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A Review of Architectures and Concepts for Intelligence in Future Electric Energy Systems
Electric Energy Systems Energy Department, AIT Austrian Institute of Technology, Vienna, Robotics and Adaptive Systems, PROFACTOR Produktionsforschungs GmbH.
Electric Energy Systems Energy Department, AIT Austrian Institute of Technology, Vienna.
Electric Energy Systems Energy Department, AIT Austrian Institute of Technology, Vienna.
Department of Industrial and Information Engineering and Economics, University of L’Aquila.
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2015 (English)In: IEEE transactions on industrial electronics (1982. Print), ISSN 0278-0046, E-ISSN 1557-9948, Vol. 62, no 4, p. 2424-2438Article in journal (Refereed) Published
Abstract [en]

Renewable energy sources are one key enabler to decrease greenhouse gas emissions and to cope with the anthropogenic climate change. Their intermittent behavior and limited storage capabilities present a new challenge to power system operators to maintain power quality and reliability. Additional technical complexity arises from the large number of small distributed generation units and their allocation within the power system. Market liberalization and changing regulatory framework lead to additional organizational complexity. As a result, the design and operation of the future electric energy system have to be redefined. Sophisticated information and communication architectures, automation concepts, and control approaches are necessary in order to manage the higher complexity of so-called smart grids. This paper provides an overview of the state of the art and recent developments enabling higher intelligence in future smart grids. The integration of renewable sources and storage systems into the power grids is analyzed. Energy management and demand response methods and important automation paradigms and domain standards are also reviewed

Place, publisher, year, edition, pages
2015. Vol. 62, no 4, p. 2424-2438
National Category
Computer Sciences
Research subject
Dependable Communication and Computation Systems
Identifiers
URN: urn:nbn:se:ltu:diva-7026DOI: 10.1109/TIE.2014.2361486ISI: 000351406000039Scopus ID: 2-s2.0-84922977838Local ID: 55a966f2-be7e-4cd9-bb87-a62c2c4bb622OAI: oai:DiVA.org:ltu-7026DiVA, id: diva2:979913
Note
Validerad; 2015; Nivå 2; 20150417 (andbra)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved

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Zhabelova, GulnaraVyatkin, Valeriy

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