Reliability improvement of wind turbine power generation using model-based fault detection and fault tolerant control: A review

Hamed Habibi, Ian Howard and Silvio Simani

Renewable Energy, 2019, vol. 135, issue C, 877-896

Abstract: Reliability improvement of wind turbine power generation is the key issue that can turn the wind power into one of the main power sources to respond to the world power demands. The likelihood of fault occurrence on wind turbine components is unavoidable, especially for large rotor modern wind turbines, operating in harsh offshore environments. Accordingly, the maintenance need increases due to unanticipated faults, which in turn, leads to higher energy cost and less reliable power generation. In this regard, model-based fault detection and fault tolerant control techniques have been extensively investigated in the last decade, for achieving good performance. In this way, the reliability, availability and safety features of the wind turbine power generation are also enhanced. Thus, in this paper a comprehensive review of the most-recent model-based fault detection and fault tolerant control schemes for wind turbine power generation is presented, focusing on the advantages, capabilities and limitations. Note that the so-called data-driven or signal-based methodologies, which rely on the analysis of the signals directly generated from the monitored system, are not reviewed in this paper. This review is organized in a tutorial manner, to be a suitable reference for further research for the wind turbine’s reliability improvement.

Keywords: Wind turbines; Model-based approaches; Reliability and robustness; Fault detection and isolation (FDI); Fault estimation; Fault tolerant control (FTC) (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:135:y:2019:i:c:p:877-896

DOI: 10.1016/j.renene.2018.12.066

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