Measuring wind turbine health using fuzzy-concept-based drifting models
Jastrzebska,Agnieszka Morales Hernández,Alejandro Nápoles,Gonzalo Salgueiro,Yamisleydi Vanhoof,Koen
Jastrzebska,Agnieszka
Morales Hernández,Alejandro
Nápoles,Gonzalo
Salgueiro,Yamisleydi
Vanhoof,Koen
Abstract
Time series processing is an essential aspect of wind turbine health monitoring. In this paper, we propose two new approaches for analyzing wind turbine health. Both methods are based on abstract concepts, implemented using fuzzy sets, which allow aggregating and summarizing the underlying raw data in terms of relative low, moderate, and high power production. By observing a change in concepts, we infer the difference in a turbine's health. The first method evaluates the decrease or increase in relatively high and low power production. This task is performed using a regression model. The second method eval-uates the overall drift of extracted concepts. A significant drift indicates that the power production process undergoes fluctuations in time. Concepts are labeled using linguistic labels, which makes our model easier to interpret. We applied the proposed approach to publicly available data describing four wind turbines, while exploring different external conditions (wind speed and temperature). The simu-lation results have shown that turbines with IDs T07 and T06 degraded the most. Moreover, the dete-rioration was clearer when we analyzed data concerning relatively low atmospheric temperature and relatively high wind speed. (c) 2022 Published by Elsevier Ltd.
Description
Funding Information: The project was partially funded by POB Research Center for Artificial Intelligence and Robotics of Warsaw University of Technology within the Excellence Initiative Program - Research University (ID-UB). Publisher Copyright: © 2022
Date
2022-05
Journal Title
Journal ISSN
Volume Title
Publisher
Research Projects
Organizational Units
Journal Issue
Keywords
Concept-based model, Diagnosis, Health index, Prediction, Regression, Time series, Wind turbine, SDG 7 - Affordable and Clean Energy
Citation
Jastrzebska, A, Morales Hernández, A, Nápoles, G, Salgueiro, Y & Vanhoof, K 2022, 'Measuring wind turbine health using fuzzy-concept-based drifting models', Renewable Energy, vol. 190, pp. 730-740. https://doi.org/10.1016/j.renene.2022.03.116
License
info:eu-repo/semantics/closedAccess