31 research outputs found

    Edge intelligence in smart grids : a survey on architectures, offloading models, cyber security measures, and challenges

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    The rapid development of new information and communication technologies (ICTs) and the deployment of advanced Internet of Things (IoT)-based devices has led to the study and implementation of edge computing technologies in smart grid (SG) systems. In addition, substantial work has been expended in the literature to incorporate artificial intelligence (AI) techniques into edge computing, resulting in the promising concept of edge intelligence (EI). Consequently, in this article, we provide an overview of the current state-of-the-art in terms of EI-based SG adoption from a range of angles, including architectures, computation offloading, and cybersecurity c oncerns. The basic objectives of this article are fourfold. To begin, we discuss EI and SGs separately. Then we highlight contemporary concepts closely related to edge computing, fundamental characteristics, and essential enabling technologies from an EI perspective. Additionally, we discuss how the use of AI has aided in optimizing the performance of edge computing. We have emphasized the important enabling technologies and applications of SGs from the perspective of EI-based SGs. Second, we explore both general edge computing and architectures based on EI from the perspective of SGs. Thirdly, two basic questions about computation offloading are discussed: what is computation offloading and why do we need it? Additionally, we divided the primary articles into two categories based on the number of users included in the model, either a single user or a multiple user instance. Finally, we review the cybersecurity threats with edge computing and the methods used to mitigate them in SGs. Therefore, this survey comes to the conclusion that most of the viable architectures for EI in smart grids often consist of three layers: device, edge, and cloud. In addition, it is crucial that computation offloading techniques must be framed as optimization problems and addressed effectively in order to increase system performance. This article typically intends to serve as a primer for emerging and interested scholars concerned with the study of EI in SGs.The Council for Scientific and Industrial Research (CSIR).https://www.mdpi.com/journal/jsanElectrical, Electronic and Computer Engineerin

    From grids to clouds: recap on challenges and solutions

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    Grid Computing is a set of resources; the separate computational power of these resources has combination to execute a huge task. Usually, in a Computational Grid environment, the main resource is the Central Processing Unit (CPU), mostly used in research fields that demand high computational power to perform massive and complicated calculations. Cloud Computing is a promising computing pattern which offers facilities and common resources on demand over the Web. The implementation of cloud computing applications has high priority, especially in the modern world, for example in providing adequate funding for social services and purchasing programs. In this paper, we discuss the implementation of cloud computing over a Smart Grid: reliable, guaranteed and efficient with low cost, it is expected to offer Long Term Evolution (LTE). This allows larger pieces of the spectrum, or bands, to be used, with greater coverage and less latency. The third technology is the Vehicular Network, an important research area because of its unique features and potential applications. In this survey, we present an overview of the smart grid, LTE and vehicular network integrated with cloud computing. We also highlight the open issues and research directions in implementing these technologies with cloud computing in terms of energy and information management for smart grids; applying cloud computing platforms for 4G networks to achieve specific criteria; and finally architectural formation, privacy and security for vehicular cloud computing

    Smart Metering Technology and Services

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    Global energy context has become more and more complex in the last decades; the raising prices of fuels together with economic crisis, new international environmental and energy policies that are forcing companies. Nowadays, as we approach the problem of global warming and climate changes, smart metering technology has an effective use and is crucial for reaching the 2020 energy efficiency and renewable energy targets as a future for smart grids. The environmental targets are modifying the shape of the electricity sectors in the next century. The smart technologies and demand side management are the key features of the future of the electricity sectors. The target challenges are coupling the innovative smart metering services with the smart meters technologies, and the consumers' behaviour should interact with new technologies and polices. The book looks for the future of the electricity demand and the challenges posed by climate changes by using the smart meters technologies and smart meters services. The book is written by leaders from academia and industry experts who are handling the smart meters technologies, infrastructure, protocols, economics, policies and regulations. It provides a promising aspect of the future of the electricity demand. This book is intended for academics and engineers who are working in universities, research institutes, utilities and industry sectors wishing to enhance their idea and get new information about the smart meters

    Data-Intensive Computing in Smart Microgrids

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    Microgrids have recently emerged as the building block of a smart grid, combining distributed renewable energy sources, energy storage devices, and load management in order to improve power system reliability, enhance sustainable development, and reduce carbon emissions. At the same time, rapid advancements in sensor and metering technologies, wireless and network communication, as well as cloud and fog computing are leading to the collection and accumulation of large amounts of data (e.g., device status data, energy generation data, consumption data). The application of big data analysis techniques (e.g., forecasting, classification, clustering) on such data can optimize the power generation and operation in real time by accurately predicting electricity demands, discovering electricity consumption patterns, and developing dynamic pricing mechanisms. An efficient and intelligent analysis of the data will enable smart microgrids to detect and recover from failures quickly, respond to electricity demand swiftly, supply more reliable and economical energy, and enable customers to have more control over their energy use. Overall, data-intensive analytics can provide effective and efficient decision support for all of the producers, operators, customers, and regulators in smart microgrids, in order to achieve holistic smart energy management, including energy generation, transmission, distribution, and demand-side management. This book contains an assortment of relevant novel research contributions that provide real-world applications of data-intensive analytics in smart grids and contribute to the dissemination of new ideas in this area

    Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts-Volume II

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    The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications, such as hybrid and microgrid power systems based on the Energy Internet, Blockchain technology, and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above

    What Ukraine Taught NATO about Hybrid Warfare

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    Russia’s invasion of Ukraine in 2022 forced the United States and its NATO partners to be confronted with the impact of hybrid warfare far beyond the battlefield. Targeting Europe’s energy security, Russia’s malign influence campaigns and malicious cyber intrusions are affecting global gas prices, driving up food costs, disrupting supply chains and grids, and testing US and Allied military mobility. This study examines how hybrid warfare is being used by NATO’s adversaries, what vulnerabilities in energy security exist across the Alliance, and what mitigation strategies are available to the member states. Cyberattacks targeting the renewable energy landscape during Europe’s green transition are increasing, making it urgent that new tools are developed to protect these emerging technologies. No less significant are the cyber and information operations targeting energy security in Eastern Europe as it seeks to become independent from Russia. Economic coercion is being used against Western and Central Europe to stop gas from flowing. China’s malign investments in Southern and Mediterranean Europe are enabling Beijing to control several NATO member states’ critical energy infrastructure at a critical moment in the global balance of power. What Ukraine Taught NATO about Hybrid Warfare will be an important reference for NATO officials and US installations operating in the European theater.https://press.armywarcollege.edu/monographs/1952/thumbnail.jp

    Smart Grid Metering Networks: A Survey on Security, Privacy and Open Research Issues

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    Smart grid (SG) networks are newly upgraded networks of connected objects that greatly improve reliability, efficiency and sustainability of the traditional energy infrastructure. In this respect, the smart metering infrastructure (SMI) plays an important role in controlling, monitoring and managing multiple domains in the SG. Despite the salient features of SMI, security and privacy issues have been under debate because of the large number of heterogeneous devices that are anticipated to be coordinated through public communication networks. This survey paper shows a brief overview of real cyber attack incidents in traditional energy networks and those targeting the smart metering network. Specifically, we present a threat taxonomy considering: (i) threats in system-level security, (ii) threats and/or theft of services, and (iii) threats to privacy. Based on the presented threats, we derive a set of security and privacy requirements for SG metering networks. Furthermore, we discuss various schemes that have been proposed to address these threats, considering the pros and cons of each. Finally, we investigate the open research issues to shed new light on future research directions in smart grid metering networks

    Algoritmos de optimización basados en capacidad y cobertura de redes inalámbricas para la infraestructura de medición avanzada de energía eléctrica

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    The advanced metering infrastructure AMI increasingly takes strength and domain in the world of smart grids, offering numerous applications in different fields: to save human lives, public and private property, to provide an automated environment and comfort for users such networks, etcetera. In this context, smart metering has a major role, and the optimal sizing of a network for it even more, so this paper presents a detailed degree of analysis optimization methods regarding how to group items and It proposes a comparison clustering algorithms in order to determine the most efficient algorithm to cover the capacity of link with smart meters - characteristic of each AP (Access Point) - and coverage - characteristic of each communication standard-, for a smart meters network based on wireless communication standard WiFi. As a result of this analysis it is to obtain the characteristics of each method analyzed under the same conditions both coverage and capacity expressed through graphics and establish the respective conclusions. That is why this research will focus on defining, modeling and simulation methods using K-means clustering, K-medoids and ILP (Integer Linear Programming) expressed as mathematical algorithms in a (500) smart meters network in an Urban residential area which we will call users, considering each method restrictions and objective functions of the network, ensuring a coverage rate of 100% of users located in clusters (groups) and thus providing an optimal solution in terms of time, fewer groups, and equitable distribution of smart meters in the different groups.La infraestructura de medición avanzada AMI toma cada vez con mayor fuerza, dominio en el mundo de las redes inteligentes, brindando numerosas aplicaciones en diferentes campos: para salvar vidas humanas, propiedad pública y privada, para ofrecer un ambiente automatizado y de confort para los usuarios de dichas redes, entre otras. En este ámbito, la medición inteligente tiene un rol trascendental, y el dimensionamiento óptimo de una red para la misma aún más, por lo que el presente trabajo de titulación presenta un análisis detallado sobre métodos de optimización en cuanto a la forma de agrupar ítems y propone una comparación entre algoritmos de agrupación con el fin de determinar el método más eficiente para cubrir tanto en capacidad de enlazar medidores inteligentes - característica propia de cada AP (Access Point)- como en la cobertura - característica propia de cada estándar de comunicación, para una red de medidores inteligentes planteada basada en el estándar de comunicación Wifi. Como consecuencia de este análisis se pretende obtener las características de cada método analizados en las mismas condiciones tanto de cobertura como de capacidad expresadas mediante gráficas y establecer las conclusiones respectivas. Es por esto que esta investigación se centrará en definir, modelar y simular mediante los métodos de agrupación k-means, k-medoids e ILP (Programación Lineal Entera por sus siglas en inglés) expresados como algoritmos matemáticos en una red de quinientos (500) medidores inteligentes en un área residencial urbana a los cuales denominaremos usuarios, teniendo presente para cada método las restricciones y funciones objetivo de dicha red, garantizando un índice de cobertura del 100% de usuarios ubicados en los clústeres (agrupaciones) y de esta manera brindando una solución óptima en cuanto a tiempo, menor número de agrupaciones, y distribución equitativa de medidores en los diferentes grupos

    A Heterogeneous Communications Network for Smart Grid by Using the Cost Functions

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    Smart Grids (SG) is an intelligent power grid in which the different SG node types with different communication requirements communicates different types of information with Control Stations (CS). Radio Access Technologies (RATs) due to its advantages are considered as the main access method to be used in order to have bidirectional data transferring between different node types and CS. Besides, spectrum is a rare source and its demand is increasing significantly. Elaborating a heterogeneous in order to fulfill different SG node types communication requirements effectively, is a challenging issue. To find a method to define desirability value of different RAT to support certain node types based on fitness degree between RAT communication characteristics and node type communication requirements is an appropriate solution. This method is implemented by using a comprehensive Cost Function (CF) including a communication CF (CCF) in combination with Energy CF (ECF). The Key Point Indicators which are used in the CCF are SG node type communication requirements. The existing trade of between Eb/N0 and spectral efficiency is considered as ECF. Based on the achieved CCF and ECF and their tradeoffs, SG node types are assigned to different RATs. The proposed assigning method is sensitive to the SG node types densities. The numerical results are achieved by using MATLAB simulation. The other different outcomes of the research output such as cognitive radio in SG and collectors effect number on data aggregation are discussed as well

    Mise en oeuvre d’une plateforme de gestion et de dissémination des connaissances pour des réseaux autonomiques

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    The growth of the Internet, the emergence of new needs expressed by the advent of smart devices ( smartphones, touchpads , etc. ) and the development of new underlying applications induce many changes in the use of information technology in our everyday life and in all sectors. This new use that match new needs required to rethink the foundation of the network architecture itself, which has resulted in the emergence of new concepts based on a "use-centeric" view instead of a "network-centric" view. In fact, the control mechanisms of the transmission network must not only exploit the information on data, control and management planes, but also the knowledge acquired or learned by inductive or deductive inference on the current state of the network (traffic, resources, the rendering of the application, etc.) to accelerate decision making by the control elements of the network. This thesis is dealing with this latter aspect, which makes it consistent with work done on autonomic networks. It is about conceiving and implementing methods for the management, distribution and exploitation of knowledge necessary for the proper functioning of the transmission network. The knowledge plane that we implemented is based on both the idea of developing a management within an adaptive hierarchical structure where only some selected nodes are responsible for the dissemination of knowledge and the idea of linking these nodes through a spanning set of specialized networks to facilitate the exploitation of this knowledge. Compared to traditionally used platforms, the one developed in this thesis clearly shows the interest of the developed algorithms in terms of access time, distribution and load sharing between the control nodes for knowledge management. For validation purposes, our platform was tested on two application examples : Cloud computing and smart gridsLa croissance du réseau Internet, l'émergence de nouveaux besoins par l'avènement des terminaux dits intelligents (smartphones, tablettes tactiles, etc.) et l'apparition de nouvelles applications sous-jacentes induisent de nombreuses mutations dans l'usage de plus en plus massif des technologies de l'information dans notre vie quotidienne et dans tous les secteurs d'activités. Ces nouveaux usages ont nécessité de repenser le fondement même de l'architecture réseau qui a eu pour conséquence l'émergence de nouveaux concepts basés sur une vue "centrée sur l'usage" en lieu et place d'une vue "centrée sur le réseau". De fait, les mécanismes de contrôle du réseau de transport doivent non seulement exploiter les informations relatives aux plans de données, de contrôle et de gestion, mais aussi les connaissances, acquises ou apprises par inférence déductive ou inductive, sur l'état courant du réseau (trafic, ressources, rendu de l'application, etc.) de manière à accélérer la prise de décision par les éléments de contrôle du réseau. Les travaux faits dans le cadre de cette thèse concernent ce dernier aspect et rejoignent plus généralement ceux tournés sur les réseaux autonomiques. Il s'agit dans cette thèse de mettre en oeuvre des méthodes relatives à la gestion, à la distribution et à l'exploitation des connaissances nécessaires au bon fonctionnement du réseau de transport. Le plan de connaissances mis en oeuvre ici se base à la fois sur l'idée de développer une gestion au sein d'une structure hiérarchisée et adaptative où seuls certains noeuds sélectionnés sont en charge de la dissémination des connaissances et l'idée de relier ces noeuds au travers d'un ensemble de réseaux couvrants spécialisés permettant de faciliter l'exploitation de ces connaissances. Comparée aux plateformes traditionnellement utilisées, celle développée dans le cadre de cette thèse montre clairement l'intérêt des algorithmes élaborés au regard des temps d'accès, de distribution et de partage de charge entre les noeuds de contrôle pour la gestion des connaissances. A des fins de validation, cette plateforme a été utilisée dans deux exemples d'application: le Cloud computing et les smartgrid
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