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Artificial Immune Network Combined with Normative Knowledge for Power Economic Dispatch of Thermal Units

  • Conference paper
Applications of Soft Computing

Part of the book series: Advances in Soft Computing ((AINSC,volume 52))

Summary

Recently, many research activities have been devoted to Artificial Immune Systems (AISs). AISs use ideas gleaned from immunology to develop intelligent systems capable of learning and adapting. AISs are optimization methods that can be applied to the solution of many different types of optimization problems in power systems. In particular, a new meta-heuristic optimization approach using artificial immune networks called opt-aiNET combined with normative knowledge, a cultural algorithm feature, is presented in this paper. The proposed opt-aiNET methodology and its variants are validated for a economic load dispatch problem consisting of 13 thermal units with incremental fuel cost function takes into account the valve-point loadings effects. The proposed opt- aiNET approach provides quality solutions in terms of efficiency compared with other existing techniques in literature for load dispatch problem with valve-point effect.

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Author information

Authors and Affiliations

  1. Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Paraná, PUCPR, Imaculada Conceição, 1155, Zip code 80215-901, Curitiba, Paraná, Brazil

    Leandro dos Santos Coelho

  2. Mechanical Engineering Graduate Program, PPGEM, Pontifical Catholic University of Paraná, PUCPR, Imaculada Conceição, 1155, Zip code 80215-901, Curitiba, Paraná, Brazil

    Viviana Cocco Mariani

Authors
  1. Leandro dos Santos Coelho
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  2. Viviana Cocco Mariani
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Editor information

Editors and Affiliations

  1. Senior Lecturer in Integrated Transport Centre for Transport & Society Faculty of the Built Environment, University of the West of England, Frenchay Campus Coldharbour Lane, BS16 1QY, Bristol, UK

    Erel Avineri

  2. Kyushu Institute of Technology, Dept. Artificial Intelligence, 680-4 Kawazu Izuka-Shi, 820-8502, Fukuoka, Japan

    Mario Köppen

  3. MOSAIC Research Group Department of Computing, University of Bradford, BD7 1DP, Bradford, UK

    Keshav Dahal

  4. Centre for Transport & Society Faculty of the Built Environment, University of the West of England, Frenchay Campus Coldharbour Lane, BS16 1QY, Bristol, UK

    Yos Sunitiyoso

  5. Professor of Decision Engineering and Head of Decision Engineering Centre Manufacturing Department, Cranfield University, MK43 OAL, Bedford, UK

    Rajkumar Roy

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© 2009 Springer-Verlag Berlin Heidelberg

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dos Santos Coelho, L., Mariani, V.C. (2009). Artificial Immune Network Combined with Normative Knowledge for Power Economic Dispatch of Thermal Units. In: Avineri, E., Köppen, M., Dahal, K., Sunitiyoso, Y., Roy, R. (eds) Applications of Soft Computing. Advances in Soft Computing, vol 52. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88079-0_6

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  • DOI: https://doi.org/10.1007/978-3-540-88079-0_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88078-3

  • Online ISBN: 978-3-540-88079-0

  • eBook Packages: EngineeringEngineering (R0)

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