Active network management using distributed constraint optimisation

Dimitrios Athanasiadis, Stephen McArthur

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

1 Citation (Scopus)

Abstract

A fully distributed intelligence and control philosophy is needed for future flexible grids to facilitate the low carbon transition and the adoption of emerging network technologies. Future grids need scalable network management solutions in order to cope with the increase in uncertainty and complexity. Fundamental research in intelligent systems and network control will deliver the next generation of intelligent electricity network. This paper presents a network management function formalised as a Distributed Constraint Optimization (DCOP) problem, in particular power flow management. DCOP is an approach to negotiation and arbitration within decentralised control systems where conflicting control decisions arise. Furthermore, the problem will be visualized and decomposed as a factor graph which is a graphical presentation of factorization of a global function into a product of local functions. Additionally, a message passing algorithm, the max-sum algorithm, will be applied which can provide almost optimal results for decentralised coordination problems and limits the computation and communication problems.
Original languageEnglish
Title of host publication2013 IEEE Power and Energy Society General Meeting (PES)
Place of PublicationPiscataway, NJ.
PublisherIEEE
Pages1 - 5
Number of pages5
ISBN (Print)9781479913039
DOIs
Publication statusPublished - 2013
Event2013 IEEE Power and Energy Society (PES) General Meeting - Vancouver, Canada
Duration: 22 Jul 201325 Jul 2013

Conference

Conference2013 IEEE Power and Energy Society (PES) General Meeting
CountryCanada
CityVancouver
Period22/07/1325/07/13

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Keywords

  • artificial intelligence
  • DCOP
  • factor graphs
  • max-sum algorithms
  • power flow management

Cite this

Athanasiadis, D., & McArthur, S. (2013). Active network management using distributed constraint optimisation. In 2013 IEEE Power and Energy Society General Meeting (PES) (pp. 1 - 5). Piscataway, NJ.: IEEE. https://doi.org/10.1109/PESMG.2013.6672504