Multi-agent systems' asset for smart grid applications

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

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Multi-agent systems' asset for smart grid applications. / Rohbogner, Gregor; Hahnel, Ulf J.J.; Benoit, Pascal et al.
in: Computer Science and Information Systems, Jahrgang 10, Nr. 4 SPEC.ISSUE, 10.2013, S. 1799-1822.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

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Rohbogner G, Hahnel UJJ, Benoit P, Fey S. Multi-agent systems' asset for smart grid applications. Computer Science and Information Systems. 2013 Okt;10(4 SPEC.ISSUE):1799-1822. doi: 10.2298/CSIS130224072R

Bibtex

@article{8cb795b115f2459d86d71f8677c44b49,
title = "Multi-agent systems' asset for smart grid applications",
abstract = "Multi-agent systems are a subject of continuously increasing interest in applied technical sciences. Smart grids are one evolving field of application. Numerous smart grid projects with various interpretations of multi-agent systems as new control concept arose in the last decade. Although several theoretical definitions of the term 'agent' exist, there is a lack of practical understanding that might be improved by clearly distinguishing the agent technologies from other state-of-the-art control technologies. In this paper we clarify the differences between controllers, optimizers, learning systems, and agents. Further, we review most recent smart grid projects, and contrast their interpretations with our understanding of agents and multi-agent systems. We point out that multi-agent systems applied in the smart grid can add value when they are understood as fully distributed networks of control entities embedded in dynamic grid environments; able to operate in a cooperative manner and to automatically (re-)configure themselves.",
keywords = "Agent-based control systems, Computer science, Information systems, Multi-agent systems, Power systems, Smart grid, Psychology, Sustainability sciences, Management & Economics",
author = "Gregor Rohbogner and Hahnel, {Ulf J.J.} and Pascal Benoit and Simon Fey",
year = "2013",
month = oct,
doi = "10.2298/CSIS130224072R",
language = "English",
volume = "10",
pages = "1799--1822",
journal = "Computer Science and Information Systems",
issn = "1820-0214",
publisher = "ComSIS Consortium",
number = "4 SPEC.ISSUE",

}

RIS

TY - JOUR

T1 - Multi-agent systems' asset for smart grid applications

AU - Rohbogner, Gregor

AU - Hahnel, Ulf J.J.

AU - Benoit, Pascal

AU - Fey, Simon

PY - 2013/10

Y1 - 2013/10

N2 - Multi-agent systems are a subject of continuously increasing interest in applied technical sciences. Smart grids are one evolving field of application. Numerous smart grid projects with various interpretations of multi-agent systems as new control concept arose in the last decade. Although several theoretical definitions of the term 'agent' exist, there is a lack of practical understanding that might be improved by clearly distinguishing the agent technologies from other state-of-the-art control technologies. In this paper we clarify the differences between controllers, optimizers, learning systems, and agents. Further, we review most recent smart grid projects, and contrast their interpretations with our understanding of agents and multi-agent systems. We point out that multi-agent systems applied in the smart grid can add value when they are understood as fully distributed networks of control entities embedded in dynamic grid environments; able to operate in a cooperative manner and to automatically (re-)configure themselves.

AB - Multi-agent systems are a subject of continuously increasing interest in applied technical sciences. Smart grids are one evolving field of application. Numerous smart grid projects with various interpretations of multi-agent systems as new control concept arose in the last decade. Although several theoretical definitions of the term 'agent' exist, there is a lack of practical understanding that might be improved by clearly distinguishing the agent technologies from other state-of-the-art control technologies. In this paper we clarify the differences between controllers, optimizers, learning systems, and agents. Further, we review most recent smart grid projects, and contrast their interpretations with our understanding of agents and multi-agent systems. We point out that multi-agent systems applied in the smart grid can add value when they are understood as fully distributed networks of control entities embedded in dynamic grid environments; able to operate in a cooperative manner and to automatically (re-)configure themselves.

KW - Agent-based control systems

KW - Computer science

KW - Information systems

KW - Multi-agent systems

KW - Power systems

KW - Smart grid

KW - Psychology

KW - Sustainability sciences, Management & Economics

UR - http://www.scopus.com/inward/record.url?scp=84886794295&partnerID=8YFLogxK

U2 - 10.2298/CSIS130224072R

DO - 10.2298/CSIS130224072R

M3 - Journal articles

AN - SCOPUS:84886794295

VL - 10

SP - 1799

EP - 1822

JO - Computer Science and Information Systems

JF - Computer Science and Information Systems

SN - 1820-0214

IS - 4 SPEC.ISSUE

ER -

DOI

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