Communication overlays and agents for dependable smart power grids

Labeeuw, Wouter; Vandael, Stijn; Beitollahi, Hakem; Craemer, Klaas De; Duan, Rui; Qui, Zhifeng; Ramaswamy, Parvathy Chittur; Meerssche, Bert Vande; Vervenne, Isabelle; Belmans, Ronnie

doi:10.1109/cris.2010.5617536

Cited by 24 publications

(7 citation statements)

References 24 publications

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“…In order to facilitate optimization and accelerate computation-time, we propose a layering into distinct control levels, which allow for parallel optimization and processing [19]. At the lowest level, the smart meter measurements of a single home are aggregated and processed.…”

Section: Structure Of the Simulation Frameworkmentioning

confidence: 99%

A smart grid simulation framework for electricity trading

Angstmann

Bracher

Bhat

et al. 2013

2013 10th IEEE INTERNATIONAL CONFERENCE ON NETWORKING, SENSING AND CONTROL (ICNSC)

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In this paper we present our evolving work on developing an interactive simulation-framework for electricity trading in Smart Grids. This simulation framework is designed to enable real-time pricing, demand-side management, and distributed generation. A modular simulation architecture is proposed to address communication challenges and to allow efficient management. The simulator framework adopts a segregation of concerns design approach to allow for effective sand boxing and localization of concerns at the appropriate levels while allowing for structured information flows between the various simulator levels. For example, the control unit on the customer-level accounts for different preferences and behavioral patterns of consumers.

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Section: Structure Of the Simulation Frameworkmentioning

confidence: 99%

A smart grid simulation framework for electricity trading

Angstmann

Bracher

Bhat

et al. 2013

2013 10th IEEE INTERNATIONAL CONFERENCE ON NETWORKING, SENSING AND CONTROL (ICNSC)

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“…traditional methods. For example, multi-agent methods have been considered for managing various aspects of electrical networks, including user demand [3,4,9] and infrastructure security [2].…”

Section: Introductionmentioning

confidence: 99%

Using mobile agents and overlay networks to secure electrical networks

Dawes

Prosser

Fulp

et al. 2013

Proceedings of the Eighth Annual Cyber Security and Information Intelligence Research Workshop

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The use of wandering, mobile agents can provide a robust approach for managing, monitoring, and securing electrical distribution networks. However, the topological structure of an electrical network can affect the agents' ability to monitor the network. For example, if the multi-agent system relies on a regular inspection rate (on average, points of interest are inspected with equal frequency), then locations that are not well connected within the network will on average be inspected less frequently. This results in lower observability into network operations and it also allows issues, either simple faults or adversarial actions, to persist longer in the network before they can be identified and addressed.This paper discusses creation and use of overlay networks that create a virtual grid graph that can provide faster coverage and a more uniform average agent sampling rate. Using overlays, agents wander a virtual neighborhood consisting of points of interest that are interconnected in a regular fashion (each point has the same number of neighbors). Experimental results show that using an overlay can often provide better network coverage and a uniform inspection rate, which can improve cyber security by providing a faster detection of threats.

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“…Although in the existing grid, power is generated and distributed by the utility companies with very less interaction with the consumers. However, the modern grid is still largely based on the existing grid [26,27]. Some of the other benefits of the smart grid are summarized in Fig.…”

Section: The Smart Gridsmentioning

confidence: 99%

Recent advances of the signal processing techniques in future smart grids

Uddin

Ahmad

Qamar

et al. 2018

Hum. Cent. Comput. Inf. Sci.

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IntroductionSmart grid is a network of electric supply that manages power demand in reliable and economic manner by detecting and reacting to local changes in usage. The infrastructure comprises of smart meters, appliances, and resources with a combination of modern technologies like, control, power, instrumentation, and communication. In such a complex scenario, signal processing techniques are essential to understand, plan, design and operate the complex future smart electronic grids [1]. In addition to this, signal processing has wide variety of applications and is becoming an important tool for electric power system analysis. This is due to the fact that measurements retrieved from numerous locations of the grid can be used for data analysis. These measurements can also be used for a variety of issues such as voltage control, power quality and reliability, power system and equipment diagnostics, power system control and protection, etc [2][3][4][5][6].Power quality is one of the main issue of the smart grid research where voltage, current and frequency deviations in the power system are the main concerns of the system operator [7]. The characterization of the incompatibilities caused by these deviations requires an understanding of their principal cause. Other possible aspects that need inspection are the efficient representation of the voltage and current variations in various electrical Abstract Smart grid is an emerging research field of the current decade. The distinguished features of the smart grid are monitoring capability with data integration, advanced analysis to support system control, enhanced power security and effective communication to meet the power demand. Efficient energy consumption and minimum costs are also included in the prodigious features of smart grid. The smart grid implementation requires intelligent interaction between the power generating and consuming devices that can be achieved by installing devices capable of processing data and communicating it to various parts of the grid. The efficiency of these devices is greatly dependent on the selection and implementation of the advance digital signal processing techniques. This paper provides a comprehensive survey on the applications of signal processing techniques in smart grids, plus the challenges and shortcomings of these techniques. Furthermore, this paper also outlines some future research directions related to applications of signal processing in smart grids. Uddin et al. Hum. Cent. Comput. Inf. Sci. (2018) Page 2 of 15 Uddin et al. Hum. Cent. Comput. Inf. Sci. (2018) 8:2 equipment. Moreover, the signal processing of the power patterns leads to better understanding the behavior of these equipment. Continuous monitoring is also required to capture various events and variations. To meet future demands, methods and techniques must be developed to explore the full range of signals derived from the complex interaction between suppliers, consumers and network operators [8]. REVIEWA smart grid performs measurement, monitoring ...

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Communication overlays and agents for dependable smart power grids

Cited by 24 publications

References 24 publications

A smart grid simulation framework for electricity trading

A smart grid simulation framework for electricity trading

Using mobile agents and overlay networks to secure electrical networks

Recent advances of the signal processing techniques in future smart grids

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