A Proportional Digital Controller to Monitor Load Variation in Wind Turbine Systems

Abstract

Monitoring the variation of the loading blades is fundamental due to its importance in the behavior of the wind turbine system. Blade performance can be affected by different loads that alter energy conversion efficiency and cause potential safety hazards. An example of this is icing on the blades. Therefore, the main objective of this work is to propose a proportional digital controller capable of detecting load variations in wind turbine blades together with a fault detection method. An experimental platform is then built to experimentally validate the main contribution of the article. This platform employs an automotive throttle device as a blade system emulator of a wind turbine pitch system. In addition, a statistical fault detection algorithm is established based on the point change methodology. Experimental data support our approach.

Predictive Speed Control of a DC Universal Motor Applied to Monitor Electric Vehicle Batteries

“…Firstly, the control strategy must meet its control objective. Secondly, the control must be fault tolerant in order to generate the data needed for a health diagnosis (see, for example, [25]). In this article, a simple discrete control is proposed to generate feasible data for fault diagnoses in wind turbines.…”