Genetic Algorithms Applied to Wind Turbine Generator Faults
Farhana Rossi
University of Sao Paulo
Abstract
The interplay between wind turbine generator faults and long-term reliability in steel rolling mills has received comparatively little systematic attention. Sensitivity to key assumptions was examined through a series of controlled numerical experiments. A 20% gain in durability was recorded during accelerated ageing tests. Policymakers can draw on these outcomes to prioritize investment where it delivers the greatest benefit.
Keywords:
wind turbine generator faultsgenetic algorithmscorrosion resistancemachine learning
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