Primary Equipment Research Articles

Design of a Substation Secondary Equipment-Oriented Error Prevention System Using Wireless Communication Technology and Edge Node Cooperation

In order to solve the error prevention problem of secondary equipment in intelligent substations, this paper designs the Substation Secondary Equipment- (SSE-) oriented error risk Prevention, Control, and Management (P&C&M) system. Firstly, the basic principle of SSE error prevention is reviewed. The SSE model is expanded based on the existing microcomputer error prevention system’s Substation Primary Equipment (SPE). Thereupon, the SSE status acquisition device is designed, and the overall architecture is implemented for SSE error prevention. Secondly, edge-node cooperation is analyzed along with the specific architecture of the edge gateway. Finally, the wireless communication network is designed based on the edge gateway. The delay and flow of different data streams are compared, and the error proof verification mechanism is introduced into SSE. The numerical results corroborate that when the Sampled Value (SV) traffic exceeds 32 Mbps, the maximum delay exceeds the specified delay (3 MS). The average flow of the Manufacturing Message Specification (MMS) message is 90 kbps, which can meet the requirements of the intelligent substation. The delay of star networking is higher than that of ring networking. Meanwhile, the proposed network analyzer has a measured flow closer to the calculated flow of SSE. In the 60-hour accuracy statistics, the proposed SSE-oriented error P&C&M system reaches an accuracy as high as 84%. Therefore, the proposed SSE-oriented error P&C&M has strong feasibility. The outcome provides a reference for the intelligent development of error prevention of secondary equipment in intelligent substations.

Experimental performance of a multi‐storey braced frame structure with non‐structural industrial components subjected to synthetic ground motions

AbstractThe seismic risk assessment of industrial facilities mainly relies on historical data and the analysis and design of uncoupled secondary components. Accordingly, the dynamic interaction between primary structures and process equipment is overlooked. The SPIF project – Seismic Performance of Multi‐Component Systems in Special Risk Industrial Facilities – was carried out to respond to this gap, within the European H2020 SERA framework. Its objective regarded the investigation of the seismic behaviour of an archetype industrial multi‐storey steel moment resisting frame (MRF) structure equipped with non‐structural components (NSCs) by means of shaking table tests. The goal of the proposed study was to extend the interaction analysis between a primary multi‐storey braced frame (BF) steel structure and NSCs in a performance‐based earthquake engineering (PBEE) perspective. Along this vein, to excite the vibration periods of the NSCs and thus enhance possible coupling with the primary structure, a synthetic site‐based ground motion model (GMM) was employed. More precisely, the proposed research intended: (i) to severely excite the process equipment and supplement the scarcity of real records with a specific frequency content by means of a stochastic GMM; (ii) to quantify seismic‐induced force and displacement demands of secondary components and their effects on the primary BF structure. The evaluation of the experimental data clearly shows buckling in the bracing system of the BF configuration and a strong interaction between vertical tanks and floor crossbeams of the BF. At the very least, the favourable performance of the archetype BF under strong seismic records is demonstrated.

NCAA Student-Athlete Training During COVID-19 Stay-At-Home Restrictions

ABSTRACT The effects of COVID-19 restrictions were ubiquitous, including decreased physical activity globally. A recent study showed significant consequences on American student-athletes, who were forced to stay at home between March and June 2020. Inadequacy of equipment and programming hampered the resulting improvised training. Resistance exercise was the second most common mode used after cardiovascular exercise, and the primary equipment utilized was dumbbells and resistance bands. More women than men did not resistance train. More women believed they were eating less and healthier. Sleep length and disturbances increased; the latter more in women. Mental health concerns and decreased motivation to train became more frequent, especially within Division III more than Division I. The most-reported overall concerns were maintenance of fitness, sport-specific training, and health, possibly implicating the equipment/programming barriers as contributors to negative psychological effects. Providers of S&C, mental health, and other support services should plan for athletes' home situations toward any future extended lockdown.

Research on Relay Protection and Security Automatic Equipment Based on the Last Decade of Big Data

The analysis of equipment record, defects and action events of relay protection and security automatic equipment has been carried out in the last decade since the establishment of an electric power company on the basis of relay protection relay protection statistics analysis and operation management module. It can be seen that the growth rate of security and stability control devices is the highest, which is mainly due to the large-scale grid connection of new energy sites; it should strengthen the operation and maintenance of capacitor protection, and stock up spare parts that are prone to frequent defects, such as triggering-power module of capacitor protection for FSC in the severe electromagnetic environment; the number of primary equipment faults and protection actions shows seasonal characteristics, most of which occur in windy, summer thunderstorm weather. The data-driven screening of familial defects, evaluation of operation and maintenance strategy for aged equipment and spare parts management have been actively explored to improve lean management.

A logical reasoning-based method for sensing the operating status of equipment

Grid equipment monitoring is to achieve comprehensive perception, rapid analysis and accurate disposal of grid operation status. As the scale of the grid continues to expand, many problems such as low efficiency in single point-based alarming, complicated and difficult process, irregular work norms, etc., have occurred in the current operating mode, which greatly restricts the improvement of management level of monitoring operation. Based on the correlation between substation monitoring information and monitoring equipment operation, we establish the correspondence between primary equipment such as main transformer, busbar, line and capacitor and the corresponding telemetry such as current, voltage, active power, reactive power and frequency. Then we analyze the occurrence mechanism of power grid equipment operation events, sense the equipment operation status, and realize timely and accurate sense and push of equipment operation defects and faults, thereby improving operational efficiency of monitoring devices.

ACCRUAL-BASED ACCOUNTING APPLICATION, INFORMATION TECHNOLOGY, HR COMPETENCIES, ORGANIZATIONAL COMMITMENT ON THE FINANCIAL STATEMENTS’ QUALITY

Background: Financial statements are the government's primary accountability equipment and sharing data with outsiders and stakeholders to address the extent of the efficiency of the organization's economic resources. Thus, good quality financial statements are needed to increase public confidence and accountability.
 Aim: This research aims to find out the effect of the accrual-based accounting application, utilization of information technology, human resource competence, and organizational commitment to the quality of financial statements with indicators of budget implementation performance as moderate variables (Satker survey in the Directorate General of Binwasnaker and K3).
 Method: This study is a quantitative study with census methods of 12 Work Units in the Directorate General of Binwasnaker and K3 as respondents. The tools used in this study used PLS-SEM. The research data used came from answers to questionnaires distributed to respondents. The results of the data assessment and analysis using structural equation modeling with alternative methods partial least square.
 Findings: Accrual-based accounting, information technology utilization, HR competence have a significant positive effect on the quality of financial statements while organizational commitment does not have a significant positive effect on the quality of financial statements and budget implementation performance indicators do not moderate the relationship of each variable of accrual-based accounting application, utilization of information technology, HR competence and organizational commitment to the quality of financial statements.

Study on the Overvoltage Protection Measures of Electrical Primary Equipment

Study on the Overvoltage Protection Measures of Electrical Primary Equipment

Most significant ageing problems actually experienced and mitigating solutions implemented for WWER primary equipment

Abstract The present paper deals with the consideration of cases of degradation of the basic equipment (reactor pressure vessels and steam generators') of WWER-440 and WWER-1000 reactor plants, the degradation mitigation measures on the equipment of operating reactor plants as well on equipment being manufactured for newly designed reactor plants.

Power Inspection Design by Internet of Things and RFID Technology in Smart City

As the basic element and module unit in the construction architecture of smart city, the Internet of things (IoT) is also the key foundation and important support for realizing "automatic perception, rapid response, and scientific decision-making" of smart city. The study aims to improve the efficiency of power inspection in power enterprises and provide intelligent technology for power inspection. After the theoretical analysis of IoT and RFID technology under the background of smart city, the study discusses the information acquisition principle of RFID technology. Second, based on IoT and smart grid, the study takes the power equipment of power company A as an example, and puts forward the power inspection scheme, including the information required for inspection and the inspection of primary and secondary equipment. The specific contents are as follows: health assessment is carried out according to the real-time alarm of power equipment, and the control command is sent to the downstream control equipment to confirm the alarm information. Meantime, based on the alarm information of power equipment and related equipment, the expert analysis system is used for reasoning and analysis, and the RFID tag is used to supervise the inspectors to arrive at the site and inspect the situation according to the predetermined route. The temperature of the cable of power company A is measured under normal and hidden dangers, and the body insulation test is conducted on No. 1 main transformer. The results show that under normal operation, the cable temperature at each point is slightly different, which is basically about 40 °C. The temperature before the fourth point of the cable rises obviously, indicating that the fourth point has faulty. Over time, the more chemical molecules are detected in phase A. When phase B and phase C are tested on the same day, the difference of chemical molecular content is relatively small. It indicates that the chemical molecular content detected by chromatographic test of bulk insulating oil is normal. To sum up, smart power, as the objective need of urban intelligent development, is an important foundation of smart city. The power inspection scheme based on IoT and RFID technology proposed has high detection efficiency.

Longwall face roof disaster prediction algorithm based on data model driving

Hydraulic support is the primary equipment used for surrounding rock control at fully mechanized mining faces. The load, location, and attitude of the hydraulic support are important sets of basis data to predict roof disasters. This paper summarized and analyzed the status of coal mine safety accidents and the primary influencing factors of roof disasters. This work also proposed monitoring characteristic parameters of roof disasters based on support posture-load changes, such as the support location and support posture. The data feature decomposition method of the additive model was used with the monitoring load data of the hydraulic support in the Yanghuopan coal mine to effectively extract the trend, cycle period, and residuals, which provided the period weighting characteristics of the longwall face. The autoregressive, long-short term memory, and support vector regression algorithms were used to model and analyze the monitoring data to realize single-point predictions. The seasonal autoregressive integrated moving average (SARIMA) and autoregressive integrated moving average (ARIMA) models were adopted to predict the support cycle load of the hydraulic support. The SARIMA model is shown to be better than the ARIMA model for load predictions in one support cycle, but the prediction effect of these two algorithms over a fracture cycle is poor. Therefore, we proposed a hydraulic support load prediction method based on multiple data cutting and a hydraulic support load template library. The constructed technical framework of the roof disaster intelligent prediction platform is based on this method to perform predictions and early warnings of roof disasters based on the load and posture monitoring information from the hydraulic support.

Research on Radiated Disturbance to Secondary Cable Caused by Disconnector Switching Operation

With the development of smart grids, the application of localized relay protection devices has greatly reduced the distance between the secondary equipment and the primary equipment. The secondary equipment will be in a more complex electromagnetic environment during the operation of the GIS disconnector. The present study takes the multi-path electromagnetic disturbance on the secondary cable caused by the disconnector switching operation of the domestic 1000 kV ultra-high voltage GIS test circuit as the research background, solves the field-line coupling problem based on the finite integral technique, and combines the multi-conductor transmission line theory to solve the radiation disturbance and obtains its influencing factors. The results demonstrate that the radiated disturbance accounted for 16% of the overall electromagnetic disturbance when both ends of the shielding layer are grounded. The use of grounding at both ends of the shielding layer, reducing the height of the secondary cable wiring, avoiding the parallel arrangement of the secondary cables and the GIS pipe mother, and installing a low-pass filter, have different levels of suppression effects on electromagnetic disturbances. The research results will guide the reasonable arrangement of secondary cables in GIS substations to some extent and have reference significance for the protection of secondary equipment.

Comprehensive performance optimisation method of the hybrid simulation platform of an MMC-HVDC system

ABSTRACT Digital–physical hybrid simulation (DPHS) technology provides an efficient means to investigate the complex interaction mechanism and dynamic behaviour of a modern power grid integrated with numerous power electronic devices. However, its further development and wide application are obstructed by many factors, especially the large investment of the physical subsystem. This paper presents a comprehensive parameter optimisation method for the development of the DPHS platform based on tools from similarity theory and nonlinear programming theory. The parameter optimisation model is formulated to minimise the one-time investment of the primary equipment of the physical subsystem and the constraints to guarantee the desired performance of the hybrid simulation platform derived according to similarity criteria. An MMC-HVDC project is taken as an example to specifically explain the implementation of the proposed method with the focus on the solution of similarity criteria. Results obtained from steady and dynamic simulation show that the proposed approach is effective for improving the technical and economic performance of a hybrid simulation platform.

Traveling Wave Fault Location Technology in Distribution Network Based on Non-Contact Sensor

In view of the fact that traditional traveling wave sensors need to be directly connected with primary high-voltage equipment, the layout is not flexible, construction is inconvenient, and the traditional ferromagnetic coil traveling wave sensors have problems such as low sensitivity and magnetic saturation. The use of magnetoresistance chip to design non-contact traveling wave sensor is proposed. Theoretical analysis of the magnetoresistance chip is carried out, and the tunnel magnetoresistance chip is selected as the non-contact sensor magnetic sensitive element; the non-contact sensor hardware circuit is designed, the sample is trial-produced, and the experimental test is carried out. The experiment shows that the non-contact sensor can detect a traveling wave signal with a bandwidth of 100kHz∼5MHz, which meets the requirements of traveling wave detection for common fault types in the distribution network. A demonstration project has been built, and operation shows that the non-contact sensor can successfully detect single-phase grounding, interphase short circuit, lightning strikes and other fault types traveling wave signal, sensitivity is higher than traditional traveling wave sensor, positioning error is less than 150m.

Research on status information monitoring of power equipment based on Internet of Things

Power equipment is an inseparable and important part of the power system, and its operation largely determines the operation of the power grid. With the continuous promotion of the application of the Internet of Things technology in the power field, the monitoring of the status information of power equipment based on the Internet of Things has high research value. In order to explore the monitoring method of power equipment status information based on the Internet of Things, this article combines work practice to analyze the data information, tasks, and technical methods of power equipment status monitoring, conducts detailed research on primary equipment and secondary equipment, and formulates the power equipment status information monitoring strategy and method based on the Internet of things.

ГОСУДАРСТВЕННАЯ ПОДДЕРЖКА ЦИФРОВИЗАЦИИ СЕЛЬСКОГО ХОЗЯЙСТВА

State support for the development of agriculture, like other subsidized industries, has a significant impact on the development of crop and livestock products, acting as a strategic bulwark of the country's food security. An increase in the volume of state support for agriculture is possible with the dynamic activity of all sectors of agriculture, the main task of which is to increase economic efficiency through the transition to innovative production principles. State support for the technical re-equipment of agribusiness is the basis of agricultural production, which has a decisive impact on the transition to digital solutions for the entire agrarian industry in the future. In this regard, the goal was set to analyze the effectiveness of the implementation of digital technologies using the example of typical agricultural enterprises of the Republic of Tatarstan located in different climatic zones of the Volga region, confirming an average decrease in the production cost of 1 centner of grain crops by 13%, payment labor on average by 14.5%, which makes it necessary to allocate financial support to agrarians as an effective mechanism for increasing the efficiency of agribusiness based on funds from the federal and regional budgets of the constituent entities of the Russian Federation and from extra-budgetary sources. Revealing the mechanism of state regulation in the form of tax, control and inspection, as well as the mechanism of state support and legal regulation, a mechanism of state support for the digitalization process is proposed in the form of subsidizing the costs of purchasing digital products, as one of the effective mechanisms, contributing to the acceleration of the transition of agribusiness to the digital economy. This mechanism will allow agrarians, at the first stage of the digitalization process of agricultural production, to acquire primary digital equipment in the form of trackers and sensors capable of receiving, sending, generating and processing data, which will subsequently lead to the need for the acquisition of interfaces capable of providing unhindered exchange of data between machines and business partners, and later portals in the form of ecosystems

Research on Conducted Disturbance to Secondary Cable Caused by Disconnector Switching Operation

The disconnector switching operation in GIS not only generates very fast transient overvoltage (VFTO) in primary equipment, but also couples to the secondary system, which affects normal operation of the secondary equipment. In this study, aiming at the conducted disturbance caused by the disconnector switching operation of the 1,000-kV UHV GIS test circuit on the secondary cable, a broadband equivalent circuit model of the potential transformer and the grounding grid is proposed based on the vector fitting method and the impedance synthesis method, and the accuracy of the model is tested. On the basis of this model, the conducted disturbance voltage of the secondary cable core is obtained by combining the measured typical disturbance source waveform. The research results of the influencing factors of conducted disturbance show that the amplitude of the disturbance voltage generated by the capacitive conduction is higher than that generated by the resistive conduction, but the main frequency of the resistive conducted disturbance voltage is higher. The amplitude of the conducted disturbance voltage will decrease with the increase of the length of the cable and the length of the grounding wire. The single-ended grounding of the secondary cable shield at the GIS side will cause serious disturbance voltage. The research results of this study will be beneficial to the protection of secondary cable electromagnetic disturbance in the intelligent substation and have reference significance for the implementation of secondary equipment protection measures in the intelligent substation.

Two-Chamber Unit for Detecting Parameters in the Neutron Flux

The detection unit contains two neutron detectors — fission chambers KNT-31 or KNT 31–1, in which the radiator sensitive to neutron radiation is 235U (concentration of 235U in the radiator is more than 90%). The detection unit also includes two radiation- resistant preamplifiers (primary electronic equipment), which are connected to the cable transmission line to the secondary equipment, which captures the moment of pulses from the reaction of neutrons with the fission chamber radiator and save information about the time of these pulses. Further processing of the intervals between neutron events (intervals between pulses) can be done according to individual methods of the experimenter. The presence of a data processing unit type B-471 significantly expands the capabilities of the experimenter on the conclusions of statistical analysis of data and forecasting the development of emergencies in fuel-containing materials of the Shelter object. The presence of time intervals in the nanosecond range of values with sufficient probability can be classified as pulses of registration of instantaneous fission neutrons, and a change in their number may indicate a change in the effective multiplication factor of fuel containing materials. The analysis of the statistical properties of the flow of neutron event recording intervals by the electronic equipment makes it possible to predict the occurrence of a self-sustaining chain reaction. This is the main task of the Shelter object nuclear safety system. The proposed configuration of the CPI is promising and can be expanded by the number of fission chambers and electronic neutron detection units for more accurate diagnosis and prediction of the state of fissile nuclear materials.

A Chinese Named Entity Recognition Model of Maintenance Records for Power Primary Equipment Based on Progressive Multitype Feature Fusion

Presently, the State Grid Corporation of China has accumulated a large amount of maintenance records for power primary equipment. Unfortunately, most of these records are unstructured data which lead to difficultly analyze and utilize them. The emergence of natural language processing technology and deep learning methods provide a solution for unstructured text data. This paper proposes a progressive multitype feature fusion model to recognize Chinese named entity of unstructured maintenance records for power primary equipment. Firstly, the textual characteristics and word separation difficulties of maintenance records are analyzed, then 7 main entity categories of power technical terms from unstructured maintenance records are chosen, and 3452 maintenance records are labeled by these categories, which is so called EPE‐MR training dataset. Secondly, the standard test reports, standard maintenance, and fault analysis reports for three types of power primary equipment (namely, main transformer, circuit breaker, and isolating switch) are employed as corpus to train character embedding in order to obtain certain words representation ability of maintenance records. After that, progressive multilevel radicals feature extraction module is designed to get detailed and fine semantic information in a hierarchical manner. Further, radicals feature representation and character embedding are concatenated and sent to BiLSTM module to extract contextual information in order to improve Chinese entity recognition ability. Moreover, CRF is introduced to handle the dependencies among prediction labels and to output the optimal prediction sequence, which can easily obtain structured data of maintenance records. Finally, comparative experiments on public MSRA dataset, China People’s Daily corpus, and EPE‐MR dataset are implemented, respectively, which show the effectiveness of the proposed method.

An Artificial Neural Network Developed in MATLAB-Simulink for Reconstruction a Distorted Secondary Current Waveform. Part 1

Recently, there has been an increased interest in the use of artificial neural networks in various branches of the electric power industry including relay protection. Аrtificial neural networks are one of the fastest growing areas in artificial intelligence technology. Recently, there has been an increased interest in the use of аrtificial neural networks in the electric power engineering, including relay protection. Existing microprocessor-based relay protection devices use a traditional digital signal processing of the monitored signals which is reduced to a multiplying the values of successive samples of the monitored current and voltage signals by predetermined coefficients in order to calculate their RMS values. In this case, the calculated RMS values often do not reflect the real processes occurring in the protected electrical equipment due to, for example, current transformer saturation because of the DC component presence in the fault current. When the current transformer is saturated, its secondary current waveform has a characteristic non-periodic distorted form, which is significantly differs from its primary (true) waveform, which causes underestimation of the calculated RMS value of the secondary current compared to its true value. In its turn, this causes to a trip time delay or even to a relay protection devices operation failure. The use of аrtificial neural networks in conjunction with a traditional digital signal processing provides a different approach to the functioning of both the measuring and logical parts of the microprocessor-based relay protection devices, which significantly increases the speed and reliability of such relay protection devices in comparison with their traditional implementation. A possible application of the аrtificial neural networks for the relay protection purposes is the fault occurrence detection and its type identification, current transformer secondary current waveform distortion restoration due to its saturation up to its true value, detection the distorted and undistorted sections of the current transformer secondary current waveform during its saturation, primary power equipment abnormal operating modes detection, for example, power transformer magnetizing current inrush. The article describes in detail the stages of the practical implementation of the аrtificial neural networks in the MATLAB-Simulink environment by the example of its use to restore the distorted current transformer secondary current waveform due to saturation.

Preventive Maintenance of Electrical Primary Equipment in Power Plant

Preventive Maintenance of Electrical Primary Equipment in Power Plant