Transformer Equipment Research Articles

Congestion Management in Deregulated Power System Using Different Control Technique

Abstract: In today’s scenario there is a challenge for power companies to meet the expected demand load due to continuous increases in load demand causes unpredictable failure in the components of power system including transmission line, generator, transformer and various other equipment this leads to over loading in the power system and the line become congested if this failure not removed on time the system reaches to emergency state, therefore we are using various techniques to control or manage these situations these methods includes Generator Rescheduling(GR),Load Shedding, Particle Swarm Optimizer(PSO), Grey Wolf Optimization (GWO),Harmony search algorithm etc. Optimal load shedding is effective control action for congestion management. The various algorithm applied on IEEE 30 bus system.

Research on transformer condition evaluation based on oil chromatography differentiation threshold

As one of the important power transmission and transformation equipment, the reliability of transformer is directly related to the safe operation of power system. At present, the on-line monitoring technology based on dissolved gas analysis in oil is widely valued by researchers all over the world because it can continuously monitor the operation status of transformers and timely and effectively find the early faults of transformers. In this paper, the on-site oil chromatography data are differentiated and classified according to the voltage level of the transformer. The curve fitting method is used for statistical analysis and to build a distribution model. The cumulative probability is associated with the defect rate and failure rate of the equipment, and the corresponding threshold value is obtained by using the inverse cumulative distribution function as the attention value and warning value. By using this method, the attention values of the volume fraction of dissolved gas in oil and the gas production rate of dissolved gas in the existing national standards are improved, and the corresponding warning values are calculated to make the warning mechanism more flexible and reliable.

Spectral Methods for Monitoring Transformer Equipment State of Paper Insulation

The insulation of an oil-filled transformer is based on materials of organic origin - oil and wood pulp. The state of insulation is a key factor in the reliable operation of a power equipment, and much attention is paid to the insulation state assessment by researchers. To assess the cellulose insulation state, indicators such as the degree of polymerization and paper moisture are determined. The existing methods for determining the moisture content and the degree of polymerization of a paper insulation have disadvantages, as they require a complex process of sampling the insulation, which is a time-consuming operation. The purpose of the work is to develop new methods for determining the moisture content and the degree of polymerization of the paper insulation of a power transformer. This goal is achieved by obtaining the reflection spectra of the paper insulation samples and constructing two correlation lines to determine the degree of polymerization and humidity. The most significant result of the article is the establishment of the dependence of the reflection coefficient of the paper on the concentration of water exceeding 4% and the position of the minimum in the reflection spectrum of paper insulation on the degree of polymerization. The significance of the obtained results lies in the fact that the optical method for determining the moisture content and the degree of polymerization of paper insulation using the constructed correlation lines is highly accurate and does not require the use of additional reagents and complex calculations.

Risk Priority Evaluation for Power Transformer Parts Based on Intuitionistic Fuzzy Preference Selection Index Method

The risk assessment of power transformer equipment can not only improve the safety and management level of transformer operation, but also reduce the operation and maintenance costs of the equipment on the basis of ensuring the overall reliable operation of the power system. As a result, it can enhance the rewards of assets investment. The quantitative analysis of power equipment risk often contains qualitative indicators that are difficult to quantify. These indicators have the characteristics of fuzziness. In order to improve the accuracy and reliability of risk assessment results, this paper proposed a new risk evaluation method based on intuitionistic fuzzy set. Firstly, language variables are transformed into corresponding intuitionistic fuzzy numbers. Secondly, a novel entropy of intuitionistic fuzzy set is established. Thirdly, a weighting method for determining each expert’s importance is proposed based on the new propose entropy. Furthermore, an extended preference selection index is put forward under intuitionistic fuzzy environment. Finally, an example of the risk assessment of power transformer components is discussed to illustrate the effectiveness of the new risk evaluation method.

Electromagnetic transient characteristics and overvoltage suppression strategy of renewable energy-oriented power system connected by gas-insulated transmission lines

New energy systems, such as wind power and photovoltaic and distributed power supply, in the power generation and grid-connected transmission system basically will use stronger insulation design, higher operational safety, and smaller footprint GIL equipment, while the new energy transmission system of the smart grid development trend requires accompanying the electronic transformer equipment to promote a large area. However, the current GIL equipment used in new energy transmission systems has caused great electromagnetic interference to the electronic equipment due to the compact layout of the equipment and the transient signals generated by normal operation, which has seriously restricted the development of smart grids and became a major obstacle to the grid connection of new energy systems. In order to study the characteristics and developmental law of transient electromagnetic interference signal of GIL equipment in new energy transmission and transformation system, this study proposes a dynamic arc model based on an optimized arc extinguishing criterion, verifies the correctness of the improved dynamic arc model through theoretical analysis, simulates calculation combined with the test measurement data, and compares and analyzes the simulation results with test measurement data to study the transient electromagnetic interference source signal during arc burning duration. The simulation results and test data are compared and analyzed to study the pulse steepness, size of the wave head, and overall waveform development law of the transient electromagnetic interference source signal during the arc burning process. It is concluded that the dynamic arc model based on the optimized arc extinguishing criterion can be better used to study the transient electromagnetic interference signal in the GIL equipment. Meanwhile, the transient electromagnetic interference signal has the characteristics of large amplitude and high frequency, the maximum overvoltage can reach 1.9 p.u., the UHF can reach 30 MHz, and the wave head rise time is about 12 ns. This study provides theoretical support for subsequent research on suppressing transient electromagnetic interference source signals, improving the anti-electromagnetic interference performance of electronic devices, and is dedicated to solving the obstruction problem in the process of grid connection of new energy transmission and substation systems.

Operational Status Monitoring and Fault Diagnosis System of Transformer Equipment

In order for valuable distribution transformer data to provide a potential solution for monitoring abnormal conditions, the authors propose a data-driven abnormal state monitoring data acquisition algorithm for distribution network transformers. The algorithm can alert operators and maintenance personnel of abnormal conditions in a timely manner. In the proposed algorithm, the Spearman rank correlation coefficient is used to display the correlation between phase currents, and its t statistic is used to determine whether there is an abnormality in the determined data collection based on hypothesis testing. Finally, the effectiveness of the proposed algorithm is verified by using the actual data collected from the power grid, and the characteristics of normal and abnormal conditions are analyzed separately. Sensitivity analyses were performed for different significance levels and sampling rates to consider their impact on monitoring results. The application results show that the power grid recovered a total of 12.98 million yuan from 136 households with a power consumption of 17.57 GWh, proving the practicability of the algorithm. Conclusion. The application in the actual power system is given, and the feasibility of the algorithm is proved.

Influence of Air Pollution Factors on Corrosion of Metal Equipment in Transmission and Transformation Power Stations

In this paper, the atmospheric environmental corrosion grade of substations in 11 prefecture level cities in Shanxi Province is evaluated through a metal hanging sheet experiment. Combined with the main environmental factors, such as temperature, relative humidity, and the concentration of main pollution factors, such as SO2, Cl−, dust, etc., the influence of various factors on the corrosion of transmission and transformation equipment is analyzed, and the corresponding anti-corrosion measures are put forward.

Research on IGOA-LSSVM based fault diagnosis of power transformers

Power transformer is an important part of power equipment, and its functionality affects the proper operation of the whole power network. In order to diagnose power transformer faults effectively, the authors propose a fault diagnosis strategy based on an improved locust optimization algorithm for least squares vector machines (IGOA-LSSVM). Firstly, it was required to address the problem that the diagnostic prediction accuracy of the least squares vector machine is reduced due to its parameters. So this paper introduces the locust optimization algorithm with simple algorithm structure and good performance for optimizing the parameters. And at the same time, the authors generate an improved locust optimization algorithm with self-learning factors, proportional weight coefficients and Levy flight strategy. Secondly, the improved locust optimization algorithm is used for optimizing the least squares vector machine parameters. Finally, in the simulation experiments, the results of the benchmark test function illustrate that the IGOA algorithm has better performance, and the test results of a fault samples diagnosis of the power transformer equipment illustrate that the IGOA-LSSVM has good prediction effect and improves the fault identification accuracy compared with ACO-LSSVM and PSO-LSSVM in five types of fault diagnosis.

Difference Analysis of Operation Stability of Vacuum Circuit Breaker in 10KV Power Distribution System

As an important part of power transmission and transformation equipment, vacuum circuit breakers have become the core device for protecting and controlling electrical lines in high-voltage electrical equipment. This paper expounds the different types of test methods for the preventive test of high and low voltage distribution rooms. Taking the 10kV high and low voltage distribution system in use as the analysis object, 37 units are randomly selected as samples, and statistical principles are used to analyze differences, extract point estimation and interval Estimating eigenvalues, judging the stability and balance of the overall operation of the vacuum circuit breaker in the power distribution system, and providing a basis for the safe use and preventive testing of the power distribution system.

Application of comprehensive diagnosis technology in fault analysis of 35kV box transformer in wind farm

Using on-line monitoring means to monitor the state quantity of power equipment is the trend of equipment diagnosis and evaluation, but it is usually difficult to accurately judge the hidden dangers of equipment by using a single means. This paper puts forward the transformer comprehensive on-line monitoring technology, which can effectively identify the equipment faults through multi state quantity and long-time comprehensive analysis. The relevant achievements are applied to the fault analysis of 35kV box-type transformer in a wind farm. The qualitative classification of fault category is realized by integrating three state quantities: temperature, oil color spectrum and iron core grounding current; Through disassembly inspection, the effectiveness of the integrated on-line monitoring system is proved; The analysis of fault mechanism is realized by using finite element electromagnetic field calculation. The technology of transformer comprehensive diagnosis in this paper has a very important reference for the defect analysis of transformer equipment.

Fuzzy Clustering of Infrared Image Features Based on Lazy Snapping Algorithm

Substation equipment is an important part of the power grid, which undertakes the function of power transmission and conversion and directly affects the operation status of the whole substation and power system. When the substation equipment is in an abnormal working state, the temperature will change. Therefore, the temperature information of the substation equipment is used as the judgment basis to complete the judgment of the working state of the equipment, which can realize the fault diagnosis of the substation equipment and ensure that the power system works in a safe and reliable environment. In this paper, according to the characteristics of the transformer equipment shape stability, the invariant moment is used to extract the infrared image feature of the transformer equipment. The support vector machine is used to complete the classification and recognition of the image. Hu invariant moments and Zernike invariant moments are used to extracting features respectively, and the results of feature extraction are used as training samples to train support vector machines for recognition. Using the Lazy Snapping algorithm to complete the infrared image segmentation processing of substation equipment, the target region is extracted from the background completely, and the segmentation image information is completed. In the experimental test, through the test of the recognition model constructed by invariant moments, it is proved that the recognition accuracy of Zernike invariant moments combined with support vector machine in this paper is higher, and the Lazy Snapping algorithm has obvious advantages in segmentation quality compared with other methods. Therefore, the method of intelligent identification and diagnosis of the thermal fault of substation equipment studied in this paper has important practical significance for the establishment of an online diagnosis system.

ТЕНДЕНЦИИ РАЗВИТИЯ СИЛОВЫХ ТРАНСФОРМАТОРОВ ПРИ ИНТЕЛЛЕКТУАЛИЗАЦИИ ЭЛЕКТРОЭНЕРГЕТИКИ

The development trends of transformers in two global directions are considered: improvement of equipment and technology of existing transformer equipment and the use of modern transformers with renewable and non-traditional energy sources with intellectualization elements

Influence of Wind Turbines on the Operating Modes of the Distribution Network

The paper aim was to study the normal functioning modes of consumers power supply by the distribution network, taking into account the electricity production using wind turbines, as well as to develop recommendations that allow optimizing power consumption modes. The goal was achieved by analyzing the initial information on the network section topology, the technical characteristics of linear and transformer equipment, as well as consumption and generation profiles. The most significant result of the paper was the determination of the fact that the connection of wind turbines according to the “install and forget” principle without prior justification of both connection place and wind turbine capacity often leads to significant change in the operating characteristics and additional technical losses of active power. In this case, the main part of the losses falls on power lines. The significance of the obtained results lies in the fact that the main problems, associated with the coordination of the operating modes of distributed generation facilities and load, were identified and possible technical solutions were proposed to improve the situation. Based on the obtained results it is possible to conclude that when connecting a wind turbine to a distribution network, it is necessary to take into account both the capacity and the installation location of the equipment, which significantly change the values of the operating parameters of electrical networks. It has been shown that use of energy storage devices, as well as the network reconstruction, can make it possible to minimize active power losses and carry out balance of regimes.

Temperature Distribution and Equipment Layout in a Deep Chamber: A Case Study of a Coal Mine Substation

With the gradual depletion of shallow resources, the process of resource exploitation is being transferred to greater depths. The temperature of the surrounding rock increases gradually in the process of deep mining, and the temperature of the underground substation chambers often exceeds the normal working temperature in summer. In this paper, the equipment layout and ventilation conditions of the deep substation chamber of the Jiangxi Qujiang Mining Company were selected as the research subjects, and numerical simulation software was used to study the temperature distribution within the chamber under different conditions by changing the combinations of the wind velocity and air temperature of the inlet air of the chamber. The study showed that, under the conditions of the current equipment layout and air door size, the equipment temperature was prone to being too high in the summer. Therefore, the layout of the equipment was optimized based on the simulation results. The transformer equipment was changed from the original serial mode to the juxtaposed mode, and the size of the air door was increased, which effectively reduced the disturbance of the air flow and the length of the air flow path in the chamber. This meant that the high temperature area of the chamber was at the end of the chamber, which efficiently reduced the area of the high temperature zone and ensured that the equipment was in a lower temperature environment. This method can be used as a reference for temperature distribution, layout, and temperature control measures within buildings.

Computing offloading method with low power consumption constraint for smart grid

With the development of the Power Internet of Things, power transmission and transformation business have a wide range of operation, large regional differences, a wide variety of equipment and other problems, making the access and deployment of mass sensors with low power consumption crucial. In order to realize the cloud-side collaborative computing of the Internet of Things, it is necessary to build a low-power information acquisition and transmission network, and realize the low-power deployment of the low-power sensor network and equipment. The embedded node device can be used as the basis of low-power transmission network to realize low-power transmission of cloud-side collaborative computing information, combined with the existing low-power transmission and transformation equipment.

Research on Operation Safety of Power Transmission and Transformation Equipment in Wind Power Plant

Wind power generation is clean renewable power without environmental pollution, so wind power plant has been paid more and more attention, and has been popularized in recent years. As an unstable energy, wind power has high requirements for the operation, management and protection of facilities to ensure the safe operation of the system. In order to improve the power efficiency, it is necessary to conduct in-depth research and Discussion on the operation management and guarantee countermeasures of the current wind power plant equipment. Based on this, this paper deeply discusses the key factors restricting the operation safety of the power transmission and transformation equipment of the wind power plant, and puts forward the safety technical means to enhance the operation safety of the power transmission and transformation equipment. It is expected to have a certain reference significance for the development of the power transmission and transformation equipment of the wind power plant, Thus, it has a positive reference for the management and guarantee measures of the current operation of power transmission and transformation equipment in wind power plants.

Multifeature Extraction and Semi-Supervised Deep Learning Scheme for State Diagnosis of Converter Transformer

The research on intelligent diagnostic models for power transmission and transformation equipment has attracted increasing interest. In the design of practical diagnostic models, the supervised learning strategy is often used. This put forward higher requirements for the number of labeled data. However, in industrial applications, the cost of collecting a large number of relevant data and effectively labeling is high. At the same time, in the case of unknown faults, the lack of prior knowledge makes accurate classification difficult to achieve. This work designs a semi-supervised hybrid framework to diagnose the state of the converter transformer in terms of the labeled data which is limited. The framework consists of three main modules: multifeature graph generation, semi-supervised training, and soft voting decision. The graph generation module encodes the vibration signal into time, frequency, and energy graphs by calculating the Gramian angular summation fields (GASF). The semi-supervised learning module integrates unsupervised learning and supervised learning strategies trained by partial label information and data reconstruction errors. The decision-making module makes multifeature decisions through soft voting. The effectiveness of the hybrid framework is verified by comparative experiments. The experimental results show that the scheme can learn and diagnose intelligently under harsh datasets.

A Collaborative optimization approach for grid equipment overhaul/retirement strategy considering system effectiveness and risk

In order to improve the science of grid equipment overhaul and decommissioning decisions, a collaborative optimization method of equipment overhaul/decommissioning strategy considering system effectiveness and risk is proposed. The interaction effect between overhaul and decommissioning is analysed from the perspective of system effectiveness, and 2 attributes of integrated cost input and system reliability improvement are proposed, and then a prospect model with cost/benefit attributes is established based on the prospect theory. Then, with the maximum integrated prospect value as the optimization objective, a collaborative optimization model of overhaul/decommissioning strategy is established with the system risk level as the constraint. Finally, the effectiveness of the proposed method is verified by taking the transformer equipment of an urban area distribution network as an example.

An Overview of Digital Twin Concept for Key Components of Renewable Energy Systems

Renewable energy (RE) is green and low-carbon energy, which can not only protect the environment, promote the technological diversification of the energy supply system, accelerate the adjustment of energy structure, but also has important significance for the sustainable development of economy. With the increasing complexity of the problems of renewable energy system asset management and ensuring the operational reliability of electric power equipment, it's necessary to establish remote, online, reliable monitoring and inspection techniques for the state evaluation of electrical equipment during the full life cycle. In order to meet these demands, the digital twin is a very suitable technology. In recent years, there are numerous scientific papers demonstrating DT's capabilities in virtual simulation, condition monitoring (CM), power optimization and fault diagnosis for RE generation systems, transmission and transformation equipment and storage systems. The majority of the research focusing on product design, maintenance of operation, condition monitoring and fault decision-making has provided many valuable contributions to academia and industrial fields. Nevertheless, all this valuable information is scattered over many literatures and it is lack of systematic generalization. In this article, different applications of DT technology in RE system are analyzed, advanced methods and theories are summarized comprehensively, and the development trend of DT technology in renewable energy system in the future is introduced.

Operation and Maintenance of High and Low Voltage Transformer and Distribution Equipment

Operation and Maintenance of High and Low Voltage Transformer and Distribution Equipment