Power Swing Conditions Research Articles

A fast, simple and local protection scheme for fault detection and classification during power swings based on differential current component

Among the various challenges of transmission line distance protection, it has become increasingly difficult to deal with the symmetrical phenomenon of power swing (PS) and it can lead to maloperation of distance relays and power system blackout. Distance relays have challenges in distinguishing the symmetrical fault during power swing and would send a wrong trip command to the circuit breakers, leading to major blackouts. To solve this issue, the main objective of this study is to provide a fast, simple, and local protection scheme based on differential current component (DCC), which is extracted by the difference in predicted and actual samples of local current component. Autoregression technique is used to predict the future cycle current samples using available samples. Based on the DCC, a novel index named differential current component ratio (DCCR) is introduced to effectively detect the internal symmetrical faults from fast/slow power swing conditions. Several tests are run for different fault types, different power swing frequencies, different fault locations, different fault resistances and different fault inception instants. Finally, the results are compared with the available methods. Results demonstrate the high accuracy of the proposed method in fast and accurate detection of internal symmetrical faults during power swing in different frequency rates in less than one cycle.

MFCDFT and impedance characteristic-based adaptive technique for fault and power swing discrimination

ABSTRACT In today’s fast-changing power systems, it is vital to have a protection system that can distinguish between power swing and fault conditions. With advanced protective devices (Digital Relays), an appropriate protection strategy can be established to identify power swing and fault conditions individually. The proposed algorithm uses the sliding window concept, which requires very little computational data unless any abnormal conditions exist in the power system. Modified Full Cycle Discrete Fourier Transform (MFCDFT) is more effective in the extraction of the fundamental phasors from the original complex signal by effectively removing the harmonics and DC components. An adaptive impedance characteristic-based MFCDFT is utilized for the discrimination of power swing and fault in this work. Several fault scenarios and power swings are generated on the test system concurrently and independently from the relay station at varied distances. PSCAD/EMTDC is utilized on a single-machine infinite bus system to analyze various test conditions. The simulation is utilized in this case to collect data from various test circumstances. After obtaining the data, the MFCDFT algorithm along with adaptive impedance estimation is performed using MATLAB code. After examining various test results, it is discovered that the suggested technique correctly recognizes power swings and various fault scenarios. It can also identify the difference between stable and unstable power swings. According to the results, the proposed technique is proficient at spotting fault and power swing conditions. In addition, the algorithm ensures dependable operation with quick detection and avoids maloperation under a typical swing condition.

Detecting loss of excitation condition of synchronous generator in the presence of unified power flow controller based on data mining method

Loss-of-excitation (LOE) conditions may cause devastating effects on both the generator and power system. If LOE is not meticulously detected, two dangerous events may emerge: 1. unnecessary trip signal, 2. not detecting this abnormal condition or detecting it with time delay. Both mentioned flaws have considerable harmful consequences on the generator and power system. Conventional techniques for detecting LOE conditions are based on impedance measurement. The presence of flexible alternating current transmission (FACT) system devices can considerably affect the impedance characteristic of the system and as a result, the operation of impedance-based relays. This paper simulates LOE and stable power swing (SPS) conditions causing failures and errors in the LOE protection in the presence or absence of a unified power flow compensator (UPFC), and parameters with different behaviors are determined. Then, the most sensitive parameters are combined using an intelligent method. The single parameter, achieved from a combination of features in the previous process, is applied to a learning vector quantization (LVQ) neural network. The LVQ is a type of artificial neural network that is based on a prototype supervised learning classification algorithm and trained its network through a competitive learning algorithm. The simulation results show that, in a single machine infinitive bus (SMIB) test system, R-X directional scheme has 2 mal-operations and the proposed algorithm has no mal-operation without UPFC in the system. With UPFC in the system, the R-X directional scheme has four mal-operations and the proposed algorithm has no mal-operation. In the IEEE 9-bus test system, the R-X directional scheme has five mal-operations and the proposed algorithm has no mal-operation. Moreover, applying the proposed algorithm, LOE is detected very quickly in the presence or absence of the UPFC in the system and this approach prevents electrical and mechanical stresses enforced to the machine and power system. © 2017 Elsevier Inc. All rights reserved.

Single fuzzy inference based fault detection and classification protection scheme for different types of short circuit faults on double circuit transmission lines

ABSTRACT An intelligent protection scheme based on the single fuzzy inference system and discrete Fourier transform is proposed for the faulty phase detection and classification of faults on the mutually coupled double circuit transmission lines. This proposed protection technique uses the magnitude of the pre-processed current information of the sending end bus only. This is implemented in the MATLAB/Simulink environment on a 400 kV, 50 Hz, and 300 km double circuit power system model. The efficacy of the proposed scheme has been tested by performing a wide range of simulation studies concerning different types of faults (common short circuit faults, cross-country and evolving faults, and high impedance faults) and typical fault scenarios (current transformer saturation, noisy environment, and fault during power swing conditions) with variations in different fault parameters and operating conditions. The results presented confirm that the proposed method detects/classifies all the faults within one cycle time and is reliable with a detection/classification accuracy of 99.75%. It is immune to variations in fault parameters, and different operating conditions, and is not affected by the zero sequence mutual impedance. It does not require any training and communication link. Further, the performance is also appraised with other training-based protection schemes.

Accurate Superimposed Component Estimation for Improved Relay Performance During Power Swing

There is continuous variation in amplitude, phase, and frequency of voltage and current signals during power swing in a power system. Such variation makes the memorized prefault data less accurate to be used as nonfault component while computing superimposed quantity for protection decisions during power swing. In this article, the voltage and current signal characteristics during power swing are analyzed and a technique is proposed to obtain correct nonfault components for superimposed quantity computation. The accuracy of the method in estimating the nonfault components is observed for different power swing conditions simulated in a 39-bus New England system and field data. The relay performance improvement as observed is also provided while applying the method to directional relaying, fault type classification, and fault location applications for faults during power swing. Comparative assessment reveals the superiority of the proposed method in improving the accuracy of the superimposed components computed during power swing.

Discrimination between in-zone and out-of-zone faults during power swing condition using synchrophasor data

A new algorithm to discriminate between in-zone fault and out-of-zone fault conditions under power swing condition for wind/synchronous generators (WG/SG) integrated power transmission network is presented in this paper. The proposed algorithm is based on the calculation of a transmission line positive sequence power loss index, derived by calculating the absolute difference between the calculated and measured values of positive sequence real power loss. The authenticity of the proposed technique is verified by performing Hardware-in-Loop (HIL) simulation in the Real-Time Digital Simulator (RTDS) framework along with physical Phasor Measurement Units (PMUs), Phasor Data Concentrator (PDC), Global Positioning System (GPS) clock, and voltage and current amplifiers. Various events such as power swing, in-zone (including close-in and high resistance) faults during power swing and out-of-zone faults during power swing are simulated by modeling WG/SG integrated IEEE-9 bus system in RSCAD (Real-Time Simulator Computer-Aided Design) framework. The single pole tripping, impact of noise and CT saturation on the proposed algorithm is also analyzed. The proposed algorithm offers accurate discernment between in-zone and out-of-zone faults during power swing conditions. The results obtained reveal increased sensitivity and improved distinguishing capability of the proposed algorithm in contrast to those of many other approaches proposed in the literature.

Distance Protection of Transmission Lines in Presence of Inverter-Based Resources: A New Earth Fault Detection Scheme During Asymmetrical Power Swings

Although it is commonly assumed that power swing is symmetrical and will have identical effects on all three-phase voltages and currents, there is another type of power swing, which is asymmetrical and mainly occurs during single-pole tripping (SPT), the impact of which on power systems integrated with the inverter-based resources (IBRs) has not been investigated so far. Since the likelihood of the occurrence of asymmetrical power swing is increasing in today's heavily loaded transmission lines, this article investigates the impact of IBR integration on the performance of distance protection during single-pole tripping. Furthermore, a new scheme is proposed to detect earth faults that occur during asymmetrical power swings to enhance the performance of power swing blocking functions. To do so, the superimposed component of the zero-sequence current during SPT is extracted. Then, the moving average window is used to calculate the average of both zero-sequence current and its superimposed component. Furthermore, to enhance the security of the proposed scheme, a new technique based on the phase angle shift between the three-phase currents is devised to detect the asymmetrical power swing conditions. This article shows that as the penetration level of IBRs increases, the standard reclosing dead-time needs to be revisited otherwise it can create an unstable power swing condition, even during SPT. Moreover, this article shows that the proposed earth fault detection scheme can efficiently detect all single-line-to-ground faults occurring during SPT.

IM-DWT with DNN Based Blocking Scheme of Third Zone Distance Relay in Power Swing Condition

ABSTRACT Zone 3 distance relay is linked in the system for protecting the transmission line that acts as a backup relay while the primary relay is in failure due to fault or any other issues; it can act as a secondary relay to clear the problems. Under power swing conditions, the magnitude of current and voltage is entirely in the relay to cause maloperation. In the mal-operative conditions, the relay was not working correctly as well to trip the transmission line. The above problem is mitigated by using the proper method of power swing blocking scheme. In the proposed approach, the supervision-based blocking scheme is introduced to avoid the maloperation of zone 3 distance relay under power swing conditions. The proposed blocking scheme is based on active power and the deviation of source and load voltage. The voltage and current signals are sensed by improved discrete wavelet transform (IM-DWT). It senses the power to generate the coefficients for analysis of the system conditions, whether the system is stressed or not. Here, the most advantageous algorithm of deep neural network (DNN) is utilized to analyze the IM-DWT coefficient for selecting the working function of distance relay. DNN operates two modes based on the coefficient values, namely RDL-1 (state assessment) and RDL-2 (power swing identification). The threshold-based blocking approach chooses the optimal function of DNN. The overall proposed system is implemented in the Western System Coordinating Council (WSCC) IEEE 9 bus system, and the design and performance are verified in MATLAB/Simulink software. The proposed approach is more advantageous and offers a rapid operation to avoid the maloperation of the zone 3 distance relay as compared to the existing methods like support vector machine, artificial neural network, and k-nearest neighbour.

Distance Protection Methodology for Detection of Faulted Phase and Fault Along With Power Swing Using Apparent Impedance

In this paper, a novel distance protection methodology that uses apparent impedance and concentric characteristics to identify faults and faulty phases along with power swing condition is proposed. The rate of change of apparent impedance is used to identify the fault or power swing condition. If a fault is detected, the relative location of the apparent impedance of the six distance elements with respect to their concentric characteristics is used to identify the faulty phases. The distance element(s) that compute the correct apparent impedance is(are) then enabled, which then issues the trip signal if the zone criterion is met. The proposed distance protection methodology is validated in Western System Coordinating Council (WSCC) Nine Bus System in MATLAB/Simulink by simulating various fault and power swing conditions. The results from the case studies proved that the proposed distance protection methodology could enable the right distance elements and issue trip signals during common faults and special kinds of faults like evolving and cross-country faults. Compared to others, the distinguishing feature of the proposed algorithm is its ability to identify the exact faulty phases even during special fault conditions like evolving and cross-country faults. The distance relay using the proposed methodology can issue the trip signal within one cycle for common faults and within one and half-cycle for evolving and cross-country faults.

End to end machine learning for fault detection and classification in power transmission lines

This paper proposes a new machine learning approach for fault detection and classification tasks in electrical power transmission networks. This method exploits the temporal sequence of the power system's operational data and develops an ‘end to end’ model employing Long Short-Term Memory (LSTM) units working directly on the operational data instead of features. The temporal sequences are different in the case of normal and faulty conditions. End to end learning simplifies the decision-making process and eliminates the need for complex feature extraction process by learning directly from the labelled datasets. The method is rigorously tested for all types of faults, which are further subjected to a range of fault resistance, distance, loading conditions, system parameters and noise levels. The proposed method can also work under power swing conditions. The method is also tested on WSCC 9 bus system. The proposed method has shown fast response in terms of time performance and is resilient towards operational conditions.

An adaptive cumulative sum based method for unblocking distance relays in TCSC compensated transmission lines

Fault detection in transmission lines with thyristor controlled series compensators (TCSC) can be challenging, in particular during power swing conditions. A reliable unblocking method based on the adaptive cumulative Sum (ACUSUM) is presented in this paper. This method alleviates the limitations of conventional methods and has the capability to detect all asymmetric and symmetric faults with high accuracy and speed. The proposed method measures the negative sequence of the current signal for fault detection. Two simulation case studies consisted of the single machine and infinite bus (SMIB) and the IEEE standard 9-bus and three machine systems are simulated in PSCAD/EMTDC to evaluate the proposed method. It is shown that the non-linear behavior of TCSC will not impact the accurate performance of this method.

Power Swing Blocking Algorithm based on Real and Reactive Power Transient Stability

Power swing due to the disturbance in the power system is a cause of the untrue operation of protective elements. Previously, many blackouts have been perceived and recorded due to reactive power mismatch problems, active power mismatch problems, and system venerability. The power system stability is usually disturbed due to the sudden loss of transmission lines, generators, and transformers. The present work proposes the concept of apparent power transient stability due to the transient disturbance. By considering that concept, we propose a power swing blocking algorithm to prevent mal-operation of distance relay. The proposed algorithm uses the relative frequency between the sending end bus and system standard frequency with simultaneous measurement of voltage decay of the transmission line. We have implemented the proposed algorithm on a single machine infinite system (SMIB) and the IEEE-9 bus system to compare the power swing detection and blocking performance with mho type out of step relay in different power swing conditions. In the end, results show the accurate performance, simplicity, reliability, and correct co-ordination of the proposed relay with distance relay, which ultimately solved the issue of mal-operation of zone-3 distance relay during complex power swing conditions.

A New Model of Numerical MHO Distance Relay Associated with Power Swing Detector

In conventional transmission line protection, a distance relay is used to provide the primary as well as backup protection. The voltage and current phasors measurement needed by the distance relay for determining the impedance may be affected by the power disturbances such as power swing. Consequently, this power swing may cause mal-operation of Zone three distance relays which in turn may affect on the reliability of the whole protective scheme. Many power swing blocking functions (PSB) have been developed to mitigate these effects. In this paper, a new model of Mho distance relay with dual-quadrilateral power swing detection characteristic has been developed and implemented first in PC using LabVIEW, then tested using Power System Simulink Model under different faults and power swing conditions. Finally, the relay prototype has been realized using acquisition card NI USB-6009, which acquires real-time signals of the currents and the voltages, processes them digitally and outputs tripping or blocking signal to the circuit breaker. The obtained results show that the relay provides good discrimination between a fault and power swing condition.

Creative conjugate based characteristics to detect the faulty part in the generator-transformer unit

This study presents an innovative protection method for the generator-transformer zone based on the conjugate concept of the positive sequence component. The traditional protection for such zone employs two relays which generally uses twelve CTs. The proposed method uses one protective relay and utilizes nine CTs (a protective relay and three CTs are saved). The conjugate based innovative method protects the generator and the transformer as one unit and identifies the faulted zone. Such conjugate based inventive protection is based on the building of two relations. The 1st relation is between an adaptive conjugate signal of the neutral-generator current and an adaptive conjugate signal of the generator-transformer current. The 2nd relation is between adaptive conjugate signals of both transformer sides. Various types of external and internal faults, CTs saturation conditions, power swing conditions, and generator startup conditions have been generated by simulating part of the IEEE 9 bus system in the ATP program. The results clearly display the worth of the proposed protection in detecting the various types of internal faults. Other than, the new scheme can accomplish sensible differentiation among generator faults, transformer winding faults, and external faults. What's more, it contributes to encouraging results in the cases of the CTs saturation, power swing, generator startup, generator startup with faults, and different fault parameters. It isn't affected by the type of connection of the transformer. The tripping signal to the generator will be sent in case of a fault inside the generator while the tripping signal to the transformer will be sent in case of the fault inside the transformer.

A Study on an Out-of-Step Detection Algorithm Using the Time Variation of Complex Power: Part I, Mathematical Modeling

Power quality and stability have become the most important issues in power system operations, Micro Grids, and Smart Grids. Sensitive equipment can be seriously damaged when exposed to unstable power swing conditions. An unstable system may cause serious damage to Micro Grid System elements such as generators, transformers, transmission lines, and so forth. Therefore, out-of-step detection is essential for the safe operation of a Micro Grid system. In general, Equal Area Criterion (EAC) is a method for evaluating the stability of Smart Grid systems. However, EAC can be performed only if it is possible to analyze the active power and generator angle. This paper presents an analysis of the trajectory of complex power using a mathematical model. The variation of complex power is analyzed using a mathematical method, and then the relationship between complex power and EAC is presented, and a simulation performed. Later, in part II, a novel out-of-step detection algorithm based on part I will be presented and tested.

A pilot protection algorithm for TCSC compensated transmission line with accurate fault location capability

This paper introduces a communication-aided scheme to enhance the fault detection, and fault location calculation for a thyristor-controlled series capacitor (TCSC) compensated transmission lines. In the proposed method only the current data at the remote-end should be synchronously sent to the local-end. Since the remote-end voltage data do not use in local-end, compared with the conventional pilot impedance-based protection schemes, the proposed method significantly reduces the requirement of data transmission bandwidth. The proposed algorithm is independent of fault resistance, power flow direction, and pre-fault condition. In the proposed method the TCSC parameters are not utilized in the derived fault location formula and as a result, the performance of the proposed method is not impacted due to variations in TCSC parameters. Several major factors are taken to investigate the accuracy of the proposed method, including measurement errors and power swing conditions. The simulation results prove the high accuracy and acceleration of the proposed scheme during all fault cases.

Grey wolf optimization-tuned convolutional neural network for transmission line protection with immunity against symmetrical and asymmetrical power swing

The similar current–voltage profile during power swing and fault quite often leads to maloperation of distance relays. As compared to symmetrical power swings, discriminating a swing scenario from a fault becomes more challenging during asymmetrical swings arising due to single-pole tripping. Unlike symmetrical power swings, the presence of zero-sequence and negative-sequence current during asymmetrical swing scenarios hinders the application of classical power swing blocking schemes. In this regard, a convolutional neural network (CNN)-based protection scheme has been proposed in this paper, which, in addition to detecting, classifying, and locating faults, is also able to discriminate between power swing (both symmetrical and asymmetrical) and faults. The discrimination avoids possible maloperation during the non-faulty stressed conditions, thereby overcoming the limitation of the existing protection scheme. With the convolutional neural network, the raw signals are directly fed to the classifier, thus avoiding the computational cost associated with feature extraction in time and frequency domains. With the aim of achieving improved input–output mapping capability of CNN for larger datasets, an evolutionary optimization technique, i.e., grey wolf optimization, has been utilized for determining the optimal values of CNN tuning parameters. The performance of the proposed scheme has been extensively validated for a wide range of fault and power swing conditions in terms of standard indices, i.e., dependability, security, and accuracy. The effectiveness of the proposed scheme has also been evaluated for practical setting by performing real-time simulation on OPAL-RT digital simulator.

Secure Loss of Excitation Detection Method for Synchronous Generators During Power Swing Conditions

Conventional loss of excitation (LOE) detection methods for synchronous generators may misoperate during power swings. In this paper, a novel method based on measured slip frequency at the terminal of synchronous generators is proposed to differentiate power swing conditions from LOE conditions. To enhance performance of the proposed method for noisy measured signals, a modified Prony method based on a combination of generalized total least-squares method and conventional Prony method is implemented to estimate slip frequency and an energy sorting technique is applied to distinguish the dominant frequency components of measured signals. Performance of the proposed method is evaluated under various operating conditions of a test system that is simulated in a co-simulation platform by linking CAPE and PSS/E software. Case study results illustrate that the proposed method can accurately differentiate power swing conditions from LOE conditions.

Sequence‐space‐aided SVM classifier for disturbance detection in series compensated transmission line

Sudden changes in loading or weak constitution of power network causes power swing which may aggravate miss-operation of protective elements. Consequently, it becomes utmost essential to rapidly and accurately distinguish between fault and power swing conditions to prevent instability in smart power grid equipped with compensation. This study demonstrates an effective disturbance classifier scheme for series compensated transmission line (SCTL) for discrimination during disparity in power grid contexts using sequence-space-based support vector machine (SVM) classifier. The test data sets are generated by performing extensive simulations in PSCAD software by varying system and fault context. SVM architecture has been trained and tested by generating feature vector using modified full cycle discrete Fourier transform in MATLAB. After proper extraction of features of the interest at the time of disturbance, a decision about power swing or fault has been carried out using SVM classifiers. Regulation and kernel function parameter have been tuned using ten-fold cross-validation applied on training set. The developed scheme is also evaluated for symmetrical fault detection during power swing and shows remarkable improvement in accuracy and speed for protection of SCTL in comparison to existing schemes.

A covariance indices based method for fault detection and classification in a power transmission system during power swing

This paper presents a new scheme based on a combination of the current signals covariance with the cumulative approach to identify faults in the power transmission system during the power swing conditions. Primarily, the covariance is used to extract the features which are useful to identify the fault from the current signals that measured at both terminals. The cumulative approach is used to enlarge the fault feature and then create a convenient index for detection and classification during the power swing. The proposed algorithm has been tested through different fault circumstances such as multiple fault locations, multiple fault resistances, and multiple fault inception time. Moreover, fault happened nearby the terminal, fault considering variable loading angles, sudden load change, power flow direction change, faults in the presence of series compensation and fault occurred in the presence of noise are also considered. The empirical results show that the approach proposed in this study has made a reasonable time response, where the fault could be detected within a few milliseconds after the fault inception. Additionally, the simple computation process depicting our proposal makes it more suitable and efficient for practical engineering applications.