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A decision support system for smart grid energy management

Sergaki Amalia, Kalaitzakis Kostas

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/27F45D0D-DA40-4E18-AC95-DEBAA4EEAF2B
Έτος 2011
Τύπος Σύντομη Δημοσίευση σε Συνέδριο
Άδεια Χρήσης
Λεπτομέρειες
Βιβλιογραφική Αναφορά A. Sergaki ,K. Kalaitzakis , "A Decision Support System for Smart Grid Energy Management", presented at Proc. 4th Int. Scientific Conf. on Energy and Climate Change, Athens, Greece,2011.
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Περίληψη

With a renewed interest in energy and climate issues, policymakers and industry leaders are recognizing thesignificant potential that the Smart Grid (SG) can play in the future. The SG enables widespread penetrationof new technologies that include smart distribution networks, demand response, increased penetration oflarge-scale renewable distributed generation, plug-in electric vehicles and electricity storage technologies andprovides new information and flexibility to both consumers and providers of electricity. The SG providesreliability, reduced peak demand, more efficient utilization of the available infrastructure and reduced energylosses. Environmental benefits associated with smart grid include a significant reduction in power sectorcarbon emissions.The SG poses many challenges as we migrate from the current grid, toward a new grid withtwo-way power flows, two-way and peer to peer customer interactions, and distributed generation.Centralized decision making and hierarchical SCADA systems have to be replaced by more flexible energymanagement systems (EMS). In addition, the models to be used must be capable of accounting foruncertainty present in the power system due to the intrinsic uncertainty of the renewable sources and also dueto the use of imprecise and vague terms or even the lack of information while stating incorporating criterialike environmental impacts, operation condition history and alternative supply availability. The workpresented in this paper identifies the requirements that lay out the functions and applications of the SG andprovides a framework of knowledge management mechanisms used by the EMS in order to support it.

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