Power System Transmission Line Research Articles

Advancements In Machine Learning Algorithms for Enhanced Fault Analysis and Categorization in Power Systems

With the growing number of sources, complexity, and dynamic elements of power systems that are prone to disturbance and electrical faults, conventional methods of fault detection are lagging in power system protection. Major faults are exposed to transmission lines due to several factors, such as climate change, heat, lightning strokes, sudden spikes of current and voltage etc. Protecting these lines from faults is cumbersome using traditional methods. However, with the increasing complexity of transmission lines in power systems, advanced technologies such as machine learning come into play for prior fault detection and identification. ML is becoming a popular and intelligent technique for monitoring and predicting health and diagnosing faults in transmission lines of power systems. Since ML is evolving at a faster pace and given the need for and growth of advanced technologies like ML and artificial intelligence, this paper emphasizes comparative analysis of various ML algorithms for transmission line fault analysis. Comparisons for various line faults (LL, LLG, LG, LLL, LLLG, no fault) in power systems using machine learning techniques have been done in terms of accuracy, precision, and other performance measures. The results of the accuracy of various algorithms are represented as tabulated facts in this paper. The Python programming language has been utilized over a dataset to calculate results. For each algorithm, the confusion matrix shows the accuracy of predicting faults over the testing data after training the model or algorithm on the training data. Upon completion of analysis and comparison of MLT's like LR, SVM, DT, RF, K-NN, and gradient descent for analysis of transmission line fault detection, RF and DT machine learning algorithms provided the best accuracy and results. Finally, this paper gives a brief overview of various line faults, ML algorithms accuracy for each transmission fault in a confusion matrix and tabular format and concluded the best machine learning algorithms for power system transmission line fault identification.

Optimizing Insulator Defect Detection with Improved DETR Models

With the increasing demand for electricity, the power grid is undergoing significant advancements. Insulators, which serve as protective devices for transmission lines in outdoor high-altitude power systems, are widely employed. However, the detection of defects in insulators captured under challenging conditions, such as rain, snow, fog, sunlight, and fast-moving drones during long-distance photography, remains a major challenge. To address this issue and improve the accuracy of defect detection, this paper presents a novel approach: the Multi-Scale Insulator Defect Detection Approach using Detection Transformer (DETR). In this study, we propose a multi-scale backbone network that effectively captures the features of small objects, enhancing the detection performance. Additionally, we introduce a self-attention upsampling (SAU) module to replace the conventional attention module, enhancing contextual information extraction and facilitating the detection of small objects. Furthermore, we introduce the insulator defect (IDIoU) loss, which mitigates the instability in the matching process caused by small defects. Extensive experiments were conducted on an insulator defect dataset to evaluate the performance of our proposed method. The results demonstrate that our approach achieves outstanding performance, particularly in detecting small defects. Compared to existing methods, our approach exhibits a remarkable 7.47% increase in the average precision, emphasizing its efficacy in insulator defect detection. The proposed method not only enhances the accuracy of defect detection, which is crucial for maintaining the reliability and safety of power transmission systems but also has broader implications for the maintenance and inspection of high-voltage power infrastructure.

Preventive-Security-Constrained Optimal Power Flow Model Considering IPFC Control Modes

The interline power flow controller (IPFC) is one of the most versatile integrated flexible alternating current transmission systems (FACTS) controllers and can realize power flow control for multiple transmission lines in modern power systems. However, control characteristics are ignored in conventional IPFC models, in which unreasonable assumptions about injected voltages may lead to security problems in realistic operation. Besides, preventive security constraints considering IPFC control modes are not included in optimal power flow (OPF) control of the system with IPFC, squandering IPFC control potential. To solve these problems, a preventive-security-constrained optimal power flow (PSCOPF) model considering IPFC control modes is proposed in this paper. IPFC control characteristics under different control modes are analyzed and employed as constraints of the optimization model. The iterative updates of converter output voltages for different control modes are derived respectively for power flow calculation, and the power and voltages required in the objective function and constraints of the proposed model can then be obtained. Through optimal selection of IPFC control modes and control parameters, the proposed model can better reconcile the economical and secure operation of the system. Numerical results demonstrate the efficient performance and superiority of the PSCOPF model considering IPFC control modes.

A Review on Power System Faults and Overcurrent Protection of Distribution Transformer

An electrical fault is the deviation of voltages and currents from nominal values. Power system equipment or transmission lines carry normal voltages and currents which results in smooth operation of the system. But when a fault occurs, it causes very high current to flow through the equipment and can damage the equipment. This paper provides the causes, effects and methods to overcome the faults of power system. Keywords— Power system; Current; Short Circuit; Faults; Power system protection; Equipment; Circuit breaker; Relay

Identification of Vulnerable Transmission Lines in Power System Based on Game Theory

Identification of Vulnerable Transmission Lines in Power System Based on Game Theory

Congestion Management in Deregulated Power System Transmission Line Utilizing Evaporation Rate Water Cycle Optimization Algorithm

Congestion Management in Deregulated Power System Transmission Line Utilizing Evaporation Rate Water Cycle Optimization Algorithm

Simulation calculation of guano fault hazardous areas in overhead transmission lines in power systems

Guano flashover is the most typical type of bird damage fault, which can be divided into two types based on the formation mechanism: guano spatial flashover and guano pollution flashover. These two types of flashover are harmful to almost all levels of transmission lines. For 110 kV level transmission lines, guano flashover faults account for over 90% of all bird damage faults. Among them, guano space flashover has caused tripping faults in multiple foreign ultra-high voltage lines. From this, it can be seen that finding the mechanism of bird manure fault formation and formulating corresponding preventive measures are of great significance for the safe operation of transmission lines.

Search strategy and line association analysis of cascading failure accident chain in new energy power systems

As the penetration rate of new energy in the power system gradually increases and the complexity of cascading faults increases, it is of great significance for the power system to comprehensively explore the chain of cascading faults in the new energy power system and quickly determine the closely related lines in the cascading faults. In response to the lack of consideration in existing research of the changes in the importance of transmission lines after the introduction of new energy, this paper proposes a cascading failure prediction index that integrates the importance and operational status of transmission lines in new energy power systems and applies it to the search for cascading failures in new energy power systems. First, the development characteristics of cascading faults were analyzed, and the main factors influencing cascading faults were identified: the importance of the transmission line and operating status of the new energy power system. Based on these factors, a prediction index for cascading faults was established, and the accident chain was searched using this index. Then, the FP-growth algorithm was used to analyze the lines in the fault chain concentration, and based on the analysis results, the correlation relationship suitable for the cascading failure lines in the new energy power system was determined. Finally, a simulation was conducted on an IEEE 10 machine 39 node system containing new energy wind turbines, and the results verified the effectiveness of the proposed indicators and strategies.

An enhanced sensitive power differential protection for series compensated transmission lines in renewable generation intensive power systems

Series compensation is widely used to improve the electrical characteristics of long transmission lines and increase the power transfer capability. However, the insertion of a series capacitor introduces various phenomena that affect the performance of traditional distance relays. Moreover, the fault characteristics of renewable generation systems coupled with generation outputs that vary with weather patterns produce additional complications to the protection of transmission lines. This paper proposes the application of an enhanced sensitive power differential protection (SPDP) algorithm to the protection of series compensated transmission lines. The algorithm incorporates a criterion that improves the security of the protection by inhibiting the SPDP algorithm from operating for faults external to the protected line. Performance of the enhanced SPDP algorithm has been evaluated on a test system built in Digsilent Powerfactory software. Various in-zone and out-of-zone fault cases were simulated at different compensation levels and fault resistances. The results showed that the enhanced SPDP protection technique can detect in-zone faults along practically the entire transmission line (99.99 %) for compensation levels up to 90 %. The method operated reliably for faults with resistances up to 330 Ω.

Improving of Transmission Cost Allocation Method to Accelerate the Investment Recovery for Transmission lines in Deregulated Power System

Improving of Transmission Cost Allocation Method to Accelerate the Investment Recovery for Transmission lines in Deregulated Power System

Shunt faults detection and classification in electrical power transmission line systems based on artificial neural networks

PurposeThis study aims to focus on an adaptive method for fault detection and classification of fault types that trigger in three-phase transmission lines using artificial neural networks (ANNs). The proposed scheme can detect and classify several types of faults, including line-to-ground, line-to-line, double-line-to-ground, triple-line and triple-line-to-ground faults.Design/methodology/approachThe fundamental components of three-phase current and voltage were used as inputs in the ANNs. An analysis of the impact of variations in the fault resistance, fault type and fault inception time was conducted to evaluate the ANNs performance. The survey compares the performance of the multi-layer perceptron neural network (MLPNN) and Elman recurrent neural network trained with the backpropagation learning technique to improve each of the three phases of the fault detection and classification process. A detailed analysis validates the choice of the ANNs architecture based on the variation in the number of hidden neurons in each step.FindingsThe mean square error, root mean square error, mean absolute error and linear regression are measured to improve the efficiency of the ANN models for both fault detection and classification. The results indicate that the MLPNN can detect and classify faults with a satisfactory performance.Originality/valueThe smart adaptive scheme is fast and accurate for fault detection and classification in a single circuit transmission line when faced with different conditions and can be useful for transmission line protection schemes.

The Use of Instantaneous Overcurrent Relay in Determining the Threshold Current and Voltage for Optimal Fault Protection and Control in Transmission Line

When a fault occurs on the transmission line, the relay should send the faulty signal to the circuit breaker to trip or isolate the line. Timely detection is integral to fault protection and the management of transmission lines in power systems. This paper focuses on using the threshold current and voltage to reduce the time of delay and trip time of the instantaneous overcurrent relay protection for a 330 kV transmission line. The wavelet transforms toolbox from MATLAB and a Simulink model were used to design the model to detect the threshold value and the coordination time for the backup relay to trip if the primary relay did not operate or clear the fault on time. The difference between the proposed model and the model without the threshold value was analysed. The simulated result shows that the trip time of the two relays demonstrates a fast and precise trip time of 60% to 99.87% compared to other techniques used without the threshold values. The proposed model can eliminate the trial-and-error in programming the instantaneous overcurrent relay setting for optimal performance.

New Optical System for Long Distance Control of Electrical Energy Flows

The problems that arise during the transmission of control commands for key elements and data on their execution via communication systems over long distances at energy facilities are considered. The necessity of a new approach to solving this problem using a fiber-optic communication line (FOCL) is substantiated. A new design of analog FOCL has been developed for transmitting control commands for key elements of substations and switching data. A new method for forming an optical signal in a laser transmitting module using direct current modulation is proposed. The advantages of using a new method for generating commands for control signals and switching data using a sequence of command codes compared with digital signals currently used in control and monitoring systems are substantiated. The main parameters of the developed analog FOCL have been calculated. An experimental prototype of an analog FOCL was assembled, and research was conducted. The results of calculations and experimental data are compared. The directions for further modernization of the developed FOCL are determined to increase the distance for transmitting an optical signal up to 600 km without the use of servers, the maintenance of which in the power transmission line system in some cases is challenging, expensive, and not always possible.

Load Frequency Control Using Golden Eagle Optimization for Multi-Area Power System Connected Through AC/HVDC Transmission and Supported With Hybrid Energy Storage Devices

The reliability of a power system depends on its ability to handle fluctuations and varying load demands, as uncontrolled frequency deviations can lead to load-shedding and blackouts. Optimally tuned controllers are essential for Load Frequency Control (LFC) applications to efficiently stabilize the power system by minimizing frequency undershoots, overshoots, and settling time. This paper proposed the application of novel Golden Eagle Optimization (GEO) algorithm for the optimal tuning of the LFC controller, which has not been previously employed in any LFC applications. Moreover, this paper presents the first-ever implementation of a hybrid energy storage system consisting of Vanadium Redox Flow Battery (VRFB) and Super Magnetic Energy Storage System (SMES) coupled with AC/HVDC transmission lines in a multi-area power system. A GEO optimized Proportional-Integrative-Derivative (GEO-PID) robust controller is designed with the Integral Time Absolute Error (ITAE) objective function to enhance the power system’s stability. The proposed controller is tested on two and four areas power systems considering the sensitivity and nonlinearity of the power systems. A robustness test is also performed to verify the stability of the system under randomly chosen loading conditions. In comparison with particle swarm optimization, dragonfly algorithm, sine cosine algorithm, ant lion optimization, and whale optimization algorithm, the GEO-PID controller significantly reduced the settling time up to 80% for different area’s frequencies. Simulation results indicate that the proposed controller outperforms other recent optimization algorithms by effectively dampening the frequency and tie-line deviations with less settling times, as well as reduced frequency undershoots and overshoots.

Reliability-Centered Maintenance for Overhead Transmission Lines in Composite Power System

Reliable overhead transmission lines have a vital role in maintaining the reliability of power systems at a desirable level and ensuring the continuity of electrical energy. In this regard, a proper preventive maintenance program can ensure the reliable functioning of transmission lines. Based on the concept of reliability-centered maintenance, this paper proposes a preventive maintenance strategy that can be implemented in real power systems due to the limited data requirements. The priority of each line for preventive maintenance was obtained by two indices revealing the technical condition and importance of each line in the network. The proposed method was applied to a real transmission network in Khorasan province of Iran. In order to extract the condition index of lines, failure statistics during six recent years as well as technical data of lines were investigated. Moreover, this paper presents a two-stage method to determine the importance index of each line by evaluating the consequences of line failures on the network. The presented results show the efficiency of the proposed approach.

PFMD: A Power Frequency Magnetic Anomaly Signal Detection Scheme Based on Synchrosqueezed Wavelet Transform

Magnetic anomaly signal detection (MASD) is a passive method for the detection of visually obscured ferromagnetic objects. This paper proposes a new method for MASD based on the ambient field of power frequency magnetic (power transmission line system). Moreover, a new information extraction technique is extended by employing Synchrosqueezed Wavelet Transform (SSWT) to improve the accuracy of the MASD method. With the extended information extraction technique, the time-frequency information of the anomalies can be efficiently distinguished from the power frequency magnetic anomaly signal. The multi-component of the time-frequency information is separated by extracting the time-frequency ridges in the spectrogram. The complexity of time-frequency information is evaluated using Rayleigh entropy. Compared with the continuous wavelet transform and short-time Fourier transform, the Rayleigh entropy of our method is reduced by 4.1886 and 4.3623, respectively. Finally, the efficiency of the new method is verified by the outfield experiments.

Fast screening method for important transmission lines in electrical power system

Abstract In the electrical power system, a few transmission lines play a crucial role in cascading failures propagation. Once it participates in the cascading failures propagation process, catastrophic power blackouts will inevitably occur. In this paper, the Electrical Transmission Line-Stochastic Approach for Link Structure Analysis method (ETL-SALSA method) is proposed, which combines the Internet thinking with the physical characteristics of power system. At the same time, important transmission lines are screened to prevent cascading failures of the power system. Additionally, considering the influence of hidden failures, the expanded adjacent matrix concept is proposed. Based on the expanded adjacent matrix, fault propagation relationship and topology structure are also taken into account in the ETL-SALSA method. In the calculation process of ETL-SALSA method, Markov probability transfer matrix of the Stochastic Approach for Link Structure Analysis algorithm (SALSA algorithm) of random method is adopted, so as to achieve higher computational efficiency. Simulations carried out on the IEEE 39-bus electrical power system and the IEEE 118-bus electrical power system show that the ETL-SALSA method can achieve high-accuracy to screen important transmission lines compared with graph theory method and cascading failure simulation method. Moreover, the screening speed of the ETL-SALSA method can be enhanced for several orders of magnitude compared with cascading failure simulation method.

A Novel Improved Crow Search Algorithm to alleviate congestion in power system transmission lines

Congestion management is one of the most critical issues in the operation of deregulated power systems. This research work proposes a Congestion Management (CM) approach considering the optimal real power rescheduling of power system generators. The Generator Sensitivity Factors (GSF) have been considered to select the most sensitive generators that would participate in CM. An Improved Crow Search Algorithm (ICSA) has been formulated to minimize the congestion cost. The stages of exploration and exploitation of the Crow Search Algorithm (CSA) have been modified with the incorporation of the dynamic awareness probability and Lévy​ flight approach for the formulation of ICSA in CM. The CM cost optimization problem was validated using the standard 39-bus new England system and the IEEE-118 bus system. A comparison analysis with other optimization techniques has also been carried over to further assess the performance of the proposed ICSA approach. The obtained results showed that the congestion cost achieved with ICSA has been reduced by 1.84%, 4.01%, 6.25%, when compared to the Differential Evolution (DE) Algorithm, Grey Wolf Optimization (GWO), and Crow Search Algorithm (CSA), respectively, for the 39-bus system. For the IEEE 118-bus system, the application of ICSA has curtailed the congestion cost by 2.50%, 8.55%, and 12.50%, when compared to the congestion cost achieved with DE, GWO, and CSA, correspondingly. It is observed that the performance of ICSA for CM cost has superseded the other approaches adopted for CM.

Application of Wavelet Packet and Fuzzy Algorithm in Power System Short Circuit Fault Classification

Short-circuit fault, also known as a lateral fault, is one of the common types of faults in power transmission lines. This paper proposes an accurate method for identifying short-circuit fault types for power transmission line systems. According to the three-phase A, B, and C values, short-circuit faults can be subdivided into ten classes. An MDL power system with controllable short-circuit fault types is designed and tested. The method of using wavelet packet to analyze short-circuit fault waveforms and using the fuzzy controller to analyze eigenvectors is also proposed. Wavelet packet analysis makes up for the defect that wavelet transform usually only decomposes low frequencies and retains high frequency. Therefore, more accurate frequency band information and eigenvectors are obtained through wavelet packet transform, and then, the fuzzy controller is used to identify the eigenvectors, which can effectively detect and discriminate short-circuit fault types. Accurate identification of short-circuit fault types can improve transmission lines’ overall operational efficiency and promote the power system’s development.

Time-Domain Differential Protection of Transmission Lines Based on Bayesian Inference

This paper presents a time-domain differential protection method based on the Bayes’ Theorem and on the current samples to determine the fault occurrence probability as a function of time. It also describes the theory involved in developing the proposed protection method when considering the differential protection of transmission lines. The authors performed fault simulations using an existing electrical system modeled in EMTP varying the fault type, phases involved, fault resistance, inception angle, and fault location, and carried out a sensitivity analysis regarding high impedance faults, current transformer saturation, noisy data, misalignments between terminal samples and power swings. The authors also tested the proposed method against actual fault events from four existing transmission lines of the Brazilian interconnected power system. All results indicate that the proposed solution is fast, accurate, secure, and dependable.