skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Real-time monitoring, prognosis, and resilient control for wind turbine systems

Abstract

This special issue aims to provide a platform for academic and industrial communities to report recent results and emerging research in real-time monitoring, fault diagnosis, prognosis, and resilient control and design of wind turbine systems. After a strict peer-review process, 20 papers were selected, which represent the most recent progress of the real-time monitoring, diagnosis, prognosis, and resilient control methods/techniques in wind turbine systems.

Authors:
 [1];  [2]
  1. Univ. of Northumbria, Newcastle upon Tyne (United Kingdom)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1417288
Report Number(s):
NREL/JA-5000-70021
Journal ID: ISSN 0960-1481
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Renewable Energy
Additional Journal Information:
Journal Volume: 116; Journal Issue: PB; Journal ID: ISSN 0960-1481
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; 42 ENGINEERING; wind turbine; wind energy; monitoring; prognosis; resilient control; analysis; fault detection

Citation Formats

Gao, Zhiwei, and Sheng, Shuangwen. Real-time monitoring, prognosis, and resilient control for wind turbine systems. United States: N. p., 2017. Web. doi:10.1016/j.renene.2017.10.059.
Gao, Zhiwei, & Sheng, Shuangwen. Real-time monitoring, prognosis, and resilient control for wind turbine systems. United States. doi:10.1016/j.renene.2017.10.059.
Gao, Zhiwei, and Sheng, Shuangwen. Sat . "Real-time monitoring, prognosis, and resilient control for wind turbine systems". United States. doi:10.1016/j.renene.2017.10.059. https://www.osti.gov/servlets/purl/1417288.
@article{osti_1417288,
title = {Real-time monitoring, prognosis, and resilient control for wind turbine systems},
author = {Gao, Zhiwei and Sheng, Shuangwen},
abstractNote = {This special issue aims to provide a platform for academic and industrial communities to report recent results and emerging research in real-time monitoring, fault diagnosis, prognosis, and resilient control and design of wind turbine systems. After a strict peer-review process, 20 papers were selected, which represent the most recent progress of the real-time monitoring, diagnosis, prognosis, and resilient control methods/techniques in wind turbine systems.},
doi = {10.1016/j.renene.2017.10.059},
journal = {Renewable Energy},
number = PB,
volume = 116,
place = {United States},
year = {Sat Oct 21 00:00:00 EDT 2017},
month = {Sat Oct 21 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Save / Share: