Power Swing Research Articles

Comparison of Pattern Recognition Techniques of Loss of Excitation and Power Swing Using Machine Learning

Comparison of Pattern Recognition Techniques of Loss of Excitation and Power Swing Using Machine Learning

Estimation of polarity of slope of instantaneous current increment for power swing immune protection of series compensated line

Existing protection schemes for series-compensated transmission line (SCTL) lack either in reliability or speed during power swing (PS). A new ultra-fast reliable method is proposed in the present article using the slope of instantaneous current increment (SICI). The peaks of SICI (denoted by PKS) of a modal component of currents above a dynamic threshold are obtained to detect the sudden jump in SICI, which occurs after a transient disturbance. PKS of two terminal-currents are of same polarity for a fault within SCTL but they are of opposite polarity for any external event. This unique characteristic is mathematically verified and exploited to discern internal faults from external events during PS. Proposed method is found unaffected for high level of series compensation, position of compensation, close-in fault, fault inception point, high fault resistance, synchronization error and CT saturation. The results are finally compared to the incremental quantity-based methods to justify its merit.

A novel setting free approach to differentiate fault and power swing using support vector machine

A novel setting free approach to differentiate fault and power swing using support vector machine

Envelope based symmetrical fault detection during power swing for series compensated lines

Envelope based symmetrical fault detection during power swing for series compensated lines

Wavelet Synchro-Squeezing Transform and Dynamic Threshold Supported Symmetrical Power Swing Technique for Modern Transmission Network

Wavelet Synchro-Squeezing Transform and Dynamic Threshold Supported Symmetrical Power Swing Technique for Modern Transmission Network

Numerical investigation on vortex characteristics in a low-head Francis turbine operating of adjustable-speed at part load conditions

In this paper, the vortex characteristics in a low-head Francis turbine operating of adjustable-speed at part load conditions are numerically investigated. First, the rules of fixed-speed and adjustable-speed operations are introduced in detail, aiming at operating limits extension. Second, comparative analysis on vortex rope is conducted, with emphasis on vortex rope volume, tail water excitation and spontaneous power swing. Finally, inter-blade vortex has been analyzed and successfully demonstrated, and its induced high amplitude pressure fluctuation characteristic is explored. It is found that at deep part load, vortex rope volume and power swing coefficient of adjustable-speed operation decreased by 69 % and 61 % respectively. The amplitude of Rheingans frequency decreased by 17 %, while the amplitude of blade passing frequency increased by 83 %. After decreasing runner speed, inter-blade vortex is stranded at blade suction surface leading-edge. In addition to low-frequency disturbance, pressure fluctuation shows high-frequency wide-band characteristics. It is concluded that adjustable-speed operation has beneficial effects on improvement of cavity cavitation and energy stability. As for hydraulic stability, the Rotor-Stator Interaction effect cannot be ignored. After changing runner speed, the inter-blade vortex becomes more serious, which could provoke low-cycle and high-cycle fatigue of the blades.

Optimization design of an innovative francis draft tube: Insight into improving operational flexibility

Hydropower has transitioned from base-load generation into an energy regulator in the hydro-wind-solar integrated systems, resulting in prolonged turbine operation under off-design conditions. Inspired by the new requirements of operation mode, an innovative Francis draft tube with inclined conical diffuser is presented to mitigate the pressure fluctuations and fatigue damage induced by flow instabilities. The design is optimized and comprehensively investigated to improve the operational flexibility. Computational fluid dynamics combined with design of experiments, artificial neural network and multi-objective optimization process lead to two optimal designs denoted as Opt-1 and Opt-2 from the Pareto fronts. Corresponding maximum pressure fluctuation amplitude is reduced by 15 % and 20 % compared to the traditional, respectively. An 81 % decrease of the fluctuating pressure recovery for the modified draft tube is obtained, leading to a steadier runner torque and consequently lower power swing. The asymmetric design of inclined daft tube is mainly targeted at the mitigation of the synchronous component as well as the attenuation of interaction between the swirling flow and elbow, accompanied with the mitigated energy of first-order vortex structure. The proposed innovative draft tube and optimization technique are found useful to broaden the operating range of hydraulic turbine in a computationally affordable way.

Signal Envelope-Based Adaptive Power Swing Blocking

This research paper proposes detection of faults during power swings by using a peak envelope-based method to prevent incorrect distance relay operation. Distance relays should not operate during power swings except to remove a correctly detected fault event. In this study, distinction between faults and power swings is achieved by correctly observing fault occurrence based on dynamic thresholds generated by peak envelopes. The method utilizes a DC offset current in determining the fault inception and fifth harmonic voltage to assess the fault clearance. If the current surpasses the calculated threshold due to fault existence, the relay is allowed to operate. Re-blocking the relay after fault clearance is achieved in the case of a higher value of the voltage than the threshold value. Current and voltage data obtained from two different test systems simulated in PSCAD for various scenarios have been used in the proposed algorithm developed in MATLAB. In order to show the effectiveness of the proposed method, the results on the second test system have also been compared to the results of selected methods in the literature. It has been perceived that the developed method has a high accuracy and provides an appropriate time range for relay and breaker operation.

Comparative assessment of fault detection methods in transmission line during power swing: analyzing single and hybrid networks for the southern Kerala grid

The blocking function of power oscillation is a highly effective feature found in distance relays. Its purpose is to prevent unintentional tripping of transmission lines. It is crucial to accurately differentiate between faults and power oscillations to minimise the occurrence of widespread power outages and monetary losses. Therefore, the detection and classification of faults arising from power swings are critical challenges in ensuring the smooth operation and overall health of transmission lines, particularly in extra-high-voltage (EHV) and ultra-high-voltage (UHV) power systems. Modern methods rely on machine learning methods which are in their infancy. The paper proposes to identify various fault conditions in transmission lines during power swing by using a hybrid Neural Network architecture. In this research, different designs such as 2-D convolution neural network (2D-CNN), 1-D convolution neural network (1D-CNN), long short-term memory (LSTM), and CNN-LSTM hybrid networks are investigated to understand the effect of various deep learning approaches. Along with the southern Kerala grid, the standard 9-bus system is selected as a test case to examine various fault circumstances of the system during power swing. Multiple tests were conducted to determine the optimal deep learning architecture, including model parameters and configurations, for accurate fault detection. For the 9 bus system, the 1D CNN network performs better with an accuracy of 98.70%, and for the Kerala grid, both networks are competitive, but the CNN-LSTM Hybrid method slightly outperforms the 1D CNN with an accuracy of 92.40%.

Highly efficient relay triggering circuit for fault detection during Power swings

This paper introduces a Discrete Wavelet Transform based very simple and fast acting algorithm with multi-resolution analysis to sense all types of faults in presence of power swings using current signal analyzation. The algorithm confirms very quick and efficient detection of various fault types in the first signal decomposition level of signal. The novelty of proposed algorithm lies in use of special type of Battle Lemarie mother wavelet having an advantage of perfect symmetry ensuring decomposition into B-Spline or same order polynomials capturing excellent speed and time-frequency localization of signal. The algorithm is tested for different fault parameters such as fault resistance, fault distance and time of initiation of faults considering EHV double circuit transmission line network and IEEE 9 Bus system developed in MATLAB environment. The proposed algorithm is capable of detecting all types of faults consistently within minimum time of 0.001 sec.

Parameter Estimation of Power System Oscillation Signals under Power Swing Based on Clarke–Discrete Fourier Transform

Accurate knowledge of oscillation parameters (i.e., frequency, amplitude, phase, and damping factor) is crucial for control strategies of power systems under power swing. This paper presents a method for the parameter estimation of power system oscillation signals under power swing based on Clarke–DFT. The proposed method provides accurate parameter estimation of damped sinusoidal signals for both balanced and unbalanced systems, which performs well even in the presence of harmonics. In the meantime, the negative frequency components in the spectra of the damped sinusoidal signals, which are caused by system imbalance, are calculated accurately using complex-valued interpolated DFT. To verify the performance of the proposed method, simulations are performed under balanced and unbalanced conditions. The results of the simulations confirm the effectiveness of the proposed method either in unbalanced or harmonic conditions.

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.

Power Swing in Systems with Inverter-Based Resources—Part II: Impact on Protection Systems

Power Swing in Systems with Inverter-Based Resources—Part II: Impact on Protection Systems

A Curve Fitting–Based Directional Protection of Transmission Lines Using Genetic Programing

In modern power systems, there is a growing need for protection techniques that are fast, precise, and stable to enhance the reliability and stability of power networks. This paper introduces an advanced technique for fault direction estimation that addresses key limitations in existing methods. Our proposed algorithm eliminates the dead‐zone issue, effectively handling both forward and reverse faults regardless of their location, including faults near relay regions. Using genetic programing (GP), we derive a closed‐form equation to drive the fault direction estimation algorithm, ensuring accurate and reliable results. The algorithm demonstrates exceptional speed and reliability in fault detection and direction estimation, even under challenging conditions such as current transformer (CT) saturation, power swing, and source strength variations. It is also insensitive to fault resistance and fault inception angle, increasing its robustness. A notable advantage of this algorithm is its efficiency at low sampling frequencies, making it highly adaptable for industrial applications and compatible with modern software and hardware requirements. We validated the algorithm through simulations on the electromagnetic transients program (EMTP‐RV) platform and with field data from the Manesht 230 kV substation in Ilam province, Iran. The results confirm the algorithm’s impressive speed and high reliability.

Comparison of Power Swing Characteristics and Efficacy Analysis of Impedance-based Detections in Synchronous Generators and Grid-following Systems

Comparison of Power Swing Characteristics and Efficacy Analysis of Impedance-based Detections in Synchronous Generators and Grid-following Systems

Out-of-Step Detection based on Phasor Measurement Unit

The electrical power systems operate as a huge, interconnected network that extends across a large area. In the power system, there is an equilibrium between generated power and a load. Any disturbance in the system, such as a fault or a change in load, will lead to imbalance and electromechanical oscillations. As a result, the power flow between two areas varies. This is known as a power swing." Large system disturbances could lead to large rotor angle deviations between groups of generators, resulting in a loss of synchronism between generators or between interconnected systems. This is known as an out-of-step condition. To avoid equipment damage and power outages, the interconnected area must be isolated as soon as possible before the electrical system loses synchronization. In this paper, PMU data is used to measure the current, voltage, and phase angle of the three phases at both ends of two interconnected area power systems. The measured data is then used to distinguish between a power swing or fault condition and predict the future phase angle difference during the disturbances to evaluate the system stability condition. If a swing is detected, then it will be ascertained whether the swing is stable or not. The performance of the proposed method has been tested on a simulated system using MATLAB / Simulink software.

Power Swing: Detection and Prevention

Abstract Power swing is a phenomenon that is basically caused by large disturbances in the power system. If not blocked, it can cause incorrect operation of distance protection and result in incorrect or unwanted disconnection of transmission line switches. Furthermore, if not prevented, it can lead to serious damage to the generator. This paper describes the basics of power system stability during power swings, lists the effects on the distance or other relay during power swing, and presents methods for detecting power swing, both traditional and advanced. Additionally, it provides a description of the settings of the Power Swing Blocking (PSB) scheme to meet these requirements.

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.

Fault Section Recognition within Duration of Power Swing Using Teager–Kaiser Energy Operator and Sequence Components

Relaying operation is not reliable during power swing due to the presence of additional lower-frequency components of electrical signals. Relay operation is prohibited during Power swing blocking (PSB) operation to restrict the malfunctioning of the distance relay. During such periods, fault section identification (FSI) schemes need to work for safeguarding the electrical power system from disturbances. Fault detection and fault direction estimation are part of FSI. This article proposes a protection algorithm within the period of power swing where a Teager–Kaiser energy operator (TKEO) of superimposed negative sequence admittance (SNSA) is utilized for fault detection and an integrated scheme for determining their direction. In this integrated direction estimation approach, the direction of fault is recognized by calculating the phases of negative sequence admittance (NSA) and positive sequence admittance (PSA). The proposed technique is verified and tested on a WSCC 9-bus, 400 kV, 50 Hz system for different balanced and unbalanced fault cases with different fault conditions. Even, in some scenarios like CT saturation and single pole tripping (SPT), the proposed approach performs accurately. The results are simulated using EMTDC/PSCAD software.

Dynamic wide‐area cooperative protection: A new approach

AbstractThis paper introduces a new dynamic wide‐area cooperative protection based on cooperative control of distributed multi‐agent systems and graph theoretical methods. For power system cooperative protection, a new voting method is designed that manages each agent's cooperation according to each protection area. Cooperative protection areas work together and make a wide area of cooperative protection for the specific protection scheme. As the power system configuration varies, the voting management and the wide‐area cooperative protection dynamically change. The proposed protection method decisions are collective, while a centralized master does not exist, and local information is used. A fault detection code and a wide‐area fault detection code are presented for fault detection. The suggested dynamic wide‐area cooperative protection scheme is tested on an IEEE 39‐bus test system. The proposed protection performance is studied as backup protection for distance relays during normal, stable power swings, unstable power swings, and load encroachment conditions.