Double-circuit Transmission Line Research Articles

Reliable Protection for Static Synchronous Series Compensated Double-Circuit Transmission Lines Based on Positive Sequence Active Power Calculations Using Pmus

Reliable Protection for Static Synchronous Series Compensated Double-Circuit Transmission Lines Based on Positive Sequence Active Power Calculations Using Pmus

Comprehensive research on hybrid energy storage strategies of park microgrids with optical storage and DC microgrids

The multi-circuit coupling transmission mode is an inevitable trend of power grid construction, mainly with partially coupled multi-circuit lines. Affected by the local coupling between lines, the existing fault location methods have large errors. To this end, fault analysis and fault location methods are carried out on partially coupled double-circuit transmission lines. According to the structure and characteristics of the partially coupled double-circuit transmission line on the same tower, the voltage and current interface equations at the coupling demarcation point of the partially coupled double-circuit transmission line are established using line decoupling theory. On this basis, a time-domain analysis model of fault location for each coupling section is constructed, and a time-domain method for fault location of partially coupled double-circuit transmission lines is proposed. Finally, the electromagnetic transient simulation software is used to construct a partially coupled double-circuit transmission line model on the same tower, and a comprehensive simulation verification is performed. The results show that the proposed method has high accuracy.

A novel line parameter adaptive phasor domain fault location method for double-circuit transmission lines

• Accurate phasor domain fault location for double-circuit transmission line. • Fault location without acquiring information of line parameters. • Uniqueness and convergence of the fault location equation solution. Phasor domain methods had been commonly used in power transmission line fault location. To improve the accuracy and line parameter adaptive ability of phasor domain fault location, this paper studies a two-terminal phasor domain line parameter adaptive fault location method. First, this paper analyses the convergence issue of original multi-dimensional non-linear fault location equations. Then, by regarding the four complexes consist of fault distance and line parameters as the new unknowns and thereby supplementing a constraint equation about the new unknowns, a quadratic fault location equation set is reconstructed. Furthermore, it is mathematically proven that the four new unknowns are all within the first quadrant. Therefore, the elements in the Jacobian matrix of the reconstructed equation set are all proven to be of symbolic invariance within the solution space. Thus, by using Newton-Raphson method and setting the initial iteration value of the four unknowns to any complexes within the first quadrant, the iteration solution of the reconstructed equation set will converge to the true solution. Finally, electro-magnetic fault simulations are used to evaluate the proposed method. The test results demonstrate that the proposed method is able to guarantee fault location accuracy under different circumstances without knowing line parameters.

Active and Reactive Power Control in Transmission Line with PSO Optimized PI controlled Five Level UPFC

Abstract: In this paper, particle swarm optimization (PSO) optimized PI controlled five level UPFC is proposed for a double circuit transmission line. To enhance UPFC performance, a different approach is considered here. It uses simplified power system models to derive the decoupled power controllers, but detailed modeling of the UPFC power converters improves their ride-through capability. This paper introduces decoupled linear UPFC power controllers to obtain the reference ac voltages and currents for the two back-to-back-connected three-phase five-level NPC converters that enforce active and reactive power control in the transmission line. This paper proposes three main contributions to increase the dc-link voltage steadiness of multilevel UPFCs under line faults: 1) decoupled active and reactive linear power controllers; 2) real-time PWM generation; and 3) balancing of dc capacitor voltages. The MATLAB/SIMULINK model for the proposed circuit with PSO-optimized PI controlled five level UPFC is shown here with the results.

Active and reactive power control in transmission line with PSO optimized PI controlled five level UPFC

In this paper, particle swarm optimization (PSO) optimized PI controlled five level UPFC is proposed for a double circuit transmission line. To enhance UPFC performance, a different approach is considered here. It uses simplified power system models to derive the decoupled power controllers, but detailed modeling of the UPFC power converters improves their ride-through capability. This paper introduces decoupled linear UPFC power controllers to obtain the reference ac voltages and currents for the two back-to-back-connected three-phase five-level NPC converters that enforce active and reactive power control in the transmission line. This paper proposes three main contributions to increase the dc-link voltage steadiness of multilevel UPFCs under line faults: 1) decoupled active and reactive linear power controllers; 2) real-time PWM generation; and 3) balancing of dc capacitor voltages. The MATLAB/SIMULINK model for the proposed circuit with PSO-optimized PI controlled five level UPFC is shown here with the results.

Fault Identification of Double-circuit Transmission Lines on The Same Tower Based on CEEMDAN-SSA-SVM

In order to improve the reliability of double-circuit transmission lines on the same tower, by analyzing the variation law of inverse wave of fault voltage inside and outside the area, a support vector machine (SVM) method for internal and external fault identification of double-circuit transmission lines on the same tower based on adaptive noise complete ensemble empirical mode decomposition and sparrow search algorithm optimization is proposed. This method carries on the phase mode transformation of the current and voltage after the fault. The inverse wave current in the time window after the fault is adaptively decomposed by CEEMDAN, and the corresponding energy entropy is extracted to form the feature vector. The SMOTE algorithm is used to balance the fault samples outside the region. Finally, the feature vector set is input to the SSA-SVM classifier for training and testing. Through theoretical and simulation analysis, the following results are obtained: the algorithm in this paper is not affected by fault initial angle, transition resistance and fault distance.

Fault Location Method for the Double-circuit Transmission Line Based on Electromagnetic Time Reversal

The current fault location ways for the double-circuit transmission lines on the same tower do not consider the coupling relationship of transmission lines. The fault location accuracy is low in practical application. Therefore, a fault location method for the double-circuit transmission lines on the same tower basing on electromagnetic time reversal is proposed in this paper. The six-sequence component method is used to transform the transmission line’s impedance matrix to eliminate the coupling between the lines of the double-circuit transmission line on the same pole. The positive and negative phase characteristics of the transmission line are analyzed by using the fault section identification function to decide the transmission lines’ fault section. The mirror line is constructed by applying the electromagnetic time reversal to measure the distance of the fault point. The experimental results indicate that the maximum error of fault location is only 0. 01 km for a double-circuit transmission line on the same tower, which has high measurement accuracy and good practicability.

Distance Relaying of Asymmetrical Double-Circuit Transmission Lines Considering Abnormal Faults

Distance Relaying of Asymmetrical Double-Circuit Transmission Lines Considering Abnormal Faults

Adopting Differential Lightning Protection Measures to Reduce Simultaneous Trip Probability of 220 kV Double-Circuit Transmission Line on the Same Tower

Double-circuit lines on the same tower are more widely used due to the increasing shortage of transmission corridors. If lightning strikes cause simultaneous tripping, it will cause severe economic losses and safety problems. Transmission lines with 220 kV voltage level are an essential part of the main grid. Reducing the simultaneous tripping rate of 220 kV lines is extremely important for the safe operation of the power grid. This paper analyses the advantages and disadvantages of several typical lightning protection methods for double-circuit lines on the same tower by simulation calculation. Combined with the characteristics of several typical double-circuit towers, lightning protection design for double-circuit lines is studied, and the differentiated lightning protection methods and basic protection processes for typical lines are proposed.

The Impact of Ferroresonance and Low Frequency Phenomena on Power Transformers and Transmission systems

Ferroresonance is a low frequency phenomenon that can occur when one side of a double circuit transmission line connected to a transformer is switched out. This can result in the transfer of power from the adjacent circuit through mutual coupling into the de-energised circuit. This can lead to saturation of the transformer and stressing of the disconnector during opening. More typically, ferroresonance will affect control and protection functions preventing circuit operations and possibly requiring an unplanned double circuit outage to safely isolate the distressed transformer. In the UK a number of power transformers are exposed to ferroresonance and remote switching where they are connected to mesh corner and circuit tee configurations. Ferroresonance will continue for a few minutes until it can be detected and quenched. In cases where it cannot be detected, this can be much longer until the transformer is fully isolated. There are a number of ferroresonance modes, which may affect the unit differently, little is known to what degree this is damaging the transformer. This paper briefly discusses the results of system tests carried out to investigate the effect of ferroresonance and subsequent modelling work. The validation of a detailed transient model has been carried in an attempt to understand the effect of ferroresonance and quantify the energy injected into the transformer core during various ferroresonance modes. The article concentrates on the early stages of this work and the impact of ferroresonance on network infrastructure including transformers, switchgear, protection and control.

Genetic algorithm optimization to minimize fields, maximize power, and inhibit corona of high voltage transmission lines by arranging the conductors

AbstractIn this paper, a comprehensive study is presented whereby genetic algorithm optimization (GAO) is used to find the best arrangement of three‐phase high‐voltage transmission line (TL) conductors, that minimizes emitted electric and magnetic fields (EMFs), maximizes power capacity, and avoids corona. Moreover, a financial cost study is conducted in order to show the feasibility of implementing such rearrangement, where construction costs are compared with the impact on a populated area in close proximity to the line. To facilitate applying the procedure of this paper, a detailed description of each step is provided. Both single circuit as well as double circuit transmission lines are considered, and bundled conductors are analyzed. To demonstrate the validity and usefulness of the mathematical formulation and MATLAB computer codes, computed results are compared with measured data where good agreement is observed. To show that using GAO for solving high voltage line problems is an alternative to other robust optimization techniques such as particle swarm optimization (PSO), GAO solutions are compared with PSO solutions. The GAO results are also compared with the unoptimized results, where significant improvements can be seen. Since according to this algorithm, line conductors move freely throughout the solution space in an attempt to find the best solution, it is important to restrict this movement in order to adhere to the separation limits of the transmission line international standards IEC‐71.

Performance research on ZigBee wireless sensor network self-organizing network for 220 kV four-circuit transmission lines on the same tower

With the integration of massive power transmission equipment and the Internet of Things (IoT), it is particularly important to choose a suitable low-power sensor networking structure, when facing a large amount of on-site sensing data. To select a suitable ZigBee network structure with a large number of embedded sensing nodes, for 220 kV four-circuit transmission lines on the same tower, this paper uses OPNET simulation software to conduct three different ZigBee wireless sensor network (WSN) models, respectively with star, tree and mesh topologies. Then, the performance of the Media Access Control (MAC) layer (delay and throughput performance), application layer (end-to-end delay and traffic received performance), and network layer (number of hops and packets dropped performance) is further investigated and compared for these three different ZigBee WSNs under 220 kV transmission scenario. Considering that quantity of sensing nodes would influence the ZigBee WSN performance greatly, thus, the simulation results under two application scenarios, 220 kV four-circuit transmission lines on the same tower and 500 kV double-circuit transmission lines on the same tower, were thoroughly compared and analyzed in this paper.

Image processing based fault classification in power systems with classical and intelligent techniques

This paper is devoted to develop interest of power system engineers in learning basic concepts of image processing and consequently using deep networks to solve problems of complex power system networks. To this end, we study fault classification in a power system through automation of equal area (EAC) criterion. By considering EAC graphs as images and using classical image processing techniques, we successfully distinguish between different transient conditions including sudden change of input power as well as short circuit at the sending end and middle points of a single and double circuit transmission lines. In addition to classification, some parameters are also determined from EAC images such as initial rotor angle, clearing angle, and maximum rotor angle. Further, the use of deep networks is introduced to perform the same task of fault classification and a comparison is drawn with multilayer perceptron neural networks. Developed algorithms are tested in MATLAB as well as Pytorch environments.

Integrated wind turbines and power transmission line: A novel concept

New technologies for wind energy systems have received great attention globally in recent years. These technologies are trying to reduce the drawbacks of conventional wind systems. This paper introduces a novel concept for wind systems to improve efficiency, reduce costs, and reduce environmental damage. The proposed system is considered from two viewpoints in this paper. Firstly, the design of a novel structure of wind turbines and power transmission towers that combines power transmission lines and wind blades. Secondly, a new power delivery method for injecting the power generated by the wind turbines is proposed. In the proposed system, a common tower is used to hold both the conductors of the transmission line and vertical-axis wind turbines, which as a result, wind turbines are located in the Right Of Way (ROW) area of the transmission line. For injecting the power of wind turbines into the transmission line in a double-circuit transmission line, creating a specific phase difference between the two lines creates a suitable voltage difference between them for injecting wind turbine power to the transmission line without using large transformers. The power circuit of the proposed system and its performance have also been analyzed. Moreover, the created voltage equation between the two lines and each wind turbine's generated power according to the system parameters are obtained. Finally, the proposed system is simulated by MATLAB software and compared with the conventional wind farms.

Series capacitor-compensated double-circuit transmission line directional relay system using a fuzzy expert system with a Haar wavelet

Series capacitor-compensated double-circuit transmission line directional relay system using a fuzzy expert system with a Haar wavelet

Performance evaluation of machine learning for fault selection in power transmission lines

Learning methods have been increasingly used in power engineering to perform various tasks. In this paper, a fault selection procedure in double-circuit transmission lines employing different learning methods is accordingly proposed. In the proposed procedure, the discrete Fourier transform (DFT) is used to pre-process raw data from the transmission line before it is fed into the learning algorithm, which will detect and classify any fault based on a training period. The performance of different machine learning algorithms is then numerically compared through simulations. The comparison indicates that an artificial neural network (ANN) achieves remarkable accuracy of 98.47%. As a drawback, the ANN method cannot provide explainable results and is also not robust against noisy measurements. Subsequently, it is demonstrated that explainable results can be obtained with high accuracy by using rule-based learners such as the recently developed quantitative association rule mining algorithm (QARMA). The QARMA algorithm outperforms other explainable schemes, while attaining an accuracy of 98%. Besides, it was shown that QARMA leads to a very high accuracy of 97% for highly noisy data. The proposed method was also validated using data from an actual transmission line fault. In summary, the proposed two-step procedure using the DFT combined with either deep learning or rule-based algorithms can accurately and successfully perform fault selection tasks but indicating remarkable advantages of the QARMA due to its explainability and robustness against noise. Those aspects are extremely important if machine learning and other data-driven methods are to be employed in critical engineering applications.

An Ultra-High-Speed Algorithm for Fault Classification in Double Circuit Transmission Lines Using Only the First Group of Received Current Traveling Waves

This paper presents a new and very fast fault detection (FD), fault classification (FC), and fault phase selection (FPS) method, which is just based on the first group of current traveling waves (cTW) in double circuit transmission lines (DCTLs). All internal, inter-circuit faults and lightning strikes on transmission line (TL) phases and shield wires are reviewed. By the proposed algorithm, FC and FPS are performed in the shortest possible time. In this study, wavelet transform (WT) is used to extract the traveling wave (TW) caused by the fault from the current signal of one DCTL terminal, and only the first group of these waves is used for FC and PFS to increase velocity. To classify various fault types, the zero components of TWs of the two lines, which can be calculated using the conventional modal transforms and another modal transform of 6*6 dimensions defined on all six phases of the DCTL, is used. All simulations are performed in PSCAD on a 230kV grid and a DCTL of 200km length. Also, the performance of the proposed algorithm is tested under various fault and lightning conditions in the presence of white noise with different incidence angles and various fault resistances.

A novel strategy for fault location in shunt-compensated double circuit transmission lines equipped by wind farms based on long short-term memory

Parallel lines are one of the main parts of the power systems due to their capability of increasing the transmitted power and reliability of the power network. However, due to their complexity, fault location in these transmission lines has always been a potential problem. Furthermore, when the wind farms are connected to the power networks, a new challenge is created for the fault location algorithms. The reason is that the impedance changes continuously in these wind power plants. Moreover, the Static Var Compensator (SVC), which is used for compensation in transmission lines, can cause problems in accurate calculation of the fault location in power transmission lines. Accordingly, this paper presents a new method based on Long Short-Term Memory (LSTM) networks for source impedance and other network parameters estimation, which are key parameters to calculate the fault location accurately. The simulations are accomplished using PSCAD and Python software on a sample two-circuit network. This network consists of two parallel lines, a wind farm, and a synchronous generator to supply the network's power. The double-fed induction generator (DFIG) model is considered as the wind farm in the studied network. The results obtained from the tests clearly illustrate the applicability of the proposed method to estimate fault location and source impedance with high accuracy. • A fast and accurate fault location algorithm is achieved using Long Short-Term Memory (LSTM) networks. • Determining the location of different fault types in two circuit transmission lines. • Accurate performance for the location of different fault types under nosy conditions. • Estimation of the source impedance with a much smaller error value.

An algorithm scheme for detecting single-circuit, inter-circuit, and grounded double-circuit cross-country faults in GUPFC-compensated double-circuit transmission lines

An algorithm scheme for detecting single-circuit, inter-circuit, and grounded double-circuit cross-country faults in GUPFC-compensated double-circuit transmission lines

Optimization-Based Fault Location Algorithm for Series-Compensated Power Transmission Lines

This paper presents an optimization-based fault location algorithm applicable to series-compensated power transmission lines. The presented method determines the fault location minimizing the errors between measured and calculated post-fault voltage and current phasors through a dynamic differential evolutionary optimization algorithm. This fault location solution may be advantageous over existing approaches found in the literature as it can locate any fault regardless of the series compensation’s design, impedance, and positioning. To validate the proposed algorithm, the authors tested it against more than a thousand and six hundred faults on a 500 [kV] series-compensated double-circuit transmission line simulated in ATP/EMTP. The results indicate that the presented method yields accurate fault location estimates, with errors within the 1% magnitude using post-fault steady-state and transient data. In addition, the proposed algorithm is robust even in situations featuring high-resistance faults, errors in the line’s parameters, in the system equivalents connected to and between the line’s terminals, and in phasor extraction, configuring it as an accurate and reliable alternative to locate faults within series-compensated lines.