loading
Documents

Research.Publish.Connect.

Paper

Authors: Afshin Tafazzoli 1 and Alvaro Mayo 2

Affiliations: 1 Global Services, Siemens Gamesa Renewable Energy, Calle Ramirez Arellano, 37, Madrid 28043 and Spain ; 2 Energy Consultant, KPMG, Torre de Cristal, Paseo de la Castellana, 259C, Madrid 28046 and Spain

ISBN: 978-989-758-373-5

Keyword(s): Wind Turbine Generator (WTG), Artificial Intelligence (AI), Condition Monitoring System (CMS).

Abstract: This project is motivated by the importance of wind energy and reducing the financial and operational impact of faults in wind turbine generator using artificial intelligence based condition monitoring system. It is to classify the fault alarms and diagnose smart solutions at level zero to resolve the faults without service expert’s intervention. Big data analysis of the large historical data pool results in the intelligent algorithms that can power the diagnostic models. For maximum efficiency, wind turbines tend to be located in remote locations such as on offshore platforms. However, this remoteness leads to high maintenance costs and high downtime when faults occur. These factors highlight the importance of early fault detection and fast resolution in great extent. The aim of the project has been to have smart wind turbines integrated with artificial intelligence. The condition monitoring system should have the capability to detect, identify, and locate a fault in a wind turbine a nd remotely reset the turbines whenever possible. (More)

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.242.193.41

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Tafazzoli, A. and Mayo, A. (2019). Smart Wind Turbine: Artificial Intelligence based Condition Monitoring System.In Proceedings of the 8th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-373-5, pages 194-198. DOI: 10.5220/0007767701940198

@conference{smartgreens19,
author={Afshin Tafazzoli. and Alvaro Novoa Mayo.},
title={Smart Wind Turbine: Artificial Intelligence based Condition Monitoring System},
booktitle={Proceedings of the 8th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2019},
pages={194-198},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007767701940198},
isbn={978-989-758-373-5},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - Smart Wind Turbine: Artificial Intelligence based Condition Monitoring System
SN - 978-989-758-373-5
AU - Tafazzoli, A.
AU - Mayo, A.
PY - 2019
SP - 194
EP - 198
DO - 10.5220/0007767701940198

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.