7,601 research outputs found

    Smart grid architecture for rural distribution networks: application to a Spanish pilot network

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    This paper presents a novel architecture for rural distribution grids. This architecture is designed to modernize traditional rural networks into new Smart Grid ones. The architecture tackles innovation actions on both the power plane and the management plane of the system. In the power plane, the architecture focuses on exploiting the synergies between telecommunications and innovative technologies based on power electronics managing low scale electrical storage. In the management plane, a decentralized management system is proposed based on the addition of two new agents assisting the typical Supervisory Control And Data Acquisition (SCADA) system of distribution system operators. Altogether, the proposed architecture enables operators to use more effectively—in an automated and decentralized way—weak rural distribution systems, increasing the capability to integrate new distributed energy resources. This architecture is being implemented in a real Pilot Network located in Spain, in the frame of the European Smart Rural Grid project. The paper also includes a study case showing one of the potentialities of one of the principal technologies developed in the project and underpinning the realization of the new architecture: the so-called Intelligent Distribution Power Router.Postprint (published version

    Towards Distributed and Adaptive Detection and Localisation of Network Faults

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    We present a statistical probing-approach to distributed fault-detection in networked systems, based on autonomous configuration of algorithm parameters. Statistical modelling is used for detection and localisation of network faults. A detected fault is isolated to a node or link by collaborative fault-localisation. From local measurements obtained through probing between nodes, probe response delay and packet drop are modelled via parameter estimation for each link. Estimated model parameters are used for autonomous configuration of algorithm parameters, related to probe intervals and detection mechanisms. Expected fault-detection performance is formulated as a cost instead of specific parameter values, significantly reducing configuration efforts in a distributed system. The benefit offered by using our algorithm is fault-detection with increased certainty based on local measurements, compared to other methods not taking observed network conditions into account. We investigate the algorithm performance for varying user parameters and failure conditions. The simulation results indicate that more than 95 % of the generated faults can be detected with few false alarms. At least 80 % of the link faults and 65 % of the node faults are correctly localised. The performance can be improved by parameter adjustments and by using alternative paths for communication of algorithm control messages

    Applied sensor fault detection, identification and data reconstruction based on PCA and SOMNN for industrial systems

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    The paper presents two readily implementable approaches for Sensor Fault Detection, Identification (SFD/I) and faulted sensor data reconstruction in complex systems, in real-time. Specifically, Principal Component Analysis (PCA) and Self-Organizing Map Neural Networks (SOMNNs) are demonstrated for use on industrial turbine systems. In the first approach, Squared Prediction Error (SPE) based on the PCA residual space is used for SFD. SPE contribution plot is employed for SFI. A missing value approach from an extension of PCA is applied for faulted sensor data reconstruction. In the second approach, SFD is performed by SOMNN based Estimation Error (EE), and SFI is achieved by EE contribution plot. Data reconstruction is based on an extension of the SOMNN algorithm. The results are compared in each examining stage. The validation of both approaches is demonstrated through experimental data during the commissioning of an industrial 15MW turbine

    Data Integrity Protection For Security in Industrial Networks

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    Modern industrial systems are increasingly based on computer networks. Network- based control systems connect the devices at the field level of industrial environments together and to the devices at the upper levels for monitoring, configuration and management purposes. Contrary to traditional industrial networks which axe con­ sidered stand-alone and proprietary networks, modern industrial networks are highly connected systems which use open protocols and standards at different levels. This new structure of industrial systems has made them vulnerable to security attacks. Among various security needs of computer networks, data integrity protection is the major issue in industrial networks. Any unauthorized modification of information during transmission could result in significant damages in industrial environments. In this thesis, the security needs of industrial environments are considered first. The need for security in industrial systems, challenges of security in these systems and security status of protocols used in industrial networks are presented. Furthermore, the hardware implementation of the Secure Hash Algorithm (SHA) which is used in security protocols for data integrity protection is the main focus of this thesis. A scheme has been proposed for the implementation of the SHA-1 and SHA-512 hash functions on FPGAs with fault detection capability. The proposed scheme is based on time redundancy and pipelining and is capable of detecting permanent as well as transient faults. The implementation results of the proposed scheme on Xilinx FPGAs show small area and timing overhead compared to the original implementation without fault detection. Moreover, the implementation of SHA-1 and SHA-512 on Wireless Sensor Boards has been presented taking into account their memory usage and execution time. There is an improvement in the execution time of the proposed implementation compared to the previous works

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

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    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

    Web Supervision System of a Freight Elevator

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    Nowadays, automation and industrial control is an area in which there are innovations ev- ery day in terms of process digitalization, equipment interconnection and human-machine interaction, which results in a constant learning and adaptation to new technologies and methodologies developed. With this comes the responsibility to keep systems robust and prepared for eventual failures, while moving towards an increasing dependence on remote communication between different controllers and different processes. This fact leads to the need to create supervision and monitoring tools capable of detecting and transmitting existing failures, while ensuring that the system continues to operate with the same stability and performance. Therefore, in this work it is proposed the development of a supervisory tool based on industrial automation that has a fault detection component and a human-machine interface in order to incorporate all the essential features of an industrial supervisor. Using industrial programming languages for Programmable Logic Controllers, it was possible to develop an algorithm that is based on inference mechanisms to identify potential faults in the system, which are then transmitted to the user in an interface that can be accessed either locally or remotely via the Web.Nos dias de hoje, a automação e controlo industrial é uma área onde existe todos os dias inovações ao nível da digitalização de processos, da interconexão de equipamentos e na interação Homem-máquina, o que resulta numa constante aprendizagem e adaptação às novas tecnologias e metodologias desenvolvidas. Com isto, vem a responsabilidade de manter os sistemas robustos e preparados para eventuais falhas, ao mesmo tempo que se avança no sentido da cada vez maior dependência da comunicação remota entre diferentes controladores e diferentes processos. Este facto leva a que tenham de ser criadas ferramentas de supervisão e monitorização capazes de detetar e transmitir as falhas existentes, enquanto se garante que o sistema continua em funcionamento garantindo a mesma estabilidade e performance. Assim, neste trabalho é proposto o desenvolvimento de uma ferramenta de supervisão baseada em automação industrial que possua uma componente de deteção de falhas e uma interface Homem-máquina de forma a incorporar todas as funcionalidades essenciais de um supervisor industrial. Recorrendo a linguagens de programação industrial para controladores lógicos programáveis, foi possível desenvolver um algoritmo que se baseia em mecanismos de inferência para identificar potenciais avarias no sistema que são posteriormente transmitidas ao utilizador numa interface que pode ser acedida quer localmente, quer remotamente via Web

    Assessing and augmenting SCADA cyber security: a survey of techniques

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    SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability
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