Improved Fault Classification and Localization in Power Transmission Networks Using VAE-Generated Synthetic Data and Machine Learning Algorithms

The reliable operation of power transmission networks depends on the timely detection and localization of faults. Fault classification and localization in electricity transmission networks can be challenging because of the complicated and dynamic nature of the system. In recent years, a variety of machine learning (ML) and deep learning algorithms (DL) have found applications in the enhancement of fault identification and classification within power transmission networks. Yet, the efficacy of these ML architectures is profoundly dependent upon the abundance and quality of the training data. This intellectual explanation introduces an innovative strategy for the classification and pinpointing of faults within power transmission networks. This is achieved through the utilization of variational autoencoders (VAEs) to generate synthetic data, which in turn is harnessed in conjunction with ML algorithms. This approach encompasses the augmentation of the available dataset by infusing it with synthetically generated instances, contributing to a more robust and proficient fault recognition and categorization system. Specifically, we train the VAE on a set of real-world power transmission data and generate synthetic fault data that capture the statistical properties of real-world data. To overcome the difficulty of fault diagnosis methodology in three-phase high voltage transmission networks, a categorical boosting (Cat-Boost) algorithm is proposed in this work. The other standard machine learning algorithms recommended for this study, including Support Vector Machine (SVM), Decision Trees (DT), Random Forest (RF), and K-Nearest Neighbors (KNN), utilizing the customized version of forward feature selection (FFS), were trained using synthetic data generated by a VAE. The results indicate exceptional performance, surpassing current state-of-the-art techniques, in the tasks of fault classification and localization. Notably, our approach achieves a remarkable 99% accuracy in fault classification and an extremely low mean absolute error (MAE) of 0.2 in fault localization. These outcomes represent a notable advancement compared to the most effective existing baseline methods.publishedVersio

Advanced flight control system study

A fly by wire flight control system architecture designed for high reliability includes spare sensor and computer elements to permit safe dispatch with failed elements, thereby reducing unscheduled maintenance. A methodology capable of demonstrating that the architecture does achieve the predicted performance characteristics consists of a hierarchy of activities ranging from analytical calculations of system reliability and formal methods of software verification to iron bird testing followed by flight evaluation. Interfacing this architecture to the Lockheed S-3A aircraft for flight test is discussed. This testbed vehicle can be expanded to support flight experiments in advanced aerodynamics, electromechanical actuators, secondary power systems, flight management, new displays, and air traffic control concepts

Control and Protection of MMC-Based HVDC Systems: A Review

The voltage source converter (VSC) based HVDC (high voltage direct current system) offers the possibility to integrate other renewable energy sources (RES) into the electrical grid, and allows power flow reversal capability. These appealing features of VSC technology led to the further development of multi-terminal direct current (MTDC) systems. MTDC grids provide the possibility of interconnection between conventional power systems and other large-scale offshore sources like wind and solar systems. The modular multilevel converter (MMC) has become a popular technology in the development of the VSC-MTDC system due to its salient features such as modularity and scalability. Although, the employment of MMC converter in the MTDC system improves the overall system performance. However, there are some technical challenges related to its operation, control, modeling and protection that need to be addressed. This paper mainly provides a comprehensive review and investigation of the control and protection of the MMC-based MTDC system. In addition, the issues and challenges associated with the development of the MMC-MTDC system have been discussed in this paper. It majorly covers the control schemes that provide the AC system support and state-of-the-art relaying algorithm/ dc fault detection and location algorithms. Different types of dc fault detection and location algorithms presented in the literature have been reviewed, such as local measurement-based, communication-based, traveling wave-based and artificial intelligence-based. Characteristics of the protection techniques are compared and analyzed in terms of various scenarios such as implementation in CBs, system configuration, selectivity, and robustness. Finally, future challenges and issues regarding the development of the MTDC system have been discussed in detail

Modal Transformation based Fault Location in Radial Distribution Network

This paper introduces the technique of fault distance estimation based on modal transformation and signal processing. The recorded faulted phase currents are applied to the Karrenbauer model transformation and these model component currents are decomposed into detail coefficients by the use of Daubechies wavelet, db6. The fault recorder installed at the terminal of the feeder records different time delays between the modal components. In order to find fault distance, the time delay values and modal components velocity are used in traveling wave theory. This paper compares two different conditions: the first condition does not use a modal transformation and the second condition uses a modal transformation. When using modal transformation conditions, three different coefficient levels (detail coefficient level 1 (D1); the combination of detail coefficient level 1+2 (D1+2) and the combination of detail coefficient level 1+2+3 (D1+2+3) ) are used to estimate the fault distance. Different fault types with different fault locations are created in MATLAB simulation

Modal Transformation based Fault Location in Radial Distribution Network

This paper introduces the technique of fault distance estimation based on modal transformation and signal processing. The recorded faulted phase currents are applied to the Karrenbauer model transformation and these model component currents are decomposed into detail coefficients by the use of Daubechies wavelet, db6. The fault recorder installed at the terminal of the feeder records different time delays between the modal components. In order to find fault distance, the time delay values and modal components velocity are used in traveling wave theory. This paper compares two different conditions: the first condition does not use a modal transformation and the second condition uses a modal transformation. When using modal transformation conditions, three different coefficient levels (detail coefficient level 1 (D1); the combination of detail coefficient level 1+2 (D1+2) and the combination of detail coefficient level 1+2+3 (D1+2+3) ) are used to estimate the fault distance. Different fault types with different fault locations are created in MATLAB simulation

A novel fault let-through energy based fault location for LVDC distribution networks

Low Voltage Direct Current (LVDC) distribution systems have recently been considered as an alternative approach to electrical system infrastructure as they provide the additional flexibility and controllability required to facilitate the integration of more low carbon technologies (LCTs). However, DC protection systems and, more specifically high accuracy DC fault location, have been recognised as a key challenge to facilitating post-fault network maintenance. Most of the existing fault location techniques rely on current derivative or communications-based methods that are either very sensitive to noise, or require a high level of data synchronisation. Fault energy has been recognized as a reliable indicator of more accurate fault location estimations. Therefore, this paper develops a mathematical model for describing fault energy during the transient period of DC faults. The method subsequently proposes a new fault let-through energy based DC fault location working strategy to facilitate post-fault network maintenance. The proposed method does not require data synchronisation regardless of the voltage, current, and the size of the converters connected to the LVDC feeder. The capabilities of the proposed fault location strategy are validated against different faults applied on an LVDC test network in PSCAD/EMTDC and shown to be more reliable and accurate than existing methods

A Decentralized Fault Section Location Method Using Autoencoder and Feature Fusion in Resonant Grounding Distribution Systems

In industrial applications, the existing fault location methods of resonant grounding distribution systems suffer from low accuracy due to excessive dependence on communication, lack of field data, difficulty in artificial feature extraction and threshold setting, etc. To address these problems, this study proposes a decentralized fault section location method, which is implemented by the primary and secondary fusion intelligent switch (PSFIS) with two preloaded algorithms: autoencoder (AE) and backpropagation neural network. The relation between the transient zero-sequence current and the derivative of the transient zero-sequence voltage in each section is analyzed, and its features are extracted adaptively by using AE, without acquiring network parameters or setting thresholds. The current and voltage data are processed locally at PSFISs throughout the whole procedure, making it is insusceptible to communication failure or delay. The feasibility and effectiveness of the approach are investigated in PSCAD/EMTDC and real-time digital simulation system, which is then validated by field data. Compared with other methods, the experiment results indicate that the proposed method performs well in various scenarios with strong robustness to harsh on-site environment and roughness of data

Comparison of Aircraft Models and Integration Schemes for Interval Management in the TRACON

Reusable models of common elements for communication, computation, decision and control in air traffic management are necessary in order to enable simulation, analysis and assurance of emergent properties, such as safety and stability, for a given operational concept. Uncertainties due to faults, such as dropped messages, along with non-linearities and sensor noise are an integral part of these models, and impact emergent system behavior. Flight control algorithms designed using a linearized version of the flight mechanics will exhibit error due to model uncertainty, and may not be stable outside a neighborhood of the given point of linearization. Moreover, the communication mechanism by which the sensed state of an aircraft is fed back to a flight control system (such as an ADS-B message) impacts the overall system behavior; both due to sensor noise as well as dropped messages (vacant samples). Additionally simulation of the flight controller system can exhibit further numerical instability, due to selection of the integration scheme and approximations made in the flight dynamics. We examine the theoretical and numerical stability of a speed controller under the Euler and Runge-Kutta schemes of integration, for the Maintain phase for a Mid-Term (2035-2045) Interval Management (IM) Operational Concept for descent and landing operations. We model uncertainties in communication due to missed ADS-B messages by vacant samples in the integration schemes, and compare the emergent behavior of the system, in terms of stability, via the boundedness of the final system state. Any bound on the errors incurred by these uncertainties will play an essential part in a composable assurance argument required for real-time, flight-deck guidance and control systems,. Thus, we believe that the creation of reusable models, which possess property guarantees, such as safety and stability, is an innovative and essential requirement to assessing the emergent properties of novel airspace concepts of operation

The half-sine method: a new accurate location method based on wavelet transform for transmission-line protection from single-ended measurements

In this work, a new and accurate method based on the wavelet transform is proposed for fault location in transmission-line systems. The proposed wavelet method consists of the analysis of the transient signal measured at a single end of the transmission line. Aerial current modes are used, and zero modes are included in the fault-detection scheme for low fault-inception angles. The fault distance is evaluated using the wavelet modulus maxima technique and a method based on the response to a half-sine voltage is proposed to overcome drawbacks arising from the limited sampling frequency and low fault-inception angle. The fault distance is calculated using the difference between the time when a 100 kHz half-sine signal is sent and the time when the derivative signal is received. The proposed algorithm is tested considering harmonic distortion and varying fault resistance, ground resistivity, location and inception angle. The high accuracy of the proposed algorithm is obtained even for faults close to the bus and low inception angle

Synchrophasor Assisted Efficient Fault Location Techniques In An Active Distribution Network

Reliability of an electrical system can be improved by an efficient fault location identification for the fast repair and remedial actions. This scenario changes when there are large penetrations of distributed generation (DG) which makes the distribution system an active distribution system. An efficient use of synchrophasors in the distribution network is studied with bidirectional power flow, harmonics and low angle difference consideration which are not prevalent in a transmission network. A synchrophasor estimation algorithm for the P class PMU is developed and applied to identify efficient fault location. A fault location technique using two ended synchronized measurement is derived from the principle of transmission line settings to work in a distribution network which is independent of line parameters. The distribution systems have less line length, harmonics and different sized line conductors, which affects the sensitivity of the synchronized measurements, Total Vector Error (TVE) and threshold for angular separation between different points in the network. A new signal processing method based on Discrete Fourier Transform (DFT) is utilized to work in a distribution network as specified in IEEE C37.118 (2011) standard for synchrophasor. A specific P and M classes of synchrophasor measurements are defined in the standard. A tradeoff between fast acting P class and detailed measurement M class is sought to work specifically in the distribution system settings which is subjected to large amount of penetrations from the renewable energy