19,170 research outputs found
Two decades of condition monitoring methods for power devices
Condition monitoring (CM) of power semiconductor devices enhances converter reliability and customer service. Many studies have investigated the semiconductor devices failure modes, the sensor technologies, and the signal processing techniques to optimize the CM. Furthermore, the improvement of power devices’ CM thanks to the use of the Internet of Things and artificial intelligence technologies is rising in smart grids, transportation electrification, and so on. These technologies will be widespread in the future, where more and more smart techniques and smart sensors will enable a better estimation of the state of the health (SOH) of the devices. Considering the increasing use of power converters, CM is essential as the analysis of the data obtained from multiple sensors enables the prediction of the SOH, which, in turn, enables to properly schedule the maintenance, i.e., accounting for the trade-off between the maintenance cost and the cost and issues due to the device failure. From this perspective, this review paper summarizes past developments and recent advances of the various methods with the aim of describing the current state-of-the-art in CM research
Vulnerability analysis of satellite-based synchronized smart grids monitoring systems
The large-scale deployment of wide-area monitoring systems could play a strategic role in supporting the evolution of traditional power systems toward smarter and self-healing grids. The correct operation of these synchronized monitoring systems requires a common and accurate timing reference usually provided by a satellite-based global positioning system. Although these satellites signals provide timing accuracy that easily exceeds the needs of the power industry, they are extremely vulnerable to radio frequency interference. Consequently, a comprehensive analysis aimed at identifying their potential vulnerabilities is of paramount importance for correct and safe wide-area monitoring system operation. Armed with such a vision, this article presents and discusses the results of an experimental analysis aimed at characterizing the vulnerability of global positioning system based wide-area monitoring systems to external interferences. The article outlines the potential strategies that could be adopted to protect global positioning system receivers from external cyber-attacks and proposes decentralized defense strategies based on self-organizing sensor networks aimed at assuring correct time synchronization in the presence of external attacks
Learning and Management for Internet-of-Things: Accounting for Adaptivity and Scalability
Internet-of-Things (IoT) envisions an intelligent infrastructure of networked
smart devices offering task-specific monitoring and control services. The
unique features of IoT include extreme heterogeneity, massive number of
devices, and unpredictable dynamics partially due to human interaction. These
call for foundational innovations in network design and management. Ideally, it
should allow efficient adaptation to changing environments, and low-cost
implementation scalable to massive number of devices, subject to stringent
latency constraints. To this end, the overarching goal of this paper is to
outline a unified framework for online learning and management policies in IoT
through joint advances in communication, networking, learning, and
optimization. From the network architecture vantage point, the unified
framework leverages a promising fog architecture that enables smart devices to
have proximity access to cloud functionalities at the network edge, along the
cloud-to-things continuum. From the algorithmic perspective, key innovations
target online approaches adaptive to different degrees of nonstationarity in
IoT dynamics, and their scalable model-free implementation under limited
feedback that motivates blind or bandit approaches. The proposed framework
aspires to offer a stepping stone that leads to systematic designs and analysis
of task-specific learning and management schemes for IoT, along with a host of
new research directions to build on.Comment: Submitted on June 15 to Proceeding of IEEE Special Issue on Adaptive
and Scalable Communication Network
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The role of smart sensor networks for voltage monitoring in smart grids
The large-scale deployment of the Smart Grid paradigm will support the evolution of conventional electrical power systems toward active, flexible and self-healing web energy networks composed of distributed and cooperative energy resources. In a Smart Grid platform, distributed voltage monitoring is one of the main issues to address. In this field, the application of traditional hierarchical monitoring paradigms has some disadvantages that could hinder their application in Smart Grids where the constant growth of grid complexity and the need for massive pervasion of Distribution Generation Systems (DGS) require more scalable, more flexible control and regulation paradigms. To try to overcome these challenges, this paper proposes the concept of a decentralized non-hierarchal voltage monitoring architecture based on intelligent and cooperative smart entities. These devices employ traditional sensors to acquire local bus variables and mutually coupled oscillators to assess the main variables describing the global grid state
NILM techniques for intelligent home energy management and ambient assisted living: a review
The ongoing deployment of smart meters and different commercial devices has made electricity disaggregation feasible in buildings and households, based on a single measure of the current and, sometimes, of the voltage. Energy disaggregation is intended to separate the total power consumption into specific appliance loads, which can be achieved by applying Non-Intrusive Load Monitoring (NILM) techniques with a minimum invasion of privacy. NILM techniques are becoming more and more widespread in recent years, as a consequence of the interest companies and consumers have in efficient energy consumption and management. This work presents a detailed review of NILM methods, focusing particularly on recent proposals and their applications, particularly in the areas of Home Energy Management Systems (HEMS) and Ambient Assisted Living (AAL), where the ability to determine the on/off status of certain devices can provide key information for making further decisions. As well as complementing previous reviews on the NILM field and providing a discussion of the applications of NILM in HEMS and AAL, this paper provides guidelines for future research in these topics.Agência financiadora:
Programa Operacional Portugal 2020 and Programa Operacional Regional do Algarve
01/SAICT/2018/39578
Fundação para a Ciência e Tecnologia through IDMEC, under LAETA:
SFRH/BSAB/142998/2018
SFRH/BSAB/142997/2018
UID/EMS/50022/2019
Junta de Comunidades de Castilla-La-Mancha, Spain:
SBPLY/17/180501/000392
Spanish Ministry of Economy, Industry and Competitiveness (SOC-PLC project):
TEC2015-64835-C3-2-R MINECO/FEDERinfo:eu-repo/semantics/publishedVersio
Smart Grid Communications: Overview of Research Challenges, Solutions, and Standardization Activities
Optimization of energy consumption in future intelligent energy networks (or
Smart Grids) will be based on grid-integrated near-real-time communications
between various grid elements in generation, transmission, distribution and
loads. This paper discusses some of the challenges and opportunities of
communications research in the areas of smart grid and smart metering. In
particular, we focus on some of the key communications challenges for realizing
interoperable and future-proof smart grid/metering networks, smart grid
security and privacy, and how some of the existing networking technologies can
be applied to energy management. Finally, we also discuss the coordinated
standardization efforts in Europe to harmonize communications standards and
protocols.Comment: To be published in IEEE Communications Surveys and Tutorial
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