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International Symposium on Neural Networks

ISNN 2009: Advances in Neural Networks – ISNN 2009 pp 165–171Cite as

Application of Artificial Intelligence Technique in Distributed Generation System

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5552))

Abstract

This paper gives a brief description of current situation of distributed generation system, and points out that microgrid can run in two kinds of operation modes. The key problems which need to be cautiously considered exist in each operation mode are summarized, and advanced artificial intelligence techniques are adopted to solve those problems as effective tools. The application situation and research status of multi-agent system, artificial neural network, genetic algorithm, fuzzy logic in distributed generation system home and abroad are summarized detailedly. The existing problems and solving thoughts of each artificial intelligence technique are analyzed, and developing directions of artificial intelligence applications in distributed generation system in the future are also prospected.

This work is supported by National Natural Science Foundation of China(NSFC) (50777057).

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Author information

Authors and Affiliations

  1. College of Information Engineering, Zhejiang University of Technology, Hangzhou, 310014, China

    Guoqing Weng, Youbing Zhang & Yi Hu

Authors
  1. Guoqing Weng
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  2. Youbing Zhang
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  3. Yi Hu
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Editor information

Editors and Affiliations

  1. Departamento de Control Automático,, CINVESTAV-IPN,, A.P. 14-740, Av.IPN 2508,, D.F., 07360,, México, México

    Wen Yu

  2. Deptartment of Electrical and Computer Engineering,, Stevens Institute of Technology,, NJ 07030,, Hoboken,, USA

    Haibo He

  3. Dept. of Electrical and Computer Engineering,, South Dakota School of Mines & Technology,, 501 E. St. Joseph Street,, SD 57701,, Rapid City,, USA

    Nian Zhang

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© 2009 Springer-Verlag Berlin Heidelberg

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Weng, G., Zhang, Y., Hu, Y. (2009). Application of Artificial Intelligence Technique in Distributed Generation System. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01510-6_19

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  • DOI: https://doi.org/10.1007/978-3-642-01510-6_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01509-0

  • Online ISBN: 978-3-642-01510-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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