Automation Optimization and Control System of Wind Power Generation Sys-tem Based on Deep Learning
To address the instability of wind power generation systems caused by wind speed fluctuations,a deep learning based automation optimization and control system for wind power generation is designed.Collect temperature,speed and other signals during the operation of the wind power generation system,use deep learning algorithms to op-timize the parameters of the incremental PID control algorithm.The incremental PID control algorithm obtains an au-tomated optimization control quantity,and through the optimization control quantity,controls the position of the wind turbine,pitch angle,and motor speed of the wind power generation system.Presenting automated optimization control processes through remote monitoring modules.Experimental results have shown that the system can effectively collect operational parameters of wind power generation systems,optimize incremental PID control algorithm parameters,com-plete automation optimization control of wind power generation systems,and improve the stability of wind power gen-eration systems.
deep learningwind power generation systemautomationoptimization and controlsensorsincremental PID control algorithm
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