Substation Equipment Research Articles

Research on the Design of UAV Relay Charging High-rise Platform for Electrical Equipment Live Detection in Substation

The multi-rotor UAV inspection technology has received extensive attention in the live detection of electrical equipment in substations and has begun to be practically applied. However, due to the short endurance and the characteristics of intermittent operations, the UAV needs to frequently travel between the operational airspace and the cabin, which seriously affects the operational efficiency of the inspection. This paper first introduces the traditional substation electrical equipment live detection technology and then summarizes the application of UAV inspection in the substation electrical equipment live detection. Finally, in view of the shortcomings of the existing technology, this paper proposes a design scheme of a relay-charging high-rise platform for live detection and inspection of electrical equipment in substations. The relay charging high-rise platform can be divided into six parts according to the functional structure: high-altitude apron, UAV landing guidance system, UAV automatic binding system, high insulation strength power supply system, and platform monitoring system. In this paper, the overall structure of the relay charging high-level platform and the technical solutions of each component are described in detail. The technical solution can effectively improve the efficiency and safety of multi-rotor UAV inspection operations for live detection of electrical equipment in substations.

Intelligent Inspection Technology of Substation Secondary System Based on Machine Vision

To solve the problems of low efficiency and poor precision in the current inspection of substation secondary systems, machine vision technology is introduced to conduct the design and research of inspection technology. It acquires equipment images and manufactures an image data set of that secondary system equipment of the transformer substation. It also processes and segments an inspection guideline image using machine vision technology and realizes itinerant inspection of the secondary system instrument equipment of the transformer substation based on the acquired inspection image. The comparative experiments show that the efficiency and accuracy of the new inspection technology have been significantly improved.

Infrared Image Target Detection of Substation Electrical Equipment Using an Improved Faster R-CNN

Infrared camera can be used to monitor the condition of substation electrical equipment. Fast and accurate target detection algorithm is the key for infrared intelligent on-line routing inspection. However, the performance of traditional detection algorithm is poor due to the complex background of substation. To solve this problem, this paper proposes a target detection model based on the improved faster region-based convolutional neural networks (Faster R-CNN), which can be used for automatic detection of five kinds of electrical equipment in substations. The feature extraction network of this model is improved based on VGG16 by abandoning some high-level convolutions to accelerate the training and testing speed. Meanwhile, the 1:3 and 3:1 aspect ratio of anchor are added to improve the detection accuracy of elongated equipment. Experiments are performed on an infrared image dataset of substation to detect five types of equipment. The robustness tests of our model are carried out, too. The results show that our model performs well in detection accuracy and speed, achieving a mean detected accuracy of 95.32% and running at 11 frame/second. In addition, our model is robust to noise and lightness, which is suitable to other substations. Comparing to other models, our model has the highest mAP@0.5 of 92.78%.

Resilience-Based Sequential Recovery Planning for Substations Subjected to Earthquakes

Electrical substations are crucial components in a power system while substation equipment can be easily damaged in an earthquake. Repairing the damaged equipment as soon as possible is essential to restore the functionality of the substation system and further secure the sustainable power supply of the power grid after the earthquake. However, the damaged equipment cannot be repaired simultaneously due to the limitation of emergency repair resources, and the recovery rate of the substation functionality will vary dramatically depending on the selection of different equipment repair sequences. Therefore, a sensible equipment repair sequence is needed to improve the recovery efficiency of the substation functionality. A resilience-based method was thus proposed in this paper to optimize the equipment repair sequence with the objective of minimizing the resilience index of the substation, which was defined as the post-earthquake overall functionality loss. The heuristic algorithm was incorporated into the systemic resilience assessment framework to find the optimal equipment repair sequence according to different initial damage states of equipment and the limitation of emergency repair resources. A case study was performed on a real-world substation system to illustrate and verify the proposed method, the analysis results can aid decision-makers in the post-earthquake recovery planning.

Analysis and Design of Integrated Intelligent Anti-error System for Substation

A new comprehensive intelligent anti-error system that meets the requirements of smart substations is proposed. This new system can overcome the problem that the microcomputer anti-error system lacks operation error prevention technology for secondary equipment and also lacks operation and maintenance operations under the integrated control operation mode. Firstly, this paper analyzes the characteristics of the anti-error system, and the principle function of the judgment model. And then, an anti-misoperation process system is established for work scenarios such as information collection and monitoring, remote control operation error prevention, sequential control operation error prevention, local operation error prevention, secondary equipment, operation, and maintenance. This paper finally builds a realtime online anti-error system that can be intelligently analyzed for the whole business process to ensure the safety of intelligent substation equipment operation.

Thermal Fault Diagnosis of Electrical Equipment in Substations Using Lightweight Convolutional Neural Network

Real-time equipment condition monitoring is crucial to ensure the regular operation of the electric system. However, the deployed heavy convolutional neural networks (CNNs) are defective for edge computation and offline diagnosis. The purpose of this article is to present a system for detecting overheating faults of substation equipment using infrared photos and U-Net deep learning techniques. First, a stepwise encoder employs a lightweight CNN (LCNN) based on inverted residuals with depthwise separable convolution. The fault location is then decoded in the decoder using stepwise upsampling and nearest-neighbor interpolation. We additionally incorporate low-level detail feature information from the encoder to include additional fault data. Finally, testing findings on our dataset demonstrated the proposed method’s superior reliability and efficiency under a variety of evaluation metrics. Ultimately, we reached a lighter structure and leading estimation with a small training dataset, so our method is well-suited for deployment on mobile devices.

Эко-НИОКР – 18 лет для охраны птиц на объектах электросетевого комплекса России

Эко-НИОКР – 18 лет для охраны птиц на объектах электросетевого комплекса России

PROSPECTS FOR THE DEVELOPMENT OF POWER SUPPLY SYSTEMS FOR AGRICULTURAL FACILITIES BASED ON DISTRIBUTED ENERGY SUPPLY

Modern trends in the development of electric distribution networks for agro-industrial facilities related to the introduction of more complex production technologies, increased consumer loads and stricter requirements for reliability and energy efficiency of networks are considered. In the conditions of sectoral supply restrictions and the need to replace imported components, the possibilities of implementing the advantages of distributed electric power in flexible energy supply of agro-industrial and social facilities on the basis of domestic technology and innovative methods are presented. (Research purpose) The research purpose is considering the technical support of distributed generation systems and analyzing possible problems that may arise during the integration of distributed generation sources into the electrical system of the agro-industrial complex. (Materials and methods) Used statistical data to analyze the availability of agro-industrial facilities with distributed electric power. (Results and discussion) It has been shown that the agro-industrial complex is dominated by objects that are far removed from the center of the energy system, with electrical equipment that is morally and technically outdated, which affects the reliability of power supply and the quality of electricity. It was determined that the introduction of distributed generation sources requires modernization or updating of the main electrical equipment of distribution points or substations. Alternative technical solutions have been proposed to improve the quality of electricity supplied to consumers and the reliability of power supply systems, focused on the maximum approximation of the power source to the consumer by placing distributed generation sources near the objects of the agro-industrial complex. They gave specific schemes of power supply systems, the results of technical and economic analysis and options for using traditional and renewable sources of electricity. (Conclusions) It was stated that the further development of the agro-industrial complex facilities is associated with an increase in the level of energy supply, reliability, energy efficiency and environmental friendliness of power supply systems through the introduction of modern distributed generation systems based on traditional, renewable and combined sources of electricity.

Analysis of Substation Joint Safety Control System and Model Based on Multi-Source Heterogeneous Data Fusion

As the number of substations continues to increase globally and the market demand continues to rise, the current workload of maintenance and daily operation of substations in power grids cannot meet the current demand if only relying on manual work, and the design and implementation of intelligent safety control solutions for substations is imperative. Therefore, this paper proposes a joint safety control system and model analysis for substations based on multi-source heterogeneous data fusion. Firstly, a three-dimensional visualization substation efficient interactive operation platform is realized, which realizes the functions of substation scene roaming, system login, information management, equipment parameters, status viewing and operation ticket pushing; after that, a variety of intelligent hardware devices for data collection, such as multi-dimensional terminal sensors, intelligent wearable devices, intelligent pre-built positioning installation measure rod, and substation intelligent inspection robots are designed to greatly improve the substation inspection efficiency and realize real-time monitoring and data interaction in the inspection process. Finally, we propose an Attention-LSTM-based prediction model for substation multidimensional data, which can predict power equipment spatio-temporal data in the short term, and the prediction results can be combined with intelligent devices for joint diagnosis. The Attention-LSTM prediction model is well-trained in transformer oil temperature experiments, and the experimental results show that this model can provide early warning for the abnormal state of substation power equipment. In summary, this thesis describes a set of complete and practically feasible intelligent safety control methods for substations. The joint safety control system and model analysis of the substation based on multi-source heterogeneous data fusion designed in this paper is mainly oriented to the substation as an electric power workplace, which has quite a vast application prospect for energy equipment.

Swin-RGC: Swin-Transformer With Recursive Gated Convolution for Substation Equipment Non-Rigid Defect Detection

Swin-RGC: Swin-Transformer With Recursive Gated Convolution for Substation Equipment Non-Rigid Defect Detection

Infrared Thermal Image Instance Segmentation Method for Power Substation Equipment Based on Visual Feature Reasoning

Infrared Thermal Image Instance Segmentation Method for Power Substation Equipment Based on Visual Feature Reasoning

Numerical modeling for the seismic response of interconnected electrical substation equipment

Numerical modeling for the seismic response of interconnected electrical substation equipment

Implementing Power System Protection Algorithms in a Digital Hardware-in-the-Loop Substation

Real-time power system algorithms are necessary for grid advancement, but few practical applications have been demonstrated in a research usability context. The work in this paper consists of implementing a data correction algorithm, its deployment within realistic substation equipment, and the design of a testbed to demonstrate the overall framework and its usability. A digital simulator is used to generate Phasor Measurement Unit (PMU) data for the algorithm. The algorithm corrects data that has been perturbed by GPS spoofing attacks. Finally, the entire system is visualized on power-utility software, SEL Synchrowave Operations. Considerations and potential issues are discussed and are applicable to digital Hardware-in-the-Loop (HIL) systems as well as to field-deployed systems. The system is demonstrated with 11 simultaneously GPS-spoofing attacked PMUs in a 21 PMU system. The HIL testbed developed in this paper provides a valuable tool for easily testing a variety of real-time power system algorithms and the communications and control necessary for them operate successfully.

Predictive Maintenance of Power Substation Equipment by Infrared Thermography

Predictive Maintenance of Power Substation Equipment by Infrared Thermography

A fast identification method of UAV inspection image target for substation equipment

A fast identification method of UAV inspection image target for substation equipment

An Intelligent Point Cloud Recognition Method for Substation Equipment Based on Multiscale Self-Attention

An Intelligent Point Cloud Recognition Method for Substation Equipment Based on Multiscale Self-Attention

A fast identification method of UAV inspection image target for substation equipment

A fast identification method of UAV inspection image target for substation equipment

An Early Warning Model for Intelligent Operation of Power Engineering based on Kalman Filter Algorithm

The accurate early warning of intelligent operation of power engineering can find the abnormal operation of substation equipment in time and ensure the safe operation of substation equipment. Thus, an early warning model for intelligent operation of power engineering based on Kalman filter algorithm is constructed. In this model, the noise elimination method of substation equipment inspection image based on particle resampling filter algorithm is introduced. After removing the noise information of operation situation inspection image of substation equipment, the gradient direction histogram feature, lab color space feature and edge contour feature in the image are extracted by the multi-feature extraction method for intelligent operation of power engineering based on multi-feature fusion. These features are combined to form the feature description set of equipment operation situation. The feature description set is used as the identification attribute set of the anomaly identification and early warning model for intelligent operation of electric power engineering based on Kalman filter algorithm to complete the anomaly identification and early warning of equipment operation situation. The test shows that when the model is used to observe the temperature change trend of the top layer of the transformer, the temperature error is very small, and the early warning accuracy for the abnormal temperature of the top layer of the transformer is very high, so the abnormal operation of the substation equipment can be found in time.

Insulation Coordination in HV/A Substation Equipment Cells

Insulation Coordination in HV/A Substation Equipment Cells

The impact of fusion welding in corrosion diagnosis of joint systems using ultrasonic technique

Nowadays the ultrasonic guide wave technique is the most accurate method in defect detection. Defect detection in the joined and continues systems make some measurement problems due to the structure and propagation of ultrasonic waves in these systems that must be considered for obtained accurate results. In this paper we analysis the manner and the effect of welded points in joint systems. For this aim we specially considered the grounding grids as a joint system and study the problem of the ultrasonic waves in corrosion diagnosis of this system. The grounding grids are the most important systems that increasing safety of power equipment in substations. The conductors of grounding grids usually connected together by fusion welding or bolts and nuts. But fusion welding make some problems for corrosion diagnosis of grounding grids and also pipelines while using ultrasonic technique. The main problem is incorrect results that obtained due to the interference of ultrasonic waves. This paper presented a new method to eliminating the effect of fusion welding points by placing the ultrasonic transducers in right locations. The influence of the soil is considered. Computer simulation results have shown the effect of this interference in accuracy of the result and effectiveness of the new method.