of the proposed scheme during internal/external faults and its independence from fault location, fault resistance, type of fault, and variations in source impedance. Finally, the effectiveness of the proposed scheme is also verified with faults during power swing and in series compensated lines.

Research on the Strategy of Failure Recovery in Smart Grid

With the development of China’s comprehensive construction and the upgrading of industrial system, China began to transform from energy-consuming and high-pollution society to energy-saving and environment-friendly society. Knowledge-intensive and equipment-intensive industries are on the increase, which causes the increasing demand for the stability of electricity supply. At present, the problem of transmission over distribution still exists in the power grid construction of China. In power systems over 110 k V, the strategy of non-homologous dual power supply is adopted to guarantee power supply. When a circuit trip occurs, the spare line can be used to continue the power supply, so the existing domestic main network system has a high reliability. The main function of the distribution network system is to connect the user and the main network, which is an important link of power transmission. In the future of the development of intelligent power network, the original parts such as mobile voltage transformer and current transformer can be used to locate the fault position after the physical fault occurs in the distribution network, and automatic reclosing device can be used for fault isolation and fault recovery. How to use the optimal strategy to make the controllable automatic reclosing device be used for switching operation after the physical failure of the distribution network so as to ensure the reliable power supply of the distribution network, has become the focus of power network hoisting service.

Deep Learning Image-Based Defect Detection in High Voltage Electrical Equipment

The increase in the internal temperature of high voltage electrical instruments is due to a variety of factors, particularly, contact problems; environmental factors; unbalanced loads; and cracks in the high voltage current transformers, voltage transformers, insulators, or terminal junctions. This increase in the internal temperature can cause unusual disturbances and damage to high voltage electrical equipment. Therefore, early prevention measures of thermal anomalies in equipment are necessary to prevent high voltage equipment failure that might shut down the whole grid system. In this article, we propose a novel non-destructive approach to defect analysis in high voltage equipment by taking advantage of the infrared thermography and the deep learning (DL) approach from the machine learning paradigm. The infrared images of the components were captured using the FLIR T630 without disturbing the operations of the power grid. In the first stage, rich features maps from the convolutional layers of the AlexNet pretrained model were extracted. After feature extraction, the random forest (RF) and support vector machines (SVM) were trained for learning of the defective and non-defective high voltage electrical equipment. In an experimental analysis, the RF optimally learned the separation between defective and non-defective equipment with greater than 96% accuracy, outperforming all the other comparative approaches for deep and nondeep features. The proposed approach based on the RF is reliable and shows its efficacy for fault detection in high voltage electrical equipment.

Automated system for determining parameters of a solar cell model

An automated system is developed, which allows measuring the light and dark current-voltage characteristics (CVC) of a solar cell (SC). It consists of a STM32 based control unit, a digital-to-analog converter, a voltage-current transformation circuit, a current and voltage sensor and a laptop with a LabVIEW graphical programming environment. The digital voltage value from STM32 is transmitted to the AD5624R DAC via the SPI interface. AD5624R is a 12 bit DAC with built-in reference voltage 2,5 V. In this configuration, the accuracy of the voltage control is 1,2 mV and the accuracy of the current setting is 40 μA. INA226 sensor was used to measure the voltage on the sample and the current flowing through it. The current is measured as the voltage drop across the shunt resistor, which is connected to the corresponding sensor inputs, using the built-in 16-bit ADC. A shunt resistor with a resistance of 0.1 Ohm is used, which allows measuring the current up to 800 mA with a resolution of 25 μA. The readings of the sensor were calibrated using the precision voltmeter B7-46. Measurement and data processing is carried out with a virtual device created in the LabVIEW environment. As a microcontroller, the SM32F401RE Nucleo development board was used. This unit provides control of the DAC, the current sensor INA226, connection of the circuit for measuring light or dark CVC, as well as recording and storing the data received from sensors in the computer. By measuring the light and dark current-voltage characteristics it is possible to obtain an approximate solar cell model, the parameters of which depend on the illumination and temperature. Solar cell light CVC is used to determine the photocurrent. By its value at a certain temperature and luminosity, it’s possible to define the photocurrent at different temperatures and luminosity levels. The saturation current and the parameter α of the solar cell are calculated using the dark CVC. With the obtained data, a model of a solar cell is defined, which can be further used to determine the maximum power point at different levels of illumination and temperature. With information about the maximum power point, it is possible to calculate the optimal resistance value for the solar cell and to provide the corresponding control signal to the voltage converter. An approach for calculating the parameters of the SC model from its CVC is described and used to determine the MPP (maximum power point) of the solar cell module. The difference with the experimental data was 6.6%. In further research, the study of methods for calculating the parameters of the SC, which could provide a more accurate model, will be continued.

Electrical characterization of argon and nitrogen based cold plasma jet

In this paper, a dielectric barrier discharge plasma based atmospheric pressure plasma jet has been generated in a floating helix and floating end ring electrode configuration using mixture of argon and nitrogen gases (50:50 ratio). This configuration is subjected to a range of supply frequencies (10–25 kHz) and supply voltages (6.5–9.5 kV) at a fixed rate of gas flow rate (i.e., 1 l/min). The electrical characterization of the plasma jet has been carried out using a high voltage probe and current transformer. The current–voltage characteristics have been analyzed, and the power consumed by the device has been estimated at different applied combinations of supply frequency and voltages for optimum power consumption and maximum jet length. A comparative analysis of the results of the above experiments has shown that maximum power consumed by the device in helix electrode configuration with end ring is 19 W for (Ar+N2) mixture as compared to only 12 mW and 7.7 mW for Ar and He gas respectively (With end ring), this may be due to the main ionization mechanisms which are different depending on the working gas. Furthermore, maximum jet length of 42 mm has been obtained for He gas at 6 kV/25 kHz due to penning ionization process in comparison to jet lengths of only 32 mm for Ar gas and jet length of only 26 mm for Ar+N2 mixture. The obtained average power consumed and maximum jet length for mixture of (Ar+N2) gases are 6.5 W and 26 mm.

The Device for Simultaneously Accuracy Testing of Current Transformers

This paper presents a three-channel device for simultaneous accuracy testing of three current transformers. The concept of multichannel device is one of the possible good solutions for accuracy testing in the process of automated or robotized manufacturing of low voltage current transformers. The paper presenrs a short description of the overview of calibration results.