Predicting Wind Turbine Scheduling Maintenance Using Artificial Neural Network for Preventing Blade Breakage: Case Study Baron Techno-Park
One of the main issue that Baron Techno-Park (hybrid power plant) is facing are the practices of finding a suitable maintenance strategy. Operation and maintenance (O&M) of wind turbines are heavily affected by weather condition, particularly wind conditions. Blade failures, such as blade breakages, can lead to catastrophic consequences. The causes of blade breakages in Baron Techno-Park is due to unpredictable high wind speed from different directions. A technique that this research propose to implement a maintenance strategy in order to create an efficient O&M and also prevent the breakage of the wind turbine blades, is by using the Artificial Neural Network (ANN). ANN performance is satisfactory with the wind speed error of 30.25 % and wind direction error of 13.74 %. Also, R2 has a highest prediction of 0.998. Analyzing the survival wind speed of 60 m/s which is specify in the wind turbine specification. Analyzing the prediction results. It is safe to say that during the month of July 2021, it is not necessary for a maintenance schedule.
Copyright (c) 2021 Fredi Prima Sakti, Haidar Rahman, Ikrima Alfi, Ridwan Budi Prasetyo
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to journal IJETS, University Of Technology Yogyakarta as publisher of the journal, and the author also holds the copyright without restriction.
Copyright encompasses exclusive rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms and any other similar reproductions, as well as translations. The reproduction of any part of this journal, its storage in databases and its transmission by any form or media, such as electronic, electrostatic and mechanical copies, photocopies, recordings, magnetic media, etc. , are allowed with a written permission from journal IJETS, University Of Technology Yogyakarta.
Jurnal IJETS Board, University Of Technology Yogyakarta, the Editors and the Advisory International Editorial Board make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in the journal IJETS, University Of Technology Yogyakarta are sole and exclusive responsibility of their respective authors and advertisers.