Substation Environment Research Articles

Design and research of a monitoring and environmental testing analysis system for substation status

Abstract By testing and analyzing the real substation environment, and analyzing and fitting on-site data, a system that simulates the operating environment of the real substation is designed, and the goal of replicating a typical on-site electricity environment is achieved. Testing and analysis are conducted on the selected substation area, and light and heavy load noise is collected for spectrum analysis and measurement point attenuation analysis. The LMF (Late Multimodal Fusion) algorithm is used and test data are fitted based on the trust region theory. Conducting noise testing and attenuation analysis in the substation area has laid the foundation for research on substation status monitoring and environmental monitoring.

An automatic robot for ultrasonic partial discharge detection of gas-insulated switchgear

Purpose Gas-insulated switchgear (GIS) stands as a pivotal component in power systems, susceptible to partial discharge occurrences. Nevertheless, manual inspection proves labor-intensive, exhibits a low defect detection rate. Conventional inspection robots face limitations, unable to perform live line measurements or adapt effectively to diverse environmental conditions. This paper aims to introduce a novel solution: the GIS ultrasonic partial discharge detection robot (GBOT), designed to assume the role of substation personnel in inspection tasks. Design/methodology/approach GBOT is a mobile manipulator system divided into three subsystems: autonomous location and navigation, vision-guided and force-controlled manipulator and data detection and analysis. These subsystems collaborate, incorporating simultaneous localization and mapping, path planning, target recognition and signal processing, admittance control. This paper also introduces a path planning method designed to adapt to the substation environment. In addition, a flexible end effector is designed for full contact between the probe and the device. Findings The robot fulfills the requirements for substation GIS inspections. It can conduct efficient and low-cost path planning with narrow passages in the constructed substation map, realizes a sufficiently stable detection contact and perform high defect detection rate. Practical implications The robot mitigates the labor intensity of grid maintenance personnel, enhances inspection efficiency and safety and advances the intelligence and digitization of power equipment maintenance and monitoring. This research also provides valuable insights for the broader application of mobile manipulators in diverse fields. Originality/value The robot is a mobile manipulator system used in GIS detection, offering a viable alternative to grid personnel for equipment inspections. Comparing with the previous robotic systems, this system can work in live electrical detection, demonstrating robust environmental adaptability and superior efficiency.

Research on Residual-Current Measurement System of Substation Considering Magnetic Shielding Effect.

Residual current is an important monitoring quantity of a power system, and a current sensor plays an important role in detecting current. The substation environment is complex. In addition to the power frequency signal, residual current also has AC and DC components. But it is also affected by the stray magnetic field of the substation. Therefore, the accuracy of the current sensor demands higher requirements. The tunnel magnetoresistive sensor has the advantages of a stable operation, high efficiency, and energy saving, but it is easily affected by the external stray magnetic field during measurements, resulting in a large error. Therefore, this paper proposes a residual-current sensing monitoring system considering the magnetic shielding effect. The root mean square error of the magnetic shielding structure is only 0.572 mA, which can effectively reduce the influence of the external magnetic field and improve the detection accuracy. At the same time, the DC measurement error is less than 1%, the AC measurement error is less than 5%, and the hybrid AC/DC error is less than 8%. It has good response ability and can accurately detect residual current.

Self-detection method for measurement error of capacitor voltage transformer considering conversion error.

The measurement error of capacitor voltage transformers (CVTs) has poor stability under the complex environment of substations. Conventionally, error detection is performed by regularly comparing the output of standard transformers, which lacks real-time performance. Moreover, CVTs are prone to operating in an out-of-tolerance state. Thus, this study first analyzes the basic principle of the CVT measurement error self-detection method based on principal component analysis under the constraints of three-phase symmetrical operating characteristics of a power system. Then, the impact of the signal conversion error of analog-to-digital conversion equipment on the self-detection results of CVT measurement errors in engineering applications is analyzed, and a multi-layer wavelet analysis signal denoising method is proposed to enhance the self-detection ability of CVT measurement errors. Finally, simulations show that the proposed method can identify an error change of 0.1%, meeting the self-detection requirements for the measurement error at 0.2 class.

Design and Implementation of Environmental Monitoring System for Substation Based on Internet of Things

At present, the environmental monitoring of the substation suffers from complex wiring, low intelligence, high staff work intensity, and a lack of information-based overall management. Moreover, the distribution of substations is relatively scattered, making it complex and costly to set up a dedicated communication network. In response to these problems, this paper combines modern communication technology, sensor technology, and mobile intelligent terminal development technology to study an overall information-based substation environmental monitoring system. The monitoring system proposed in this paper includes a main controller, a data collection terminal, and a mobile communication terminal. The environmental data collected by the main controller is sent to the server through the communication method of subscription and substation using wireless communication technology, and the interface of the mobile communication terminal can display indoor environmental monitoring data. When the environmental data of the Substation exceeds the set threshold value to issue an early warning alert, the user can control it remotely through the mobile communication terminal to improve the indoor environment of the Substation. The system has a simple operation interface, low power consumption, and strong expansion compatibility, which effectively realizes remote monitoring and control of the substation environment and has good engineering application value.

Integrated Sensing, Communication, and Computing for Self-Powered UAV-Assisted Corona Detection in High-Voltage Substations

Unmanned aerial vehicle (UAV) provides a cost-efficient solution for corona detection in high-voltage substations. In this article, we address the integrated sensing, communication, and computing joint optimization problem. The objective is to maximize the average amount of data sensed by UAV through jointly optimizing sensing, i.e., acquisition frequency and image depth selection, communication, i.e., task splitting and power control, and computing, i.e., local computation resource allocation. We propose a dueling deep Q network-based integrated sensing, communication, and computing joint optimization algorithm for self-powered UAV named DESCANT to solve the problem. DESCANT explores dueling DQN to intelligently learn the optimal strategy under complex electromagnetic environment of high-voltage substations. The historical information of electromagnetic interference (EMI) is incorporated into the state construction to improve convergence and learning optimality. DESCANT also realizes energy awareness through the dynamic adjustment of resource management based on energy consumption as well as harvested energy. DESCANT is compared with state-of-the-art algorithms and its superiority is verified through simulations.

A Non-Invasive Circuit Breaker Arc Duration Measurement Method with Improved Robustness Based on Vibration–Sound Fusion and Convolutional Neural Network

Previous studies have shown that the contact wear estimation of circuit breakers can be based on the accumulative arc duration. However, one problem that remains unresolved is how to reliably measure the arc duration. Existing methods encounter difficulties in implementation and suffer from limited accuracy owing to the impact of the substation environment. To overcome these issues, this article presents a novel, non-invasive method for measuring arc duration that combines vibration–sound fusion and convolutional neural network. The proposed method demonstrates excellent performance, achieving errors below 0.1 ms under expected noise conditions and less than 1 ms in the presence of various forms of noise, transient interference, and even sensor failure. Its advantages include its ability to accurately measure arc duration and its robustness against noise and interference with unknown patterns and varying intensity as well as sensor failure. These features make it highly suitable for practical deployment in substation environments.

A Semantically Annotated 15-Class Ground Truth Dataset for Substation Equipment to Train Semantic Segmentation Models

The lack of annotated semantic segmentation datasets for electrical substations in the literature poses a significant problem for machine learning tasks; before training a model, a dataset is needed. This paper presents a new dataset of electric substations with 1660 images annotated with 15 classes, including insulators, disconnect switches, transformers and other equipment commonly found in substation environments. The images were captured using a combination of human, fixed and AGV-mounted cameras at different times of the day, providing a diverse set of training and testing data for algorithm development. In total, 50,705 annotations were created by a team of experienced annotators, using a standardized process to ensure accuracy across the dataset. The resulting dataset provides a valuable resource for researchers and practitioners working in the fields of substation automation, substation monitoring and computer vision. Its availability has the potential to advance the state of the art in this important area.

Research and application of box type substation operation safety management and control system based on three-dimensional modeling and UWB positioning

This paper proposes a box type substation operation safety management and control system based on GIM modeling technology and UWB positioning technology to address the current challenges of personnel and vehicle control, single control methods, difficult information exchange, and blind spots in on-site substation operations. This system integrates safety control measures throughout the entire operation process of the substation before, during, and after operation, achieving closed-loop control of operation safety. Firstly, laser point cloud and power system GIM technology are used for three-dimensional modeling of substation environment and equipment. Then, UWB positioning technology is used for indoor positioning. Combined with various business systems such as substation work tickets and SCADA, the qualification review of station personnel and vehicles before substation operation is achieved, real-time monitoring of personnel status and movement trajectory during operation, and real-time monitoring of on-site environment after operation are achieved. The system has been deployed and applied to a 35kV box type substation in Guizhou, and through a period of actual operation, it has effectively controlled the operation site.

Measurement and Analysis on Magnetic Field Influence of Substation for Magnetic Shielding Device

The residual magnetic field in a magnetic shielding device with a multilayer high permeability material (permalloy) structure can be obtained at the nanotesla (nT) level or even lower. At present, in the process of designing a magnetic shielding device, most of the external environmental magnetic field settings are set at the size of the Earth’s environmental magnetic field, but the instruments inside the magnetic shielding device need to be powered, the active compensation coil needs to be powered, and the degaussing coil of passive shielding layer needs to be powered, so substations need to be used around magnetic shielding devices. The magnetic field generated by the substation will affect the magnetic shielding device, so this paper analyzes and measures the magnetic field generated by the substation. Firstly, the finite element model of a substation is established, and the influence of different substations on the environmental magnetic field is analyzed by changing the power. Secondly, the test method of a substation environment magnetic field is determined. Finally, the site test was carried out to measure the influence of different power substations and different distances on the magnetic field, and its influence on the magnetic shielding device was analyzed, which provided an important basis for the construction of the magnetic shielding device.

Research on rapid construction technology of three-dimensional safety control area for the complex maintenance work environment of substation

According to the actual needs of the substation operation and maintenance team, this paper studies the defect video intelligent analysis technology in realizing three-dimensional cross-border early warning, analyzes the principle and early warning application of narrowband millimeter-wave technology and develops a set of 3D cross-border early warning system for substation maintenance operation. The system adopts wideband network technology to realize the remote operation and stable data transmission between the system and the warning and analysis service software of mobile terminal. In this early warning analysis system, this study uses the combination of intelligent video analysis and millimeter-wave radar dynamic target capture to solve many deficiencies in early warning accuracy by relying solely on intelligent video analysis and early warning. Through the on-site verification of the test system, the system’s overall function is consistent with the substation maintenance and maintenance requirements. It is simple to use, and the accuracy of the crossover warning reaches more than 85%.

Optimization of Positioning Error and Time for UWB and Virtual-Real Scenes Similarity Measure Based on Error Model

To overcome the problem of large UWB positioning errors caused by obstacles and other factors in the complex environment of substations, a positioning method combining UWB and virtual-real scene similarity measures is proposed, which effectively improves the positioning accuracy of substation operation and maintenance personnel. To further improve the positioning accuracy of the operation and maintenance personnel in the complex environment of the substation, and reduce the positioning time, this paper analyzes the influence of the virtual scene image acquisition step (x, y, yaw, pitch) on the positioning error. Firstly, the mathematical relationship between the step size parameter and the positioning error as well as the positioning time is quantified using the spatial geometric relationship and probability error theory, and the spatial error model of the fusion positioning algorithm is established; then, based on the established spatial error model, the acquisition step size and the positioning error and positioning time have been optimized to make the positioning time the shortest under the conditions of allowable positioning error. The experimental results show that the spatial error model established in this paper has high accuracy and the optimization results are reliable; the spatial error model is used to optimize the acquisition step parameters, which can ensure the UWB and virtual-real scenes similarity measurement fusion positioning algorithm with positioning error less than 0.2 m (with confidence greater than 0.95) and positioning time of 0.173 s, which significantly improves the positioning speed.

Research on Transmission Characteristics of 5G Signal for Indoor Substation Based on Ray Tracing

The 5G networks can be used to enhance the transmission ability of substation power services. However, because of the complex and diverse environment of substations, such as the presence of a large number of obstacles of different materials and electrical equipment indoors, we need to conduct wireless coverage modeling and transmission quality assessment. In this paper, the 5G signal transmission characteristics in the indoor environment of substations for the established indoor environment and equipment layout are analyzed using methods such as road loss statistical analysis and 3D ray tracing. It can quickly evaluate the 5G indoor coverage quality of substations and provide technical support for planning a reasonable and efficient 5G network.

Semantic Segmentation of Substation Site Cloud Based on Seg-PointNet

3D point cloud semantic segmentation has been widely used in industrial scenes and has attracted continuous attention as a critical technology for understanding the intelligent robot scene. However, extracting visual semantics in complex environments remains a challenge. We propose the Seg-PointNet model based on multi-layer residual structure and feature pyramid for the LiDAR point cloud data semantic segmentation task in the complex substations scene. The model is based on the PointNet network and introduces a multi-scale residual structure. The residual structure multilayer perception (RES-MLP) model is proposed to fully excavate features at different levels and improve the characterization capabilities of complex features. Moreover, the 3D point cloud feature pyramid module is proposed to characterize the substation scene’s semantic features. We tested and verified the Seg-PointNet model on a self-built substation cloud point (SCP) dataset. The results show that the proposed Seg-PointNet model effectively improves the point cloud data segmentation accuracy, with an accuracy of 89.23% and mean intersection over union (mIoU) of 63.57%. This shows that the model can be applied to substation scenarios and provide technical support to intelligent robots in complex substation environments.

Reliability of SCADA systems in BIH substations

This paper describes the concept of modern SCADA systems in general, as well as in BiH substations, and its connection to remote control centers, with a focus on redundancy, reliability and availability. Also, benefits from the usage of redundant protocols, RTU redundancy, usage of industrial equipment designed to work in substation environment and parameters needed for these systems are discussed in this paper. Besides local SCADA systems, telecommunication issues regarding connection to remote control centers are also considered.

3D point cloud recognition of substation equipment based on plane detection

Substation equipment identification is a key step in the process of intelligent substation designing. The target recognition of 3D point cloud of substation equipment firstly uses a 3D laser scanner to obtain the 3D point cloud data that can express the surface shape and spatial position of a substation device, then identify the device information by matching it with template point cloud data. Because the point cloud data obtained by 3D laser scanner is affected by equipment attitude and substation environment, there is redundant, missing, and shadow phenomena in the data, resulting in a low algorithm recognition rate. This paper proposes a method combining plane detection and point cloud registration algorithm, achieving substation equipment identification better result. The main steps of the method include: point cloud preprocessing, plane detecting, preliminary filtering based on Umeyama registration method, and Iterative Closest Point (ICP) algorithm identifying. Plane detection is used for the pre-processed point cloud to obtain planar features, then samples and the planar feature templates in template library are preliminarily selected by Umeyama registration method, and substation equipment is finally identified by Iterative Closest Point algorithm. Experiments show that the recognition rate of devices point cloud reaches 92.2% and the recognition time is shorter, which proves that this recognition algorithm has a good recognition effect.

Modeling of the Coupling of the Lightning Shock Wave Flow Circuit in the High Voltage Electrical Network

This article focuses on the aggression of lightning overload on the equipment of the electrical network of sites where storm activity is very dense; and the electrocution of people located in the direct environment of the high-voltage substation during the flow of lightning current to the ground through the ground socket. The modeling of the flow circuit of the shock wave consisting of guard wire, lightning arrester and ground socket couple to the transformer of the high voltage substations, thanks to the approach of a servo block, led to the synthesis of a PID regulator (corrector) whose action is to reject the effects of the overvoltage on the network equipment and to significantly reduce or even cancel the effects of the step or touch voltage due to the distribution of the potential around the ground socket; and thus improve the quality of service of the high-voltage transmission and distribution electricity network, especially in stormy times.

Analysis of the Optimization Strategy Based on the Cooperation of Drones and Intelligent Robots for the Inspection of Substations

With the continuous development of the power system, the operation environment and scale of the power grid substation are more complex. It will become an inevitable trend for automated detection methods to replace manual detection methods because of their intelligence and security. However, at present, the use of intelligent robot inspection substation technology is not very mature, there are visual blindness, long inspection cycle, poor inspection effect, and other problems. By the development trend of the substation, this paper proposes a high altitude, low altitude, and ground inspection strategy of a substation based on the cooperation of UAV and intelligent robots. This strategy uses the grid method to construct the two-dimensional planning of the substation and then optimizes the inspection path of UAV and intelligent robots based on the improved ant colony algorithm. The UAV and the intelligent robot cooperate to realize the real-time inspection of the substation, forming a three-dimensional inspection system of "low-mid-high", "dynamic + static". The simulation results show that the inspection strategy using UAVs and intelligent robots is safer and can effectively reduce inspection time.

Lidar SLAM Based on Particle Filter and Graph Optimization for Substation Inspection

Simultaneous Localization and Mapping (SLAM) is the core technology of intelligent substation inspection robot. Because of lightweight computation, Rao-Blackwellized Particle Filter (RBPF) is widely used in two-dimensional SLAM. However, it suffers from poor positioning accuracy, low robustness and rapid cumulative errors despite recent improvement. This paper presents a lidar SLAM system based on RBPF and graph optimization that can adapt to unstructured operating environment of substation. Firstly, the diversity of particles is increased by rebuilding the resample algorithm to improve the robustness of the system, and high-quality poses are estimated in submaps. Secondly, the multi-submap system is established to construct odometry constraints (one pose corresponds to two submaps). Furthermore, loop detector is an important part of optimization algorithm, and the branch-bound method is used to reduce computation burden and accelerate the loop detection. Finally, global poses of robot are optimized by the whole odometry and loop constraints in real time. Experiment results show that the proposed method is more accurate than other methods, and can maintain and produce high-precision positioning and mapping in complex substation operation and maintenance environment. It provides a new idea for intelligent substation inspection and positioning method.

Research on path planning algorithm of intelligent inspection robot

With the development of intelligent inspection robot technology, inspection robots are widely used in substations to complete the inspection work of substations and move toward intelligent inspection. At present, substations begin to reduce the number of inspection personnel, reduce labor costs, and improve inspection efficiency and ensure the safe operation of electrical equipment in substations by using inspection robots to conduct intelligent inspection of substation equipment. The algorithm is used to realize the path planning of the inspection robot and model the substation environment.