Relay Protection Research Articles

A review of potential fault detection methods for traditional collector stations and sensor fault diagnosis in wind farm doubly-fed generator converters

Collector stations sometimes face situations where existing relay protection systems may fail, making potential fault monitoring technology increasingly important. This technology plays a critical role in ensuring the stability of power supply and enhancing economic benefits. Simultaneously, in response to the nation's "dual carbon goals," the construction and operation of large-scale renewable energy power stations are booming. Therefore, potential fault monitoring technology for new power stations should not be overlooked. For traditional power stations, the application and development trends of infrared thermal imaging technology, vibration analysis and acoustic detection technology, chemical analysis, and oil quality detection technology will be compared and discussed. Regarding new power stations, methods for diagnosing sensor faults in doubly-fed generator converters in wind power will be analyzed and discussed.

Effect of DG penetration on hybrid relay coordination using user-defined dual-setting directional overcurrent relays and distance relays

ABSTRACT The efficient coordination of the distance and directional overcurrent relays (DOCRs) is jeopardized by the massive deployment of renewable distributed generation (DG) into electrical power networks. The two key aspects influencing the relay coordination are the bidirectional flow of current and increased short-circuit currents due to DG integration. This study investigates the consequences of variable DG penetration on the distance and dual-setting DOCRs (DS-DOCRs) coordination. As a result, common optimal relay settings have been obtained that can be utilized for variable DG penetration levels in modified IEEE-14 bus test system. For the distance relays (DRs), a fixed zone 1 and variable zone 2 operation have been considered. The proposed combined protection scheme is tested on a modified IEEE-14 bus test system using DS-DOCRs and DRs. The relay coordination problem is formulated as a constrained non-linear optimization problem and solved by genetic algorithm (GA) and gray wolf optimization (GWO). In this paper, DS-DOCRs with user-defined relay characteristics have demonstrated superior performance in line protection compared to conventional DOCRs with normal inverse (NI) characteristics. In addition, a comprehensive comparative analysis of optimization algorithms has been performed between GA and GWO algorithms.

Research on the Construction of Power System Relay Protection Course System in Electrical Engineering Discipline

Power system relay protection is one of the core courses in the discipline of electrical engineering, which is directly related to the students' professional ability in the field of power system operation and protection. With the rapid development of power system, especially the popularization of smart grid technology, the existing curriculum system gradually exposes problems such as obsolete content, insufficient practical teaching, and disconnection with cutting-edge technology. By analyzing the current situation of the existing curriculum system, this paper proposes key elements such as the combination of theory and practice, the introduction of cutting-edge knowledge, the optimal allocation of teaching resources, and the innovation of teaching methods, and discusses the implementation strategy of curriculum system reform. The study aims to build a relay protection curriculum system that better meets the development needs of modern power systems, and to enhance students' practical ability and innovative thinking to meet the challenges of the future power industry.

Optimal coordination of directional overcurrent relays in power energy systems with emphasis on the discreteness of variables: Comprehensive comparisons

The challenge related to the coordination of overcurrent relays in a looped network, which is a highly constrained problem, is to find a more optimum solution and at the same time there is no miscoordination. In this problem, the utilized optimization algorithm has a direct effect on finding a more optimal solution. High exploration particle swarm optimization (HEPSO) algorithm, which utilizes multi-crossover mechanism of the genetic algorithm and the bee colony mechanism to increase the exploration capability, has been selected to solve the coordination problem. To validate the HEPSO algorithm, a new algorithm called turbulent flow of water-based optimization (TFWO) is also used, and their results are compared. A new approach to discretization of variables is presented, which prevents miscoordination in the relays coordination. It is a realistic assumption for all relay types, especially digital relays, in preventing miscoordination. Also, the outage of sub-transmission transformers is considered for determining pickup current, which is a practical aspect of power systems operation. The obtained results are compared with the results of other algorithms and methods such as metaheuristic, mathematical and analytical, and hybrid methods. The efficiency of the selected algorithm is proven through comprehensive comparisons. The results show more optimum solutions while there is no miscoordination. Finally, the performance of the selected algorithm and the proposed approaches are tested on IEEE 14 and 30-bus test systems. Since these test systems are large enough, the number of problem variables will increase significantly, effectively validating the power and robustness of the selected algorithm to tackle this complex and constrained problem. The outage of transformers in determining pickup currents had been implemented in this section.

Enhancing Grid Resiliency in High Fire or Flood Risk Areas: Integrating Protective Relay Settings, Broken Conductor Detection, and Grid Hardening for Climate-Induced Event Preparedness

Enhancing Grid Resiliency in High Fire or Flood Risk Areas: Integrating Protective Relay Settings, Broken Conductor Detection, and Grid Hardening for Climate-Induced Event Preparedness

Optimal over-current relay coordination in distribution network using grew wolf optimization

Optimal over-current relay coordination in distribution network using grew wolf optimization

Restoration of the current transformer secondary current under core saturation conditions based on ANN

Relay protection and emergency automation is an integral part of electric power systems. The algorithms of the relay protection and emergency automation are based on the use of analysis of the parameters of the electrical mode - current and voltage - obtained from current and voltage instrument transformers. As a rule, these transformers operate on the basis of the laws of electromagnetism. Operational experience shows that the magnetic core of current transformers under fault conditions can be saturated. As a result, the shape of the measured current is distorted which can lead to false operation of the relay protection and emergency automation system. In this paper a comparative analysis of the existing methods is presented. The advantages and disadvantages of them are described. The problem of current transformer core saturation is reduced to a regression problem. To solve the problem an artificial neural networks-based method is proposed. Computational experiments for both proposed and existing methods are performed. The results of experiments show that the efficiency of the proposed method is 1.25 times higher relative to the most effective existing method. The method of re-scaling data at real-time work applied to the restoration of the distorted shape of current is proposed.

An Energy Efficient Transmission Mechanism based on Optimal Relay Distance for Underwater Acoustic Sensor Networks

Abstract Due to the limited resources and energy of communication in underwater acoustic sensor network (UASN), there are many challenges in designing energy-efficient and reliable media access control (MAC) protocols for UASN. This paper proposes an energy-efficient media access control (MAC) protocol with dynamic transmission range control (TRC), referred to as TRA-MAC. The protocol provides an adaptive, multi-hop and energy-saving solution for underwater sensor network communication. The protocol dynamically adjusts the transmission power of the node according to the distance between the source node and the destination node, and has the ability to adapt to network conditions. Simulation results show that compared with Slotted Aloha, the proposed adaptive relay node selection mechanism increases the energy efficiency by 43.07%, the network throughput by 46.6%, and the end-to-end delay is greatly reduced. Compared with Slotted FAMA, it has more significant advantages.

Метод обработки сигналов токов статора асинхронного двигателя для диагностики обрыва стержня ротора

The study is relevant due to high requirements to the reliability of the operation of auxiliary mechanisms of thermal power plants (TPP). The main source of mechanical power of auxiliary mechanisms of TPPs is high-voltage induction motor with squirrel cage rotor (IMSC). One of the most difficult causes of emergency shutdown to detect early is a broken rotor bar. The breakage of IMSC rotor bar is of latent character. It can be for a long time without considerable influence on the machine operation mode. Nevertheless, the fact of the breakage can be considered as an emergency condition of IMSC, and the consequences of leaving the groove of the magnetic core are irreversible. Scientifically, early diagnostics of IMSC rotor bars breakage of TPP auxiliary needs is both a difficult and extremely urgent task. The existing methods of diagnostics of such damage are based on measurement and analysis of vibration and acoustic physical quantities. The most common electrical parameter, used as a source of information, as a rule, is current consumption. And most of methods are based on Fourier analysis. The purpose of the study is to develop a mathematical algorithm to process digitized curves of stator phase currents to diagnose high-voltage IMSC. The theory of electric machines, the method of analytical approximation of experimental data, the method of regression analysis have been used to solve the problem. Experimental data is obtained, and testing of the algorithm is conducted on an experimental installation with a 0,4 kV induction motor with a modified design of the active part of the rotor developed for physical simulation of IMSC broken rotor bar. This paper proposes a new method of digital processing of stator current signals based on the regression analysis method for diagnostics of IMSC rotor winding. The authors have developed an algorithm for mathematical processing of digitized stator current curves based on regression analysis in the cosine-sine basis to identify the diagnostic sign of failure of one rotor bar of IMSC rotor. The authors have determined the number of harmonic components that best describe the initial signal from the point of view of the balance between saving computational resources and accuracy of approximation. A mathematical algorithm to detect the rotor bar breakage of an induction motor based on regression analysis of stator currents has been obtained and tested. It allows to detect rotor circuit damage with 97 % accuracy. At the same time the diagnostic sign changes its level when one bar breaks by 5 %. It is recommended to adapt the algorithm to the programming languages of microprocessor relay protection units.

Определение факта насыщения магнитопровода трансформатора тока на основе непрерывного измерения сопротивления цепи намагничивания

Saturation of electromagnetic current transformers in transient modes of operation of an electric power system can lead to incorrect operation of relay protection devices. One of the most promising directions to improve the stability of the operation of relay protection devices in such modes is digital correction of secondary current. Currently, effective methods have been developed to restore the secondary current based on determination of magnetic circuit saturation. However, the practical application of these methods is impossible due to the imperfection of existing methods of secondary current segmentation. Thus, it is urgent to develop a method to determine saturation for implementation of digital correction algorithms for electromagnetic current transformers. To solve the stated problem, methods of mathematical modeling of electrical circuits containing transformers and the small-disturbance theory have been used. Verification of the research results is carried out in the Matlab software package. A mathematical criterion is formulated to determine the saturation of the magnetic circuit of an electromagnetic current transformer based on the inductance of the magnetization circuit. A method of segmentation of the secondary current has been developed for the implementation of digital correction algorithms based on the proposed criterion. The effectiveness of the developed method to determine the saturation of the magnetic circuit of an electromagnetic current transformer using computational experiments in the Matlab software package is demonstrated. It is planned to verify the developed method using a physical model of an electromagnetic current transformer.

Development of a fuzzy logic-based model for assessing the reliability of relay protection systems

This article presents a reliability assessment model for relay protection devices using fuzzy logic. It introduces an algorithm for simulating these devices, employing the Mamdani model with an "if-then" rule base. Inputs include the percentage of correct operation and the frequency of correct and incorrect operations. Implemented in Matlab with 21 rules, the fuzzy logic model uses triangular membership functions for input and output variables, with defuzzification via the center of gravity method. The model was tested using statistical data from SIEMENS SIPROTEC terminals, specifically distance protection and differential protection devices for transformers and autotransformers. The assessment considers operation frequencies for 1 to 3 devices, combining statistical and simulation data for a comprehensive analysis. Results show that including operation frequencies improves evaluation accuracy. The proposed model not only assesses current reliability but also predicts future behavior, aiding in the planning and optimization of relay protection systems. This model is valuable for professionals in generating companies, grid organizations, and operational dispatch control entities, helping them analyze relay protection performance and develop strategies to ensure reliable operation. The research focuses on the reliability of relay protection devices in power systems, addressing the need for a more accurate and comprehensive evaluation method. Traditional methods may not fully account for the complexities in modern microprocessor-based protections. This study aims to enhance reliability assessments through a model that integrates statistical data and simulation techniques, ultimately supporting better planning and optimization of relay protection systems

Positive sequence component based directional relaying for lines integrated with solar photovoltaic plant

Different fault current characteristics of converter interfaced solar photovoltaic plants as compared to the synchronous generator based sources impose challenges to the commonly used directional relaying methods. In this work, the issues with phasor based directional relay algorithms are analysed for the solar plant connected lines. A directional relaying method is proposed for such connectivity using the phase angle difference between positive sequence voltage and the line current measured at the local bus relay. Using PSCAD/EMTDC simulations the proposed method is tested for solar plant connected 39 bus system and validated using field data. The accuracy of the proposed method is also evaluated on a real-time simulation platform. Comparative analysis with the conventional directional relaying methods reveals the superiority of the proposed method.

Innovative protection schemes through hardware-in-the-loop dynamic testing.

In microgrid environments, the behaviour of Distributed Generation (DG) during fault conditions varies significantly based on DG types and penetration levels. Conventional Overcurrent Relays (OCRs) with standard time-current characteristics may exhibit limitations during excessive fault scenarios, leading to OCR operating delays and mis-coordination within the microgrid. This study proposes a novel constraint on the maximum Current Multiplier Setting (CMS) and utilizes Water Cycle Algorithm (WCA) and Particle Swarm Optimization (PSO) techniques to optimize the Time Multiplier Setting (TMS). Comparative dynamic analysis through real-time validation shows that the non-standard OCR approach outperforms the standard IEC scheme across all grid operation modes with different type, size and location of DGs. For instance, under F1 conditions, the tripping time of OCR1 was reduced from 0.0226 seconds (IEC) to 0.000981 seconds (non-standard). HIL results further affirm the efficacy of the proposed scheme. The optimization process, implemented in MATLAB and validated using ATP/EMTP simulations and SIPROTEC 7SJ62 relays, demonstrates enhanced microgrid protection coordination, improving system reliability and performance.

Highly sensitive protection scheme considering the PV operation control models

The integration of distributed generation (DG) based on inverters into power systems has increased significantly, necessitating a thorough understanding of its impact on fault analysis and the performance of distribution networks' protection mechanisms. This study addresses this issue by examining how various inverter management modes influence protective relay systems within IEEE 9-bus redial and mesh networks, CIGRE and IEEE 33-bus networks featuring Photovoltaic (PV) farms and Battery Energy Storage Systems (BESS), by IEEE1547–2018 and German grid code standards. By analyzing grid-connected scenarios with five distinct PV control modes, the research introduces a novel protection methodology termed the Photovoltaic Overcurrent Relay (PVOCR). This method introduces a current-voltage characteristic to optimally coordinate Overcurrent Relays (OCRs), aiming to reduce their operational time and eliminate mis-coordination events. The proposed PVOCR is evaluated against standard inverse time, SOCR, and modern adaptive voltage, VOCR, relay schemes across various fault scenarios differing in type and location. Furthermore, the PVOCR scheme effectively operates across all PV inverter modes without experiencing miscoordination events, whereas the SOCR and VOCR schemes encountered such issues during the operation of Control 4. These results underscore the potential utility of the PVOCR methodology in enhancing the reliability and efficiency of protection systems in inverter-based DG networks.

A new and effective directional overcurrent relay coordination approach for IIDG-based distribution networks using different setting groups for peak and off-peak demand periods

Directional overcurrent relays (DOCRs) must be properly coordinated to avoid vulnerabilities in the protection of distribution systems. Although most researchers have focused on changes in fault currents caused by distributed generation units (DGs), changes in load currents are also important. Due to the stochastic nature of load demand and output power of renewable-based DGs, load current magnitudes can change significantly and reach high values throughout the day. Therefore, to avoid maloperation, high pickup current settings for DOCRs must be selected. However, at this time, protection coordination may become ineffective. This paper proposes a novel DOCR coordination strategy for inverter-interfaced DG (IIDG)-based distribution systems by assigning different setting groups to each DOCR for the peak and off-peak loading periods of the day and using a realistic approach to determine maximum load currents. The aim is to achieve high effectiveness in DOCR coordination by lowering selectable pickup settings. To obtain the optimal setting groups, a new variant of the white shark optimizer is developed and used. The proposed approach reduces the total operating time of relay pairs by up to 24.5 % and 21.5 % for the IEEE 14-bus and IEEE 30-bus distribution systems, respectively, compared to the traditional coordination approach.

Dynamic mater-slave control strategy for transient coordination of inverter based microgrids under asymmetric faults

The ever-expanding inverter-based microgrids (MGs) require the grid-forming distributed renewable energy resources (DERs) to enhance the system safety. However, the different types of grid-forming DERs are prone to have transient conflicts with each other under short circuit faults, leading to unexpected outage or even system collapse. The fast response and poor overcurrent capability of DERs make transient coordination a challenge. This paper proposes a dynamic master–slave architecture for transient coordination control in islanded MGs under asymmetric faults. A dynamic reconfigurable voltage reference unit (DVRU) is designed according to the real faults. In this manner, the other DERs could comply with this DVRU to achieve both system voltage support, inrush current restraining, and power oscillation suppression. It is action signals instead of phase signals need to be transferred by the communication bus with the proposed local fault current differential time delay method (FCDDM). Thus, the low-bandwidth and the enhanced robust communication could be met under transient state. Additionally, the feasibility of the proposed method to combined with relay protection is analyzed. Finally, case study results on islanded MGs consisting of various grid-forming and grid-following DERs demonstrate the effectiveness and robustness of the proposed method under short circuit faults as well as communication failures.

DEVELOPMENT AND APPLICATION OF A WEARABLE TECHNOLOGY PRODUCT THAT DETECTS AND INFORMS THE PRESENCE OF ELECTRICAL ENERGY

Electrical energy has both positive and negative effects nowadays, with the potential to cause property and human loss. Technical professionals working at electrical energy generation, distribution, and utilization points may die due to carelessness or neglect. Although there are protection elements (fuses, residual current protection relays, etc.) in electrical panels that interrupt the flow of electrical energy in the event of a shock, there may be working areas where energy cannot be cut off due to incorrect electrical connections caused by unauthorized people interacting with the panel. Existing protective components may be insufficient. The experiments include both wired protection elements and wireless detection elements. However, they need to be enhanced because they have limited detection distances. Furthermore, using an ergonomic design can improve operability. New protection and warning features must be designed using developing technology. To prevent employees from being shocked by being exposed to electrical energy in the workplace, AC voltage can be detected without contact using this study, which includes the design and test results of a wearable technology product that warns when electricity is present. An electrical circuit that technical staff can wear on their finger detects voltage without contact and displays the existence of energy with a red LED. It was discovered that the test circuit detects 230V AC electrical energy up to 8 cm away and warns with light.

Pilot protection based on the similarity of the traveling waves between the quadratic fitting curve and the calculated curve for the All-DC wind power transmission system

The All-DC wind power generation system can effectively solve the harmonic resonance problem caused by large-scale wind power AC collection and transmission, gradually becoming a hot topic in future research. However, there are few studies on the relay protection of the All-DC wind power transmission systems. In the All-DC wind power systems, there are differences in topology, control strategies, fault characteristics, boundary characteristics, etc. At the same time, existing pilot protection has problems such as strict information synchronization requirements and selection of setting values through simulation. Therefore, the proposed pilot protection based on the similarity of the traveling wave between the quadratic fitting curve and the calculated curve for the All-DC wind power system transmission lines. Firstly, the difference of the 1-mode initial current waveform characteristics is analyzed in the time domain at both ends. Then, the least squares method is introduced to fit the differential curves of the current forward and backward traveling waves at two terminals. The differential characteristics of the differences between the fitted curve, the calculated curve, and the measured curve under the influence of internal and external errors are analyzed. Finally, the calculated value of traveling wave current during external metallicity fault is used as the standard. By comparing the fitting curve of current traveling waves and the difference in the calculation curve to distinguish internal faults from external faults. The simulation results show that the proposed protection principle can fault resistance of 2200 Ω and noise interference of 20 dB. In addition, the proposed method does not require strict data synchronization, higher sampling frequency, and setting value through simulation.

Neural Network-Based Aggregated Equivalent Modeling of Distributed Photovoltaic External Characteristics of Faults

Distributed power networks have a large number of photovoltaic power sources. The bidirection of power flow, different transient control strategies, and installation locations make the transient characteristics highly complex and unpredictable. The vast network of the distribution system makes it almost impossible to predict the electrical quantities of each branch. Reasonable aggregation modeling of the distribution network can greatly simplify the network topology, facilitating transient control and the setting of relay protection settings. An aggregated equivalent modeling method based on the LSTM neural network for distributed PV fault external characteristics is proposed. This method equates the complex distribution network to a highly nonlinear but controllable current source. The method can output the I–V curves of equivalent PV system parallel points under any output power and is able to predict the fault characteristics of the equivalent system after a voltage drop at the parallel point. Compared to traditional mechanistic modeling, this method does not require specific modeling of complex physical systems and is able to accurately map the strong nonlinear inputs and outputs of distribution networks. The established LSTM model first uses a one-dimensional convolutional layer for feature extraction of the PV power coefficients (input), and then two hidden layers are utilized to process the sequence data; the vectors are mapped into a sequence of external characteristic curves (output) in a fully connected layer. A typical distribution network is built based on the traditional PV power model, and a large number of different output combinations are selected for simulation to provide an effective training set and validation set data for LSTM model training. By using the training set data, the weights and offset coefficients of each layer of the LSTM are continuously optimized until the model with the smallest overall error is obtained, which is the optimal model. Finally, the optimal model is utilized to establish an equivalent distribution network system, different degrees of voltage drops are set up at the grid-connected points, the fault characteristics are compared with those of the complete model, and the simulation results can prove the reliability and practicality of the proposed method.

Energy efficient clustering and routing protocol based on quantum particle swarm optimization and fuzzy logic for wireless sensor networks

Clustering and routing protocols play a pivotal role in reducing energy consumption and extending the lifespan of wireless sensor networks. However, optimizing energy efficiency to maximize network longevity remains a primary challenge for these protocols. This paper introduces QPSOFL, a clustering and routing protocol that integrates quantum particle swarm optimization and a fuzzy logic system to enhance energy efficiency and prolong network lifespan. QPSOFL employs an enhanced quantum particle swarm optimization algorithm to select optimal cluster heads, utilizing Sobol sequences for population diversification during initialization. Additionally, it incorporates Lévy flight and Gaussian perturbation-based position updates to prevent trapping in local optima. Benchmark experiments validate QPSOFL's efficacy compared to Harris Hawks Optimization (HHO), Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Quantum Particle Swarm Optimization (QPSO), focusing on accuracy, search capability, and convergence speed. Within QPSOFL, a fuzzy logic system determines the best next-hop cluster head based on descriptors such as residual energy, energy deviation, and relay distance. Extensive simulations compare QPSOFL's performance in terms of network lifetime, throughput, energy consumption, and scalability against existing protocols E-FUCA, IHHO-F, F-GWO, and FLPSOC, demonstrating its superior performance over these counterparts.