Turbulence classification of load data by the frequency and severity of wind gusts. Oscar Moñux, DEWI GmbH Kevin Bleibler, DEWI GmbH

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1 Turbulence classfcaton of load data by the frequency and severty of wnd gusts Introducton Oscar Moñux, DEWI GmbH Kevn Blebler, DEWI GmbH Durng the wnd turbne developng process, one of the most mportant attrbutes of a wnd turbne to consder, s the fatgue of the wnd turbne s components. The fatgue helps to understand the magntude of the varaton on the loads and how they are affectng the turbne, ndcatng therefore the expected lfetme of the turbne. Both a measurement campagn and a smulatons on the turbne have results of the fatgue analyzes of wnd turbne s components. The problem begns when both fatgue results are beng compared. Dfferent atmospherc condtons are not always consdered n smulatons. The duraton of a load measurement campagn s often not more than 3 to 6 months and these condtons are dependent on the season, the ste and the nfluence of the locaton on the wnd turbne then the results can be obvously mslead. In ths paper a new classfcaton method s presented whch helps to compare measurement wth smulaton results. Ths s an approach not to change the certfcaton procedures, but to mprove the current classfcaton procedures. The current classfcaton method Currently the fatgue of wnd turbne components s obtaned Capture matrx Wndturbne: Example by analyzng (measurement or Wnd speed bn sze (x axs): 1 m/s 2% Turbulence bn sze (y axs) : smulaton) data wth certan 0 < wnd and turbulence condtons. Ths s done Turbulence accordng to the normatve IEC [1] for mechancal >29 1 load measurement on wnd Datasets : 3156 Turbulence at 15m/s: 8,18 turbne. The normatve gves a Fatgue capture matrx whch classfes a database nto wnd and Fgure 1 Capture matrx turbulence bns. Fgure 1 shows ths capture matrx where the wnd speed s ndcated on the horzontal cells n bns of 1m/s and the turbulence n vertcal cells wth bn wdths of 2%. From the matrx a sub-database wth one or more turbulences are selected for the fatgue analyss. The approach for a new classfcaton method The new method conssts of three dfferent phases. The database for the evaluatons s prepared accordng to the IEC Devatng from ths, 1 Mnute (and not 10 Mnute) tme seres are used n the new method to gather a sutable bg database n a reasonable measurement tme. Fgure 2 gves an overvew of the new method. Ths frst phase s dvded nto two parts. The frst part s the varables defnton, where for meteorologcal mast and turbne s quanttes several parameters are obtaned. Furthermore the fatgue of turbne s calculated from measured load quanttes. In the second part the correlaton between the parameters and the fatgue s nvestgated. The last phase s the reproducblty and the conclusons. Phase 1A Varables Wnd speed V(m/s) 0 1,5 2,5 3,5 4,5 5,5 6,5 7,5 8,5 9,5 10,5 11,5 12,5 13,5 14,5 15,5 16,5 17,5 18,5 19,5 20,5 21,5 22,5 23,5 >24.5 I(% ) 1,5 2,5 3,5 4,5 5,5 6,5 7,5 8,5 9,5 10,5 11,5 12,5 13,5 14,5 15,5 16,5 17,5 18,5 19,5 20,5 21,5 22,5 23,5 24,5 V out For ths paper, the followng quanttes from a meteorologcal mast are used: Mean Wnd Speed Standard Devaton of Wnd speed

2 Phase 0: Select the database NOP1 1 mnute No IEC ? Yes Met Mast Turbne Fatgue IEC Phase 1A: Varables Wnd, Atmosphere Varables Loads, Wnd, Control Classfcaton Range Par Spectra EQL Met Mast: Wnd speed + Turbulence Phase 1B: Compare Varables Wnd, Atmosphere versus Fatgue Loads, Wnd, Control versus Fatgue Phase 2: Classfcaton & Results % varables wth nfluence n IEC classfcaton Learn whch condtons affects to the turbne Fatgue: turbulences + wnd speeds Phase 3: Reproducblty & Conclusons Recombne the database or change condtons n model Conclusons Fgure 2 Scheme of the new classfcaton method Turbulence Gust factor for wnd speed Trend of the wnd speed The gust factor s calculated accordng to the equatons 1 to 2 Gust = val{ max( TaL( f )) ( Envelope x ) Whereas = Equatons 1 and 2 t The followng quanttes from the nacelle measurement are used: Mean Wnd Speed Standard Devaton of Wnd speed Man frequences of the nacelle anemometer Integraton of the FFT of the nacelle anemometer accordng to equaton 3 f Percentage = value Ampltude =0 x = = Ampltude x Equaton 3

3 For an example the fatgue s obtaned by usng the blade root moment out of plane n every dataset. The followng fatgue quanttes are used: M40 M20 M05 Counts As the fgure 3 llustrates the parameters: M05, M10, M20 untl M60 The equvalent loads Ampltude Fgure 3 Fatgue Indexes Phase 1b Comparson of the varables. In ths phase the fatgue and the varables are compared n order to fnd: a) The man correlatons between the met mast varables and the fatgue of turbne components b) The man correlatons between the turbne varables and the fatgue of turbne components There are several methods to fnd these correlatons. To name some: lnear or polynomal regressons, statstcal approaches, neural networks, or methods based on the convoluton product (Laplacan) Fgure 4 Correlaton between M20 and the frequency of the nacelle anemometer The correlatons can be used to estmate the fatgue: a) on the turbne s ste wth not measured load condtons. b) of same model turbnes on dfferent stes c) wth the worst case scenaro. [ MNm ] Fgure 4 shows a correlaton to obtan M20 as equaton 4 ndcates: [ Hz ] 1.00 [ m/s ] 0.00 M 2 20 = a vmean + b f medan + c f medan Equaton 3 Phase 2 Classfcaton and Results At last the man correlatons are ndcated n the new capture matrx (fgure 5). Every cell of the capture matrx s splt n two dmensons: the horzontal have the varables found before, and the vertcal contans the bn analyss of the varables. In ths paper for clarty just the gust s ncluded although more parameters are possble.

4 Wndturbne: Example Wnd speed bn sze (x axs): 1 m/s Turbulence bn sze (y axs) : 2% Capture matrx V(m/s) 0 1,5 2,5 3,5 4,5 5,5 6,5 7,5 8,5 9,5 10,5 11,5 12,5 13,5 14,5 15,5 16,5 17,5 I(%) 1,5 2,5 3,5 4,5 5,5 6,5 7,5 8,5 9,5 10,5 11,5 12,5 13,5 14,5 15,5 16,5 17,5 18,5 gust gust gust gust gust gust gust gust gust gust gust gust 0 < total class class class class class > Datasets : 2672 Mean Turbulence 10,00 gust mnmum 0,82 class sze 0,29 Fgure 5 New capture matrx Ths representaton helps: a) If the model cannot be smulated wth specfc atmospherc condtons, then the capture matrx can be fltered wth the possble ones b) to study the nfluence of the atmospherc effects on the fatgue c) to understand the statstcal dstrbuton of the atmospherc condtons at the ste In the followng example (fgure 6) for two turbnes wth dfferent szes, locatons and weather condtons several varables are fltered. The parameters are gust and frequency on the nacelle anemometer (hgh or low). The fatgue of the moment out of plane s evaluated for ther correspondent webull dstrbuton, extrapolated over 20 years, the wnd speed range s n all cases from 4 m/s to 14 m/s. Dfferent wnd condtons alter the result as t can be seen of the fatgue analyss.

5 counts Normal: Mbop_4_RP No_gust: Mbop_4_RP low_medan: Mbop_4_RP hgh_medan: Mbop_4_RP counts normal: Mbop_4_RP no_gust: Mbop_4_RP low_medan: Mbop_4_RP hgh_medan: Mbop_4_RP %MNm %MNm Fgure 6 Fatgue results Conclusons Applyng the descrbed method allows to adapt the gven measurement condtons to the smulaton and so obtan a better understandng of the wnd turbne and the effects of dfferent behavors on the loads of the turbne. Ths helps to estmate the fatgue n any turbne and to understand the dfferences between the smulatons and the measurements. References [1] Techncal Specfcaton TS IEC : Wnd Turbne Generator Systems, Part 13: Measurement of Mechancal Loads. 1. Edton Internatonal Electro-techncal Commsson. Geneva, Swtzerland