940 resultados para smart systems


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The availability of electricity is fundamental to modern society. It is at the top of the list of critical infrastructures and its interruption can have severe consequences. This highly important system is now evolving to become more reliable, efficient, and clean. This evolving infrastructure has become known as the smart grid; and these future smart grid systems will rely heavily on ICT. This infrastructure will require many servers and due to the nature of the grid, many of these systems will be geographically diverse requiring communication links. At the heart of this ICT infrastructure will be security. At each level of the smart grid from smart metering right through to remote sensing and control networks, security will be a key factor for system design consideration. With an increased number of ICT systems in place the security risk also increases. In this paper the authors discuss the changing nature of security in relation to the smart grid by looking at the move from legacy systems to more modern smart grid systems. The potential planes of attack for future smart grid systems are identified, and the general anatomy of a cyber-attack is presented. The authors then introduce the various threat levels of different types of attack and the mitigation techniques that could be put in place for each. Finally, the authors' introduce a Phasor Measurement Unit (PMU) communication system (operated by the authors) that can be used as a test-bed for some of the proposed future security research.

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Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.

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The key attributes of a smarter power grid include: pervasive interconnection of smart devices; extensive data generation and collection; and rapid reaction to events across a widely dispersed physical infrastructure. Modern telecommunications technologies are being deployed across power systems to support these monitoring and control capabilities. To enable interoperability, several new communications protocols and standards have been developed over the past 10 to 20 years. These continue to be refined, even as new systems are rolled out.

This new hyper-connected communications infrastructure provides an environment rich in sub-systems and physical devices that are attractive to cyber-attackers. Indeed, as smarter grid operations become dependent on interconnectivity, the communications network itself becomes a target. Consequently, we examine cyber-attacks that specifically target communications, particularly state-of-the-art standards and protocols. We further explore approaches and technologies that aim to protect critical communications networks against intrusions, and to monitor for, and detect, intrusions that infiltrate Smart Grid systems.

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Experiences from smart grid cyber-security incidents in the past decade have raised questions on the applicability and effectiveness of security measures and protection mechanisms applied to the grid. In this chapter we focus on the security measures applied under real circumstances in today’s smart grid systems. Beginning from real world example implementations, we first review cyber-security facts that affected the electrical grid, from US blackout incidents, to the Dragonfly cyber-espionage campaign currently focusing on US and European energy firms. Provided a real world setting, we give information related to energy management of a smart grid looking also in the optimization techniques that power control engineers perform into the grid components. We examine the application of various security tools in smart grid systems, such as intrusion detection systems, smart meter authentication and key management using Physical Unclonable Functions, security analytics and resilient control algorithms. Furthermore we present evaluation use cases of security tools applied on smart grid infrastructure test-beds that could be proved important prior to their application in the real grid, describing a smart grid intrusion detection system application and security analytics results. Anticipated experimental results from the use-cases and conclusions about the successful transitions of security measures to real world smart grid operations will be presented at the end of this chapter.

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Under the European Union Renewable Energy Directive each Member State is mandated to ensure that 10% of transport energy (excluding aviation and marine transport) comes from renewable sources by 2020. The Irish Government intends to achieve this target with a number of policies including ensuring that 10% of all vehicles in the transport fleet are powered by electricity by 2020. This paper investigates the impact of the 10% electric vehicle target in Ireland in 2020 using a dynamic programming based long term generation expansion planning model. The model developed optimizes power dispatch using hourly electricity demand curves up to 2020, while incorporating generator characteristics and certain operational requirements such as energy not served and loss of load probability while satisfying constraints on environmental emissions, fuel availability and generator operational and maintenance costs. Two distinct scenarios are analysed based on a peak and off-peak charging regimes in order to simulate the effects of the electric vehicles charging in 2020. The importance and influence of the charging regimes on the amount of energy used and tailgate emissions displaced is then determined.

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Semiconductor-sensitised photocatalysis is a well-established and growing area of research, innovation and commercialisation; the latter being mostly limited to the use of TiO2 as the semiconductor. Most of the work on semiconductor photocatalytic systems uses oxygen as the electron acceptor and explores a wide range of electron donors; such systems can be considered to be examples of oxidative photocatalysis, OP. OP underpins most current examples of commercial self-cleaning materials, such as: glass, tiles, concrete, paint and fabrics. OP, and its myriad of applications, have been reviewed extensively over the years both in this journal and elsewhere. However, the ability of TiO2, and other semiconductor sensitisers, to promote reductive photocatalysis, RP, especially of dyes, is significant and, although less well-known, is of growing importance. In such systems, the source of the electrons is some easily oxidised species, such as glycerol. One recent, significant example of a RP process is with respect to photocatalyst activity indicator inks. paiis, which provide a measure of the activity of a photocatalytic film under test via the rate of change of colour of the dye in the ink coating due to irreversible RP. In contrast, by incorporating the semiconductor sensitiser in the ink, rather than outside it, it is possible to create an effective UV dosimeter, based on RP, which can be used as a sun-burn warning indicator. In the above examples the dye is reduced irreversibly, but when the photocatalyst in an ink is used to reversibly photoreduce a dye, a novel, colourimetric oxygen-sensitive indicator ink can be created, which has commercial potential in the food packaging industry. Finally, if no dye is present in the ink, and the semiconductor photocatalyst-loaded ink film coats an easily reduced substrate, such as a metal oxide film, then it can be used to reduce the latter and so, for example, clean up tarnished steel. The above are examples of smart inks, i.e. inks that are active and provide either dynamic information (such as UV dose or O2 level) or a useful function (such as tarnish removal), and all work via a RP process and are reviewed here

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With the increasing utilization of electric vehicles (EVs), transportation systems and electrical power systems are becoming increasingly coupled. However, the interaction between these two kinds of systems are not well captured, especially from the perspective of transportation systems. This paper studies the reliability of integrated transportation and electrical power system (ITES). A bidirectional EV charging control strategy is first demonstrated to model the interaction between the two systems. Thereafter, a simplified transportation system model is developed, whose high efficiency makes the reliability assessment of the ITES realizable with an acceptable accuracy. Novel transportation system reliability indices are then defined from the view point of EV’s driver. Based on the charging control model and the transportation simulation method, a daily periodic quasi sequential reliability assessment method is proposed for the ITES system. Case studies based on RBTS system demonstrate that bidirectional charging controls of EVs will benefit the reliability of power systems, while decrease the reliability of EVs travelling. Also, the optimal control strategy can be obtained based on the proposed method. Finally, case studies are performed based on a large scale test system to verify the practicability of the proposed method.

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This paper presents a framework for a telecommunications interface which allows data from sensors embedded in Smart Grid applications to reliably archive data in an appropriate time-series database. The challenge in doing so is two-fold, firstly the various formats in which sensor data is represented, secondly the problems of telecoms reliability. A prototype of the authors' framework is detailed which showcases the main features of the framework in a case study featuring Phasor Measurement Units (PMU) as the application. Useful analysis of PMU data is achieved whenever data from multiple locations can be compared on a common time axis. The prototype developed highlights its reliability, extensibility and adoptability; features which are largely deferred from industry standards for data representation to proprietary database solutions. The open source framework presented provides link reliability for any type of Smart Grid sensor and is interoperable with existing proprietary database systems, and open database systems. The features of the authors' framework allow for researchers and developers to focus on the core of their real-time or historical analysis applications, rather than having to spend time interfacing with complex protocols.

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As modern power grids move towards becoming a smart grid, there is an increasing reliance on the data that is transmitted and processed by ICT systems. This reliance introduces new digital attack vectors. Many of the proposed approaches that aim to address this problem largely focus on applying well-known ICT security solutions. However, what is needed are approaches that meet the complex concerns of the smart grid as a cyber-physical system. Furthermore, to support the automatic control loops that exist in a power grid, similarly automatic security and resilience mechanisms are needed that rely on minimal operator intervention. The research proposed in this paper aims to develop a framework that ensures resilient smart grid operation in light of successful cyber-attacks.

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With the development and deployment of IEC 61850 based smart substations, cybersecurity vulnerabilities of supervisory control and data acquisition (SCADA) systems are increasingly emerging. In response to the emergence of cybersecurity vulnerabilities in smart substations, a test-bed is indispensable to enable cybersecurity experimentation. In this paper, a comprehensive and realistic cyber-physical test-bed has been built to investigate potential cybersecurity vulnerabilities and the impact of cyber-attacks on IEC 61850 based smart substations. This test-bed is close to a real production type environment, and has the ability to carry out end-to-end testing of cyber-attacks and physical consequences. A fuzz testing approach is proposed for detecting IEC 61850 based intelligent electronic devices (IEDs) and validated in the proposed test-bed.

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Application of sensor-based technology within activity monitoring systems is becoming a popular technique within the smart environment paradigm. Nevertheless, the use of such an approach generates complex constructs of data, which subsequently requires the use of intricate activity recognition techniques to automatically infer the underlying activity. This paper explores a cluster-based ensemble method as a new solution for the purposes of activity recognition within smart environments. With this approach activities are modelled as collections of clusters built on different subsets of features. A classification process is performed by assigning a new instance to its closest cluster from each collection. Two different sensor data representations have been investigated, namely numeric and binary. Following the evaluation of the proposed methodology it has been demonstrated that the cluster-based ensemble method can be successfully applied as a viable option for activity recognition. Results following exposure to data collected from a range of activities indicated that the ensemble method had the ability to perform with accuracies of 94.2% and 97.5% for numeric and binary data, respectively. These results outperformed a range of single classifiers considered as benchmarks.

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This paper describes a smart grid test bed comprising embedded generation, phasor measurement units (PMUs), and supporting ICT components and infrastructure. The test bed enables the development of a use case focused on a synchronous islanding scenario, where the embedded generation becomes islanded from the mains supply. Due to the provisioned control components, control strategy, and best-practice ICT support infrastructure, the islanded portion of the grid is able to continue to operate in a secure and dependable manner.

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Recently there has been an increase of interest in implementing a new set of home appliances, known as Smart Appliances that integrate Information Technologies, the Internet of Things and the ability of communicating with other devices. While Smart Appliances are characterized as an important milestone on the path to the Smart Grid, by being able to automatically schedule their loads according to a tariff or reflecting the power that is generated using renewable sources, there is not a clear understanding on the impact that the behavior of such devices will have in the comfort levels of users, when they shift their working periods to earlier, or later than, a preset time. Given these considerations, in this work we analyse the results of an assessment survey carried out to a group of Home Appliance users regarding their habits when dealing with these machines and the subjective impact in quality caused by either finishing its programs before or after the time limit set by the user. The results of this work are expected to be used as input for the evaluation of load scheduling algorithms running in energy management systems. © 2014 Springer International Publishing.

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The increasing number of players that operate in power systems leads to a more complex management. In this paper a new multi-agent platform is proposed, which simulates the real operation of power system players. MASGriP – A Multi-Agent Smart Grid Simulation Platform is presented. Several consumer and producer agents are implemented and simulated, considering real characteristics and different goals and actuation strategies. Aggregator entities, such as Virtual Power Players and Curtailment Service Providers are also included. The integration of MASGriP agents in MASCEM (Multi-Agent System for Competitive Electricity Markets) simulator allows the simulation of technical and economical activities of several players. An energy resources management architecture used in microgrids is also explained.

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The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.