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Multi-Agent Systems Applied to Power Loss Minimization in Distribution-Level Smart Grid with Dynamic Load Variation
Federal University of Para, Brazil.
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.ORCID iD: 0000-0003-3014-5609
Federal University of Para, Brazil.
2017 (English)In: 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings, IEEE, 2017, p. 217-224, article id 7969316Conference paper, Published paper (Refereed)
Abstract [en]

Modern distribution system are expected to provide new features such as taking advantage of Cyber-Physical Systems (CPS) - new equipment and devices embedded with sensors, network communication, and computational intelligence techniques to provide increased system performance and power quality. Among the performance improvement, the reduction of electrical losses is an important quality factor which is associated with energy efficiency. This paper presents a method based on Multi-agent Systems (MAS) that manages topology changes by switching operations to improve the system performance in dynamic scenario, where the power demand varies throughout the day. Experiments were performed allocating three different load consumer profiles (residential, commercial, and industrial) in two test systems with 12-bus and 16-bus, creating several scenarios. The agents were deployed in a set of small-sized single-board computers with low computational power to mimic CPS. The simulations has shown the success of the method on managing the decision making among different agents to provide the joint effort to manage the loss reduction on the network.

Place, publisher, year, edition, pages
IEEE, 2017. p. 217-224, article id 7969316
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-208198DOI: 10.1109/CEC.2017.7969316ISI: 000426929700029Scopus ID: 2-s2.0-85027835238ISBN: 9781509046010 (print)OAI: oai:DiVA.org:kth-208198DiVA, id: diva2:1104873
Conference
2017 IEEE Congress on Evolutionary Computation, CEC 2017, Donostia-San Sebastian, Spain, 5 June 2017 through 8 June 2017
Note

QC 20170831

Available from: 2017-06-02 Created: 2017-06-02 Last updated: 2024-03-15Bibliographically approved

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Nordström, Lars

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf