Abstract

Abstract For wind turbine development, load size is the core and critical factor. Currently, most companies employ Bladed software for load calculations, which enjoys widespread use in engineering applications due to its efficiency and ease of use. However, constrained by the limitations of blade element theory and momentum theory, there still exist discrepancies between the simulation results and actual conditions. This paper aims to combine simulation algorithms with the application of an LSTM (Long Short-Term Memory) neural network to develop a compensation algorithm for the main shaft loads of wind turbines. By doing so, it endeavors to realize real-time monitoring of the main shaft loads, thereby providing a foundation for achieving high-precision control in wind turbine systems.

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