Applications of artificial intelligence techniques in wind power generation

  • Authors:

  • S. A. Papathanassiou;A. G. Kladas;J. A. Tegopoulos

  • Affiliations:

  • Lab. of Elec. Mach., Elec. Pwr. Div., Dept. of Elec. and Comp. Eng., Natnl. Tech. Univ. of Athens, 9, Iroon Polytechneiou street, 15780 Athens, Greece. Tel.: +301 7723766/ Fax: +301 7723968/ E-mai ...;Lab. of Elec. Mach., Elec. Pwr. Div., Dept. of Elec. and Comp. Eng., Natnl. Tech. Univ. of Athens, 9, Iroon Polytechneiou street, 15780 Athens, Greece. Tel.: +301 7723766/ Fax: +301 7723968/ E-mai ...;(Correspd.) Lab. of Elec. Mach., Elec. Pwr. Div., Dept. of Elec. and Comp. Eng., Natl. Tech. Univ. of Athens, 9, Iroon Polytechneiou street, 15780 Athens, Greece. Tel.: +301 7723766/ Fax: +301 772 ...

  • Venue:
  • Integrated Computer-Aided Engineering
  • Year:
  • 2001

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Abstract

The paper presents two applications of Artificial Intelligence techniques, namely Artificial Neural Networks (ANNs) and Decision Trees (DTs), in wind power generation. The first concerns the design procedure of a permanent magnet generator for a 20 kW wind turbine prototype. This work has been developed in the frame of a research project funded by the General Secretariat for Research and Technology of Greece, concerning the design and construction of a gear-less wind turbine for both autonomous and interconnected operation with the electrical grid. The second application concerns the security assessment of networks including wind farms and has been developed in the frame of JOULE-II European Community research programme. The results from the application of ``learning from examples'' methods, namely ANNs and DTs, for the fast dynamic security assessment of the power system of Lemnos island are presented and comparatively assessed.