Open AccessArtificial Intelligent Control of Permanent Magnet Synchronous Generator Based Wind Energy Conversion System
Author(s) -
Maher Mohammed
Publication year - 2019
Publication title -
kirkuk university journal-scientific studies
Language(s) - English
Resource type - Journals
eISSN - 2616-6801
pISSN - 1992-0849
DOI - 10.32894/kujss.2019.14.2.3
Subject(s) - permanent magnet synchronous generator , adaptive neuro fuzzy inference system , control theory (sociology) , rotor (electric) , generator (circuit theory) , variable speed wind turbine , maximum power principle , torque , computer science , wind power , induction generator , vector control , control engineering , power (physics) , shunt generator , magnet , engineering , fuzzy control system , fuzzy logic , control (management) , voltage , artificial intelligence , mechanical engineering , electrical engineering , physics , quantum mechanics , induction motor , thermodynamics
In this work new maximum power extracted architecture is proposed for wind turbine generator. Adaptive network based fuzzy inference system (ANFIS) is used to precisely estimate the rotor angle and speed which is necessary for vector control in order to forces the generator to track maximum power using variable speed operation generator. In this algorithm the separate control of the torque from the flux make the control of a generator operation with variable speed more efficient. The ANFIS network is trained off line from the normal operation of the permanent magnet generator.
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