Recent Developments and Challenges on AC Microgrids Fault Detection and Protection Systems–A Review

The protection of AC microgrids (MGs) is an issue of paramount importance to ensure their reliable and safe operation. Designing reliable protection mechanism, however, is not a trivial task, as many practical issues need to be considered. The operation mode of MGs, which can be grid-connected or islanded, employed control strategy and practical limitations of the power electronic converters that are utilized to interface renewable energy sources and the grid, are some of the practical constraints that make fault detection, classification, and coordination in MGs different from legacy grid protection. This article aims to present the state-of-the-art of the latest research and developments, including the challenges and issues in the field of AC MG protection. A broad overview of the available fault detection, fault classification, and fault location techniques for AC MG protection and coordination are presented. Moreover, the available methods are classified, and their advantages and disadvantages are discussed

Advances in fault diagnosis for high-speed railway: A review

The high speed railway (HSR) is a complex system with many subsystems and components. The reliability of its core subsystems is a key consideration in ensuring the safety and operation efficiency of the whole system. As the service time increases, the degradation of these subsystems and components may lead to a range of faults and deteriorate the whole system performance. To ensure the operation safety and to develop reasonable maintenance strategies, fault detection and isolation is an indispensable functionality in high speed railway systems. In this paper, the traction power supply system, bogie system, civil infrastructure system, and control and signaling system of HSR are briefly summarized, and then different fault diagnosis methods for these subsystems are comprehensively reviewed. Finally, some future research topics are discussed

Fault Management in DC Microgrids:A Review of Challenges, Countermeasures, and Future Research Trends

The significant benefits of DC microgrids have instigated extensive efforts to be an alternative network as compared to conventional AC power networks. Although their deployment is ever-growing, multiple challenges still occurred for the protection of DC microgrids to efficiently design, control, and operate the system for the islanded mode and grid-tied mode. Therefore, there are extensive research activities underway to tackle these issues. The challenge arises from the sudden exponential increase in DC fault current, which must be extinguished in the absence of the naturally occurring zero crossings, potentially leading to sustained arcs. This paper presents cut-age and state-of-the-art issues concerning the fault management of DC microgrids. It provides an account of research in areas related to fault management of DC microgrids, including fault detection, location, identification, isolation, and reconfiguration. In each area, a comprehensive review has been carried out to identify the fault management of DC microgrids. Finally, future trends and challenges regarding fault management in DC-microgrids are also discussed

A Multilabel Approach for Fault Detection and Classification of Transmission Lines using Binary Relevance

In Contemporary automation systems, Fault detection and classification of electrical transmission lines in grid systems are given top priority. The broad application of Machine Learning (ML) methods has enabled the substitute of conventional methods of fault identification and classification. These methods are more effective ones that can identify faults early on using a significant quantity of sensory data. So detecting simultaneous failures is difficult in the context of distracting the noise and several faults in the transmission lines. This study contributes by offering a unique way for concurrently detecting and classifying several faults using a multilabel classification approach based on binary relevance classifiers. The proposed binary relevance multilabel detection and classification models’ performances are examined. Under both ideal and problematic circumstances, faults in the dataset are collected. A variety of multilabel fault types detection and classification determines the suggested method’s effectiveness

Measurements, Models, Systems and Design

531 s.

Faults Detection for Power Systems

Non

AI Solutions for MDS: Artificial Intelligence Techniques for Misuse Detection and Localisation in Telecommunication Environments

This report considers the application of Articial Intelligence (AI) techniques to the problem of misuse detection and misuse localisation within telecommunications environments. A broad survey of techniques is provided, that covers inter alia rule based systems, model-based systems, case based reasoning, pattern matching, clustering and feature extraction, articial neural networks, genetic algorithms, arti cial immune systems, agent based systems, data mining and a variety of hybrid approaches. The report then considers the central issue of event correlation, that is at the heart of many misuse detection and localisation systems. The notion of being able to infer misuse by the correlation of individual temporally distributed events within a multiple data stream environment is explored, and a range of techniques, covering model based approaches, `programmed' AI and machine learning paradigms. It is found that, in general, correlation is best achieved via rule based approaches, but that these suffer from a number of drawbacks, such as the difculty of developing and maintaining an appropriate knowledge base, and the lack of ability to generalise from known misuses to new unseen misuses. Two distinct approaches are evident. One attempts to encode knowledge of known misuses, typically within rules, and use this to screen events. This approach cannot generally detect misuses for which it has not been programmed, i.e. it is prone to issuing false negatives. The other attempts to `learn' the features of event patterns that constitute normal behaviour, and, by observing patterns that do not match expected behaviour, detect when a misuse has occurred. This approach is prone to issuing false positives, i.e. inferring misuse from innocent patterns of behaviour that the system was not trained to recognise. Contemporary approaches are seen to favour hybridisation, often combining detection or localisation mechanisms for both abnormal and normal behaviour, the former to capture known cases of misuse, the latter to capture unknown cases. In some systems, these mechanisms even work together to update each other to increase detection rates and lower false positive rates. It is concluded that hybridisation offers the most promising future direction, but that a rule or state based component is likely to remain, being the most natural approach to the correlation of complex events. The challenge, then, is to mitigate the weaknesses of canonical programmed systems such that learning, generalisation and adaptation are more readily facilitated

Fault detection in a three-phase inverter fed circuit: Enhancing the Tripping capability of a UPS circuit breaker using wave shape recognition algorithm

Uninterruptible power supplies (UPS) are electrical devices that protect sensitive loads from power line disturbances such as source side overcurrents caused by overvoltage and power surges. The critical load in a double conversion UPS system is supplied from an invert-er. When overcurrents occur on the load side of double conversion UPS systems, both the UPS system’s inverter and the critical load connected to it stand a high risk of damage. Load side overcurrents due to short circuits, ground faults and motor/transformer start-up are very damaging to power electronic components, electrical equipment and cable connections. There exists circuit breakers on the load side designed to trip when a huge overcurrent occurs, thereby clearing the fault. A circuit breaker is normally sized and installed based on the maxi-mum capacity of the host system and trips when a predetermined overcurrent is recorded within a specific period of time. The UPS system’s inverter has a pre-set current limit value to protect insulated-gate bipolar transistors (IGBTs) from damage. During an overcurrent, invert-ers can supply a fault current whose peak value is limited to the IGBT current limit value. This inverter supplied fault current is not high enough to trip the circuit breaker. After an extended period of overcurrent, UPS internal tripping will be activated and all loads lose power. Opera-tion of the UPS in bypass mode supplies the required fault current but exposes the sensitive load to power line distortions. Therefore, it is desired to always supply the critical load via the inverter. This study targets to design a detection algorithm for short circuits and ground faults with a detection time faster than the UPS system’s internal tripping in order to isolate the faulted ar-ea, when the inverter is supplying the critical load. To achieve this, first, a MATLAB model was designed to aid in preliminary studies of fault detection through analysing the system behaviour. Secondly, literature review was conducted and a fault detection method selected with the help of the MATLAB model. Next, laboratory tests on a real UPS system were carried out and compared to the MATLAB results. Lastly, the detection algorithm was designed, im-plemented and tested on a real double conversion UPS system. The test results indicate that the implemented detection algorithm successfully detects short circuits and ground faults well within the desired time. It also successfully distinguishes short circuits and ground faults from other sources of overcurrents such as overloading and transformer inrush current. Future development of this study includes additional features such as a fault classification method proposed for implementation to improve the UPS debugging process during maintenance. Moreover, the detection algorithm will also be refined and devel-oped further to activate a circuit that discharges a current pulse to increase the fault current fed to the circuit breaker