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A Multi-Agent Approach for Decentralized Voltage Regulation by Considering Distributed Generators

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AI 2015: Advances in Artificial Intelligence (AI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9457))

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Abstract

Distributed generators (DGs) are considered as significant components to modern micro grids in recent years because they can provide instant and renewable electric power to consumers without using transmission networks. However, the use of DGs may affect the use of voltage regulators in a micro grid because the DGs are usually privately owned and cannot be centrally managed. In this paper, an innovative multi-agent approach is proposed to perform automatic and decentralized controls of distributed electric components in micro grids. Autonomous software agents are employed to make local optimal decisions on voltage regulation by considering multiple objectives and local information; and agent-based communication and collaboration are employed toward a global voltage regulation through dynamic task allocation. The proposed approach contains three layers for representing the micro grid, the multi-agent system and the human-computer interface, and is implemented by using three Java-based packages, i.e. InterPSS, JADE and JUNG respectively.

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Authors and Affiliations

  1. School of Computing and Information Technology, University of Wollongong, Wollongong, Australia

    Fenghui Ren & Minjie Zhang

  2. School of Computer Science and Technology, Dalian University of Technology, Dalian, China

    Chao Yu

Authors
  1. Fenghui Ren
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  2. Minjie Zhang
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  3. Chao Yu
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Corresponding author

Correspondence to Fenghui Ren .

Editor information

Editors and Affiliations

  1. The University of Waikato, Hamilton, New Zealand

    Bernhard Pfahringer

  2. The Australian National University, Canberra, Aust Capital Terr, Australia

    Jochen Renz

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Ren, F., Zhang, M., Yu, C. (2015). A Multi-Agent Approach for Decentralized Voltage Regulation by Considering Distributed Generators. In: Pfahringer, B., Renz, J. (eds) AI 2015: Advances in Artificial Intelligence. AI 2015. Lecture Notes in Computer Science(), vol 9457. Springer, Cham. https://doi.org/10.1007/978-3-319-26350-2_43

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  • DOI: https://doi.org/10.1007/978-3-319-26350-2_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26349-6

  • Online ISBN: 978-3-319-26350-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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