Reliability of onshore wind turbines based on linking power curves to failure and maintenance records: A case study in central Spain

Author:

Sanchez‐Fernandez Andres J.1ORCID,González‐Sánchez José‐Luis1ORCID,Luna Rodríguez Íñigo2ORCID,Rodríguez Félix R.1ORCID,Sanchez‐Rivero Javier3ORCID

Affiliation:

1. Department of Computer Systems Engineering and Telematics University of Extremadura, School of Technology Cáceres Extremadura Spain

2. Supervisión y Monitorización Naturgy Renovables Pamplona Navarra Spain

3. CénitS‐COMPUTAEX Extremadura Supercomputing, Technological Innovation and Research Center Cáceres Extremadura Spain

Abstract

SummaryWind turbine (WT) reliability has come to the forefront of research due to the rapid growth of wind energy in recent years. Reliability information can help understand failure causes and focus maintenance and prevention efforts on the most critical components, reducing costs and increasing profits. This paper offers new insights into WT reliability after analysing the data provided by the Supervisory Control And Data Acquisition (SCADA) system collected from seven onshore WTs located in central Spain from January 2014 to September 2021. To this end, we propose a method to link SCADA data to failure and maintenance records based on checking whether each 10‐min average time sample was collected when any failure or maintenance action had been reported. These records have been manually mapped to the WT taxonomy based on the standard Reference Designation System for Power Plants (RDS‐PP®) with minor changes. We present three different results: (i) The capacity factor and time‐based availability of each WT; (ii) the subsystem failure rate and downtime to identify the most critical ones; and (iii) each WT power curve with the 10‐min time samples labelled as healthy, under maintenance, or failure states, along with a ranking of the subsystems causing the most failures in each part of the power curves. It is the first time that time samples are linked to failure and maintenance records to visualise their distribution on the power curves. These results can help research point in the right direction to improve reliability and increase electricity production worldwide.

Funder

European Regional Development Fund

Publisher

Wiley

Subject

Renewable Energy, Sustainability and the Environment

Reference33 articles.

1. UnivDatos Market Insights.Press releases. wind energy market size growth opportunities future challenges and forecast to 2021‐2027

2. 2021. Accessed January 20 2022.https://www.openpr.com/news/2487729/wind-energy-market-size-growth-opportunities-future

3. Reliability analysis of wind turbines;Zhu F;Stab Control Reliable Perform Wind Turbines,2018

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3