Breaker Status Research Articles

Industrial Fault Detection Systems

This project presents an industrial fault detection system that monitors important electrical and environmental conditions to improve equipment reliability and safety. Using an ESP32 microcontroller, the system checks for issues like fuse and Miniature Circuit Breaker (MCB) status, as well as under and over-voltage situations with a ZMPT101B sensor. It also tracks temperature and humidity levels using a DHT11 sensor. The system displays real-time information on a 16x2 LCD and can be accessed via a web page, allowing operators to monitor conditions from anywhere. By quickly detecting electrical faults and environmental changes, this system helps reduce downtime and maintenance costs.

DLCH-YOLO: An Object Detection Algorithm for Monitoring the Operation Status of Circuit Breakers in Power Scenarios

In the scenario of power system monitoring, detecting the operating status of circuit breakers is often inaccurate due to variable object scales and background interference. This paper introduces DLCH-YOLO, an object detection algorithm aimed at identifying the operating status of circuit breakers. Firstly, we propose a novel C2f_DLKA module based on Deformable Large Kernel Attention. This module adapts to objects of varying scales within a large receptive field, thereby more effectively extracting multi-scale features. Secondly, we propose a Semantic Screening Feature Pyramid Network designed to fuse multi-scale features. By filtering low-level semantic information, it effectively suppresses background interference to enhance localization accuracy. Finally, the feature extraction network incorporates Generalized-Sparse Convolution, which combines depth-wise separable convolution and channel mixing operations, reducing computational load. The DLCH-YOLO algorithm achieved a 91.8% mAP on our self-built power equipment dataset, representing a 4.7% improvement over the baseline network Yolov8. With its superior detection accuracy and real-time performance, DLCH-YOLO outperforms mainstream detection algorithms. This algorithm provides an efficient and viable solution for circuit breaker status detection.

Real-time hardware-in-the-loop approach for adaptive centralized protection schemes using clustering algorithms

The main objectives of adaptive protection are isolating only the faulty network section and operating with varying network topologies and levels of generation. To accomplish this, the settings of protective devices may need to modify if, for example, the network topology is changed. Protection relays can have several predefined setting groups (SGs) depending on the number of possible configurations. However, centralized protection and control devices can store a limited number of setting groups, in many cases by far less than the number of possible network topologies. Therefore, in adaptive centralized protection schemes where online setting calculation is not feasible, a proper method should be used to cluster the different possible configurations and reduce their number to match or be fewer than the number of available SGs in relays. The offline calculated settings for each cluster can be stored in the centralized protection and control devices, which continuously monitor the status of circuit breakers (CBs) online. Then, upon detecting a change in the CB status, the corresponding SG will be activated. This paper presents three new methods for clustering network topologies, considering N-1 contingency in adaptive relay coordination. These methods are compared to the one in the literature and each other in terms of operation time delay of relays. Moreover, to mitigate false operations of relays due to unavailability of communication networks, a setting group is dedicated to the robust setting group. Finally, a practical implementation of the proposed method using IEC 61850 standard is illustrated using two schemes step by step. IEEE 14-bus is selected as a test system to evaluate the applicability of the proposed methods. The results, obtained by using MATLAB, DIgSILENT Programming Language, and hardware-in-the-loop setup show the effectiveness of the proposed methods in minimizing operating time delays of overcurrent relays.

The Methodology for Evaluating the Operating State of SF6 HVCBs Based on IDDA.

To enhance the precision of evaluating the operational status of SF6 high-voltage circuit breakers (HVCBs) and devise judicious maintenance strategies, this study introduces an operational state assessment method for SF6 HVCBs grounded in the integrated data-driven analysis (IDDA) model. The relative degradation weight (RDW) is introduced as a metric for quantifying the relative significance of distinct indicators concerning the operational condition of SF6 HVCBs. A data-driven model, founded on critical factor stability (CFS), is formulated to convert environmental indicators into quantitative computations. Furthermore, an optimized fuzzy inference (OFI) system is devised to streamline the system architecture and enhance the processing speed of continuous indicators. Ultimately, the efficacy of the proposed model is substantiated through validation, and results from instance analyses underscore that the presented approach not only attains heightened accuracy in assessment compared to extant analytical methodologies but also furnishes a dependable foundation for prioritizing maintenance sequences across diverse components.

Power System Fault Detection and Analysis Using Numerical Relay in Power grid Corporation Limited, Shoolagiri

The faults in a power system may be of various nature and they may affect the stability of the power system by causing outage of the line, there by overloading other connected lines and also causing cascading effect in the system. In order to access the nature of fault and analyze the impact of the same in a power system, fault analysis is required to be carried out as the same will be useful for the system operation and to take quick decisions in securing the system. In this paper we discuss the various types of faults in EHV system that may occur in line or substation. These faults are identified by Numerical relays which use IEDs [Intelligent Electronic Device]. The faults identified includes symmetrical and unsymmetrical faults in power system. Further in this project, we have taken into consideration the theoretical and practical study of the fault analysis through Numerical relays. In case of occurrence of Transient faults, Auto re-closure works with dead time of 1 sec. Current, voltage, Breaker status (open, close) are graphically represented by Disturbance Recorder. Events are recorded by Event logger. The above mentioned project for faults and analysis of faults in line or substation were carried out at Power grid Corporation Limited, 400 / 230kv Sub-Station Shoolagiri.

An Accelerated Distance Protection Scheme for the Lines Connected to Inverter-Based Resources

Distance relay based pilot protection schemes are commonly employed in industrial relays to provide fast tripping of the faulty transmission lines. However, the probable communication link failure or interruption can make these schemes ineffective. Therefore, some non-pilot methods are addressed in the technical literature which cannot offer an appropriate performance in the presence of inverter-based resources (IBRs) owing to the unconventional fault behavior of IBRs as compared with that of synchronous generators. Thus, an analytical non-pilot method is established for the accelerated tripping (AT) of the second zone of distance relay in the presence of IBRs. At the first place with the proposed method, the faulted phase is identified through a fault classification scheme. Within the second phase, using the strength of the variations existing in the negative and zero sequence components of both voltage and current signals, the remote breaker status is realized. Finally, according to the remote breaker status, the AT or delayed tripping decision is decided. Performance of the established methodology is examined for different simulation scenarios, such as different fault locations as well as fault resistances, employing the PSCAD/EMTDC software. The obtained promising results obviously approve the efficiency of the proposed framework.

Adaptive Machine-Learning-Based Transmission Line Fault Detection and Classification Connected to Inverter-Based Generators

Adaptive protection schemes have been developed to address the problem of behavior-changing power systems integrated with inverter-based generation (IBG). This paper proposes a machine-learning-based fault detection and classification technique using a setting-group-based adaptation approach. Multigroup settings were designed depending on the types of power generation (synchronous generator, PV plant, and type-3 wind farm) connected to a transmission line in the 39-Bus New England System. For each system topology, an optimized pretrained ensemble tree classifier was used. The adaptation process has two phases: an offline learning phase to tune the classifiers and select the optimum subset of features, and an online phase where the circuit breaker (CB) status and the active output power of the generators are continuously monitored to identify the current system topology and to select the appropriate setting group. The proposed system achieved an average accuracy of 99.4%, a 99.5% average precision, a 99.9% average specificity, and a 99.4% average sensitivity of classification. The robustness analysis was conducted by applying several fault scenarios not considered during training, which include different transmission network configurations and different penetration levels of IBGs. The case of incorrect selection of the appropriate setting group resulting from selecting the wrong topology is also considered. It was noticed that the performance of developed classifiers deteriorates when the transmission network is reconfigured and the incorrect setting group is selected.

Grid behavior: PMU-enabled dynamic state estimation [Editors’ Voice

The notion of the state of health is widely used in asset management. For instance, electric vehicle batteries are replaced after they lose ∼30% capacity, which means that their state of health is not good enough for reliable use in day-to-day travels, even though they still possess 70% capacity. Estimating the state of health of an asset is difficult, and for a power grid spanning thousands of kilometers and interconnecting millions of components, it is barely imaginable. We use familiar biomedical tests, such as blood tests, to grasp quantitative information about the health of a person, which is then interpreted by a doctor. A similar measurement-based approach is adopted in power grid operations. Electronic devices located in substations acquire and process current and voltage signals, breaker status, meteorological data, etc., which are sent to control rooms for digestion and interpretation by power system operators.

Soft Open Points-Assisted Resilience Enhancement of Power Distribution Networks Against Cyber Risks

Cyberattacks are increasingly threatening the normal operation of electric power grids. The purpose of this study is to develop an optimization model for planning and operation of distribution systems to enhance the resilience to cyberattacks. A new distribution system planning method is presented utilizing a Defender-Attacker-Defender (DAD) tri-level model to improve the system resilience to withstand potential disruptions from cyberattacks. In the first level of the model, the system planner optimizes the Soft Open Points (SOPs) installation in the planning stage. The attacker’s objective in the second level of the model is to change the status of the network circuit breakers and jam the communication maximizing disruption of the system. The optimization of Distribution Generators’ (DGs’) outputs, SOPs’ power flow, and topology reconfiguration are comprehensively considered in the third level. The novel model presented in this paper considers hardening measures of the SOPs in response to the attacks on distribution systems. The Column and Constraint Generation (C&CG) algorithm is utilized to solve the proposed DAD model. A procedure is devised to solve the two-layer subproblem (the Attacker-Defender model), with the bottom layer being a Mixed Integer Second Order Cone Programming (MISOCP) problem. Finally, the proposed models are validated in 33-bus and 135-bus test systems. The results show that the installation of SOPs significantly improves the service restoration under cyberattacks. Both the number and location of SOPs influence the extent of restored service, and differing SOP allocation schemes may lead to similar restoration outcomes. The proposed models and techniques could also be extended to deal with other similar problems in industrial cyber-physical systems.

Application of High-voltage Circuit Breaker Status Evaluation Method Based on Primary and Secondary Integrated Switch Detection Platform

This paper proposes a high-voltage circuit breakers status evaluation method based on the primary and secondary integrated switch detection platform to cope with the poor effect of existing evaluation methods. A high-voltage circuit breaker status evaluation index system was determined in combination with the actual situation of high-voltage circuit breakers. The subjective weight of the status of the high-voltage circuit breaker was determined with the analytic hierarchy process, the objective weight of the status of the high-voltage circuit breaker was calculated by the entropy method, and the analog acquisition accuracy of the high-voltage circuit breaker was improved with the amplification circuit design of the genetic algorithm. After the weight was determined, the overall weighted evaluation was performed, and the status of the high-voltage circuit breaker was evaluated through primary and secondary integration. Through comparative experiments, it can be seen that the results of the weight proportion test on the high-voltage circuit breaker status evaluation based on the primary and secondary integration are greater than that of the traditional high-voltage circuit breaker status evaluation method. Therefore, the designed evaluation method based on the primary and secondary integration can be better applied to the distribution network and protect the circuit.

An Adaptive Overcurrent Coordination Scheme Withstanding Active Network Operations

This paper aims to present a centralized adaptive protection scheme (APS) for the directional overcurrent relays (DOCRs) considering system dynamics such as load demand variations, topology changes and DGs to mitigate the above-mentioned effects. The scheme is suitable for different types of networks whether its radial or meshed. Afterall, it can determine the actual topology with the micro-PMUs and breaker status, automatically generate relay names accordingly with the topology bus locations, establish protection coordination pairs, coordinate DOCRs for parallel lines, identify transformers to offer backup operation for differential protection, perform load flow and fault studies, execute contingency and sensitivity analysis, and lastly, coordinate the DOCRs using differential evolution algorithm so that they always have the proper settings to operate in appropriate time providing selectivity. The performance of the proposed centralized adaptive overcurrent protection scheme is tested on the highly meshed IEEE 14 bus system. The proposed scheme has shown that it can adequately consider impacts of system dynamics and DG.

Hardware Design of Online Monitoring Device for the High-voltage Vacuum Circuit Breaker

In order to monitor the mechanical structure status of high-voltage vacuum circuit breakers in real time and diagnose faults online, a hardware design scheme of an online monitoring device for 10kV vacuum circuit breakers is proposed in this paper. From the perspective of practical application, this design scheme fully considers the practical working conditions of the monitoring device. The device not only monitors the mechanical vibration of the circuit breaker, the rotation stroke of the spindle and the position signal of the mechanical switch, but also monitors both the voltage and current of the opening (closing) coil, the energy storage motor and the closing lock coil. In this paper, in order to adapt the monitoring device to the actual application conditions, a modular design is adopted, the isolation and protection performance of the ports is strengthened and the integration degree of the device is increased.

Concise Silicon Carbide DC Circuit Breaker Module for Satellite Electrical Systems

Fault protection and real-time monitoring of Satellite Electrical Power Systems (SEPS) are of importance for the advancement of modern satellite systems of high power, compact sizing and long lifespan. Conventional protection methods could handle the overcurrent faults but lack flexibility in fault clearance time. With these important considerations, a compact and programable Silicon Carbide (SiC) power MOSFET based DC circuit breaker module is developed to not only handle multiple levels of overcurrent faults with suitable time-delay protection scheme, but also provide the real-time monitoring of circuit breaker status by using the Long Range (LoRa) and Internet of Things (IoT) Technology. The proposed module has been implemented and its effectiveness was tested and confirmed in laboratory under various overcurrent fault conditions.

Application of State Estimation in Distribution Systems with Embedded Microgrids

In this paper, a weighted least square (WLS) state estimation algorithm with equality constraints is proposed for smart distribution networks embedded with microgrids. Since only a limited number of real-time measurements are available at the primary or secondary substations and distributed generation sites, load estimates at unmeasured buses remote from the substations are needed to execute state estimation. The load information can be obtained by forecasted and historical data or smart real-time meters. The proposed algorithms can be applied in either grid-connected or islanded operation mode and can efficiently identify breaker status errors at the main substations and feeders, where sufficient measurement redundancy exists. The impact of the accuracy of real and pseudo-measurements on the estimated bus voltages is tested with a 55-bus distribution network including distributed generation.

Fuzzy Theory Based Quality Assessment of Multivariate Electrical Measurements of Smart Grids

Electrical measurements of smart grids form the backbone of various data driven applications. Proper analysis of these measurements can result in improved system planning, operation, monitoring and protection. However, the efficacy of smart grid data mining is highly influenced by the quality of the data. Hence, quality assessment of smart grid data is essential prior to the usage of the data in various applications. A fuzzy assessment method is proposed in this paper for assessing quality of multivariate electrical measurements of smart grids. At first, relevant quality dimensions of smart grid data are identified. Then, based on certain desirable characteristics, novel membership functions are proposed for assessing the data quality with respect to each of the considered dimensions. The proposed membership functions are evaluated on the current and real power measurements obtained from the power flow analysis of the IEEE 14-bus system. In addition, the proposed method is also implemented on the voltage, current and the real power measurements obtained from the power flow analysis of an actual 34 node feeder located in Arizona. The impact of measurement noise is also investigated by polluting the original measurements with Gaussian noise. It is found that the quality of the noisy measurements worsens with the increase in variance of the added noise. The proposed method has also been validated on a database containing practical SCADA and PMU measurements of the Southern Regional Grid of India. It is found that the PMU datasets are relatively incomplete compared to the SCADA datasets. In addition, the obtained results indicate that PMU data are suitable for use in more number of applications compared to the SCADA datasets. Unlike the existing methods, the proposed method can be used for quantifying the quality of any smart grid dataset that contains electrical measurements of multiple power system variables including boolean variables such as circuit breaker status. Moreover, unlike the existing methods, the proposed method can measure the consistency among the measurements. In addition, the proposed method is found to be sensitive to the distribution of the bad measurements in a given database.

An Adaptive Protection for Radial AC Microgrid Using IEC 61850 Communication Standard: Algorithm Proposal Using Offline Simulations

The IEC 61850 communication standard is getting popular for application in electric power substation automation. This paper focuses on the potential application of the IEC 61850 generic object-oriented substation event (GOOSE) protocol in the AC microgrid for adaptive protection. The focus of the paper is to utilize the existing low-voltage ride through characteristic of distributed generators (DGs) with a reactive power supply during faults and communication between intelligent electronic devices (IEDs) at different locations for adaptive overcurrent protection. The adaptive overcurrent IEDs detect the faults with two different preplanned settings groups: lower settings for the islanded mode and higher settings for the grid-connected mode considering limited fault contributions from the converter-based DGs. Setting groups are changed to lower values quickly using the circuit breaker status signal (XCBR) after loss-of-mains, loss-of-DG or islanding is detected. The methods of fault detection and isolation for two different kinds of communication-based IEDs (adaptive/nonadaptive) are explained for three-phase faults at two different locations. The communication-based IEDs take decisions in a decentralized manner, using information about the circuit breaker status, fault detection and current magnitude comparison signals obtained from other IEDs. However, the developed algorithm can also be implemented with the centralized system. An adaptive overcurrent protection algorithm was evaluated with PSCAD (Power Systems Computer Aided Design) simulations, and results were found to be effective for the considered fault cases.

An Adaptive Protection Technique for Smart Distribution Network

The future distribution networks (DNs), commonly known as the smart grid is expected to be reliable, efficient, and can accommodate renewable energy resources. The smart distribution network has to withstand the technical challenges related to the integration of distributed generations (DGs). Among these technical challenges, protection malfunctioning with the increased integration of DGs is one of the important issues, which requires a great concern. Thus, a protection philosophy, which can suit the future smart grid requirements with respect to increased integration of DGs, has to be devised. In this paper, an adaptive protection technique, which is based on the characteristics of fault-current and load-current variation, is proposed. In the proposed method, intelligent electronic devices (IEDs) monitor the status of circuit breakers (CBs) and DGs. If any status change occurs, the calculation and relay agents are triggered to update the IEDs. DigSILENT PowerFactory is used to verify the suggested philosophy. Especially DigSILENT Programming Language (DPL) is used to model the adaptive protection. The solar power plant in the Antalya vicinity in Turkey is used to verify the proposed method. The results of the simulation study show the correct operation and effectiveness of the proposed method.

A New Intelligent Method for Parallel Transmission Lines Protection

In many countries, the parallel lines are widely used in transmission systems due to economic and technical benefits. Distance relays have poor performance on the protection of parallel transmission lines because of the mutual coupling effect. The distance relay may underreach when both lines are in-service. On the other hand the over reach problem may arise when only one line is in-service and another line is disconnected and grounded at both sides. Therefore, a new intelligent method is presented to protect parallel lines comprehensively in different operating modes. In the first stage, considering the status of circuit breakers as well as measured current signals at both sides of parallel lines, the fault types are identified by allocating a probabilistic neural network (PNN). Then, in the second stage, the fault location is estimated by assigning an artificial neural network (ANN) to each type of fault. The results obtained from the simulation of a part of the power system including 230-kV parallel lines, show that the proposed method can accurately detect all fault types and also it can precisely locate the fault points with an accuracy of 98.8%.

An enhanced ground fault selection and distance measurement approach for single and double circuit fixed series compensated transmission line

This work demonstrates a superior local measurement-based ground fault selection and distance computation approach for a single and double circuit series compensated transmission lines. The proposed design was constructed to defeat the weaknesses of the usual protection approaches as influencing of mutual coupling, series capacitor, long outage time, one line operation mode, necessitating of synchronization, the unbalance load switching, the CT saturation, needing to know the status of circuit breakers, and the difficult fault initial condition as weak inception time, fault resistance loop, remote locations, and nearby locations. In this research, the decision data is exported from zero-sequence impedance relaying signals and positive sequence voltage relaying signal based imaginative Cos-Sin concept. To approve the suggested approach, widespread faults were simulated in the ATP program as well as the suggested approach is made in MATLAB program. The outcomes show that the proposed method is correct and overcomes the aforementioned weaknesses and difficulties.

High-Voltage Circuit Breakers Technical State Patterns Recognition Based on Machine Learning Methods

This paper is devoted to improving the assessment of the technical state (health index) of power circuit breakers through the use of machine learning, which allows to formalize expert knowledge, to identify implicit correlations and dependencies, and to automate the decision-making process under uncertainty. The paper proves the possibility of using machine learning based on decision trees to solve the task of assessing the power circuit breakers technical state and solves the problem of determining its optimal parameters and the training sample. The authors of the study carried out approbation of the developed model for assessing the technical state of breakers based on analyzing a large area of electrical networks in the Sverdlovsk Region, the Russian Federation, which proved its efficiency. The necessity of taking into account short-circuit currents when recognizing the pattern of the power breakers technical state is substantiated.