Performance analysis of different predictive models for condition monitoring of direct drive wind turbine generator

Nelson T Corbita,Jui-Hung Liu

doi:10.1177/00202940211003930

Abstract

This paper presents a performance analysis of predictive models for the generator module which can be used as a reference for improvement in the condition monitoring system using wind turbines in a wind farm in Taiwan. With the generator being a critical component prone to failures, it is important to perform data analysis on its parameters that could be used for condition monitoring. The main innovative feature in this framework is the conduct of performance analysis before the development of the condition monitoring system. Also, the consistency of the performance between the different wind turbines in the wind farm is evaluated. The predictive models are generated using the neural network algorithm with a different combination of parameters from the SCADA system. The correlation of the parameters as well as the mean square error of the predictive models were then computed for analysis. Results showed that pairing of input parameters with a higher correlation to the output parameter would give better performance for the predictive model. Furthermore, the performance of the different models was consistent throughout the different wind turbines in the wind farm which indicates that the same model can be developed and used for wind turbines belonging to the same wind farm. Employing a preliminary performance analysis of different combinations of component parameters could help in optimizing predictive models for condition monitoring.

Highlights

Wind energy is the energy generated from the movement of the wind
The input combination that gives the optimal performance to the generator speed model is the four-input parameter combination of air gap temperature, bearing temperature, stator temperature, and active power
Looking at the different input parameters in these number code combinations, it can be seen that the common parameter among these combinations is the parameter ‘‘active power.’’ It implies that the active power parameter improves the performance of the generator speed model

Summary

Introduction

The wind turbine converts the kinetic energy from the wind to mechanical energy to electrical energy. Through the mechanism of the different components of the wind turbine, it can harness wind power from the motion of the wind.[1] Direct drive wind turbine assembly removes the gearbox configuration that connects the rotor to the generator. This means that for direct-drive wind turbines, the speed of the generator is the same as the speed of the rotor.[2] The main difference for the direct drive assembly compared with the gearbox configuration is the design of the generator

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Conclusion