Abstract
Wind energy is contributing to more and more portions in the world energy market. However, one deterrent to even greater investment in wind energy is the considerable failure rate of turbines. In particular, large wind turbines are expensive, with less tolerance for system performance degradations, unscheduled system shut downs, and even system damages caused by various malfunctions or faults occurring in system components such as rotor blades, hydraulic systems, generator, electronic control units, electric systems, sensors, and so forth. As a result, there is a high demand to improve the operation reliability, availability, and productivity of wind turbine systems. It is thus paramount to detect and identify any kinds of abnormalities as early as possible, predict potential faults and the remaining useful life of the components, and implement resilient control and management for minimizing performance degradation and economic cost, and avoiding dangerous situations. During the last 20 years, interesting and intensive research results were reported on fault diagnosis, prognosis, and resilient control techniques for wind turbine systems. This paper aims to provide a state-of-the-art overview on the existing fault diagnosis, prognosis, and resilient control methods and techniques for wind turbine systems, with particular attention on the results reported during the last decade. Finally, an overlook on the future development of the fault diagnosis, prognosis, and resilient control techniques for wind turbine systems is presented.
Highlights
In order to enhance the capability of harvesting wind energy, wind turbines have become larger, but more complex and expensive
One of the important techniques is condition monitoring and fault diagnosis, which is to monitor whether a system is healthy, detect any faults or malfunctions in their early stages, determine where the faults occur, and assess the severity of the faults so that appropriate actions can be taken in order to avoid further damages and even dangerous situations in wind turbine systems
Resilient control is a technique to minimize the effects from the faulty components or unexpected disruptions so that the wind turbine system can work with tolerant performance degradation under some abnormal conditions
Summary
In order to enhance the capability of harvesting wind energy, wind turbines have become larger, but more complex and expensive. In [17], an overview was presented for condition monitoring, fault diagnosis, and operation control (including online maintenance and fault tolerant control) on electric power conversion systems in direct-drive wind turbines. [23] is editorial review for 23 papers included in a special issue This motivates us to provide a comprehensive review on fault diagnosis, prognosis, and resilient control for wind turbine systems in a single paper, which would benefit the readers to appreciate the current state of the art of heath monitoring and management and control in wind turbine conversion systems. FaulCt oDnidaigtnioonsims oonfiWtoriinndg Taiumrbs itnoecsheck operation parameters of wind turbines to provide an eCaorlnydiintidoincamtioonniotof rfianugltsa,imansdtofacuhltedckiaogpnoersaistiiosncopnadraumcteetdertos odfetwecint,dlotcuartbe,inaensdtiodpenroti-fy viodcecuarnrienagrlfyauinltds,icwahtiiocnh aolflofawusltuss, atondplfaanuslyt sdtieamgnroepsiasirisstcroantedguiecstepdritoor dtoetceocmt, plolectaetefa, ialunrdes. idCenotnidfyitoiocncumrroingitofariunlgts,iswahcitcuhalalyllokwinsduosftfoaupltandestyesctteiomn,rethpearierfsotrreatiengtihesisppraioprertowceomw-ill plseutervfeayilcuornesd.itCioonndmitoinointomrinongiatonrdinfgauilst adciatuganlolysiskiwnidthoinf faaufrlatmdewteoctriko.nF,rtohmertehfoerveieinwpthoiisnt paopf edrifwfeerewnitlltsyuprevseoyfctohnediintifonrmmaotinointorreindgunanddanfacyu,ltfaduialtgdnioasgisnowsiitshcinanabfreacmaetewgorkiz.eFdroimnto thme ovdieew-bpaosiendt mofedthifofedrse,nstigtynpael-sboasfetdheminetfhoromdsa,tikonorwedleudngdea-bnacyse, dfamulet tdhioadgsn,oasnisdcahnybbreid methods by combining the three above-mentioned methods
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