Support at the choice of solutions to the phase of preliminary design based

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Support at the choice of solutions to the phase of preliminary design based

  1. 1. INTERNATIONALMechanical Engineering and Technology (IJMET), ISSN 0976 – International Journal of JOURNAL OF MECHANICAL ENGINEERING 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME AND TECHNOLOGY (IJMET)ISSN 0976 – 6340 (Print)ISSN 0976 – 6359 (Online)Volume 4, Issue 1, January- February (2013), pp. 150-162 IJMET© IAEME: www.iaeme.com/ijmet.aspJournal Impact Factor (2012): 3.8071 (Calculated by GISI)www.jifactor.com ©IAEME SUPPORT AT THE CHOICE OF SOLUTIONS TO THE PHASE OF PRELIMINARY DESIGN BASED ON RELIABILITY ANALYSIS « APPLICATION TO GEARED-DRIVE AND DIRECT-DRIVE WIND TURBINES » H. Zaghar*; M. Sallaou; A. Chaâba Department Mechanics & Structures ENSAM, Moulay Ismail University B.P. 15290 EL Mansour, Meknes-Morocco ABSTRACT In the context of industrial competitiveness, taking into account the process design throughout the product life cycle is inevitable, from the expression of the need to recycle, the capitalization and knowledge management increasingly a target much sought after companies because of increased knowledge. Indeed, during the approval phase and use studies and scientific researches make have generated knowledge especially that concerning the reliability of system components. Methods of the knowledge structuring in mechanical design, based on functional approaches are analyzed and compared. We propose an energy approach based on the Law of System Completeness, which decomposes a system specific entity. This article provides help in the choice of solutions to the phase of preliminary design between direct-drive and geared drive wind turbine concepts, based an analytical reliability methods. Reliability data from field surveys will be used in this study in particular the failure rate. First, we propose a model of reliability of both existing and modified concepts, using a decomposition of systems at a detailed level, then qualification will be carried out of the global model is done with respect to the need expressed by the user, and which is the reason for its existence. Such a tool is intended to help designers make decisions about the choices inherent in comparison between these concepts. KEYWORDS: Preliminary design; qualification; geared and direct-drive wind turbines; reliability analysis; quality factor. 150
  2. 2. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME1. INTRODUCTION AND CONTEXT Due of the competitive environment in electric power generation, the industry willprefer the most productive and economic concepts of WTs, and reliable. The estimation ofthese criteria will help the designer to choose among several possible configurations.However, long-term cost analysis, including operation and maintenance (O&M), as well asthe first investment costs, would result in a better choice of WT concept. This is only possibleif the analysis included a comprehensive study of the reliability of different technologies.This Article refers to introduce the analysis of the reliability of the preliminary design phase,using the Markov modeling. It is expected that the method introduced in this paper will assistin the comparison between different WT technologies from a reliability point of view. Thequalification of the global model will be conducted based on a share of an assessmentcriterion that is fairly related to the need expressed by the user, and represents the reason forits existence, and also the total cost the system.The approach we seek to implement to provide assistance to the designer to conduct designand exploitation of knowledge related to the product for the evaluation of different concepts(architectures and components). This is done based on a preliminary design approach based onthe use of knowledge already capitalized [1], [2], which is based on the needs analysis anddefinition of functional specifications, to generate and analyze the knowledge necessaryto result in the generation and prioritization of valid solution.For this we propose to study geared-drive and direct-drive WT which their characteristics areillustrated in (Table 1). Table 1.Characteristics of the selected WT. [3] [4] Vestas V39/500 Enercon E40 Technology Geared-drive Direct-drive Power (kW) 500 500 Rotor diameter (m) 39 40 Rotor speed (tr/mn) 30 12-34 Control technology Pitch-regulated, Pitch-regulated, active stall variable speed Turbine years 804 900 considered2. MARKOV MODELING It is common to divide systems, from a reliability point of view, into two categories:mission orientated and repairable. For mission-orientated systems, the first failure is the mostinteresting, the probability to be in the operation state, is the most appropriate parameter tocalculate. On the other hand, for repairable systems, the availability, what the probability tofind the system in an operation state, is the most appropriate index to calculate.A WT can be considered as a repairable system and accepting that the system operates duringhis useful life, the Markov process is the best tool to study its reliability.The failure rate function of almost all systems obeys from the bath-tube curve (Figure 1),suggested that it is reasonable to consider that most WT components lie in the bottom of thiscurve, i.e. that they have a fixed failure rate, this hypothesis to define these transition rate asthe inverse of the average duration of operation and repair. [5] 151
  3. 3. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME Burn in λ(t) Wear Out Useful life Time Figure 1.The Bath tub curveAccording to the reliability theory [6] failure and repair rate can be defined respectively as:λ: Number of failures in a given period of time divided by total period of time the componentwas operated. 1 λ= (1) MTTFµ : Number of repairs in a given period of time divided by total period of time the componentwas being repaired. 1 µ= MTTR (2)In the Markov model, all states of system performance are considered. Using the transitionrates between these states could lead to the probability of residence in each state. In thesimplest form, a model with two states: running Ok and failed Ko could be considered. Inthis study a simple two-state model is assumed.A system consisting of a mechanical part and other electrical for example, could be classifiedinto two main categories, mechanics represented by M, and electric represented by E. So thesystem could be treated as a two component system.It is assumed that after electrical or mechanical failure, the system will be disconnected, andfailure in other parts will not occur, so the state which shows both electrical and mechanicalfailure is omitted. The transition rate between state 1 and state 2 in (Figure 2) is theaggregation of all the electrical components considered in series from the reliability point ofview. The same procedure is considered for mechanical components. E Ko λe λm E Ok E Ok 2 3 M Ok 1 M Ko M Ok µe µm Figure 2.Markov model of a two-component system.Since both the mechanical and electrical problems could result in a system fault, these twocomponents are considered in series from the reliability point of view, so their failure andrepair rates can be combined as: λ=λ M +λ E (3) 152
  4. 4. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME λ µ M µ E ( λ M +λ E ) µ= = (4)  λi  µ M λ E +µ E λ M ∑  i  µi Using the frequency balance approach [6], the three-state model of (Figure 2) could besummarized to a two-state model shown in (Figure 3). λ 1 OK KO 2 µ Figure 3.Markov model reduces.To evaluate the model parameters of the reduced system reliability, and applying this method[6] to (Figure 2) to obtain the probability, p(n), of any state, n, yields: P(1)(λ M +λ E )=P(2)µ E +P(3)µ M P (2 )µ E = P (1 )λ E P (3 )µ M = P (1 )λ M P(1)+P(2)+P(3)=1 (5)State 1 in (Figure 3) is equivalent to state 1 in (Figure 2) and state 2 in (Figure 3) can bededuced from aggregation of states 2 and 3 in (Figure 2), so: µMµE PO k (1)=P(1)= (6) λ E µ M +λ M µ E +µ M µ E λ E µ M +λ M µ E +λ M λ E PKo (2)=P(2)+P(3)= (7) λ E µ M +λ M µ E +µ M µ ESince state 1 in both figures 2 and 3 are equivalent, their frequencies are the same, that is: f O k (1)= f(1) ⇒ PO k (1)λ=P (1)(λ E +λ M ) (8)Interpretation of (Figure 3) shows that the probability of the Ok state, which is identical to thesteady-state availability for this system, could be calculated as the function of this modelparameter as below: µ PO k ( 1 ) = (9) λ+µ3. DEFINITION OF COMPONENTS The first step in a reliability study of a system is the structural and organicdecomposition into different entities constituting the system. The accuracy of such a study ofreliability depends on the depth and level of decomposition. 153
  5. 5. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME System Entity 1 Entity 2 Entity 3 Entity 11 Entity 12 Entity 13 Figure 4.Work breakdown structures.The (Figure 5) shows a decomposition of a geared-drive WT. Although other components aresignificant in WT reliability, this paper concentrates on the following components: blade,gearbox, generator, converter, pitch and yaw systems. The main difference between thetwo concepts is gearbox, so a direct-drive WT has fewer components, the main reason forusing this concept is to eliminate the failures the gearboxes and the effects of downtime. Acomparison of reliability between these two concepts can verify this result. There isno standard decomposition for the components of WT, but they are similar. Level 0 Site Wind Turbine Grid Level 1 Level 2 Processing unit power Electrical unit Control unit Support unit Blade Low shaft Gearbox High shaft Yaw Pitch Vane Generator Converter Cable Nacelle Tower Foundation Figure 5.Work breakdown structures for geared-drive WT4. ENERGY VISION The logical organization can be useful to limit confusion or differences ofdescription. The law of completeness of the parties, as defined by the TRIZ method, todistinguish for a given system, four main elements essential to achieving the requiredfunctions [7], this law states that the realization of a function comes from the transformationof energy (Converter), this energy is then transmitted (Transmitter), an operator then performsthe action (Operator). The law of completeness of the parties believes that a system is moresophisticated (optimal) if it contains a control function provided by a controller component.The control can be one, two, or all of the components.The components must be positioned relative to a reference, which may be external to thesystem to a global reference (level 0), or internal to the system to a local reference to a givensystem level. 154
  6. 6. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME Input Converter C Action Transmitter T Operator O Energy Controller C/C Figure 6.Law of the completeness party [8]As the pitch and yaw components are assumed to optimize the electrical energy production ofWT, and avoid stopping operation in unfavorable weather conditions. The function of thepitch system in normal wind condition is to optimize the WT performance, by controllingthe pitch angle β; also the function of the yaw system is to adjust the nacelle position takingaccount of the position of the WT in a wind farm, depending on the prevailing wind direction. Input Action Blade C Gearbox T Generator C Converter O energy Pitch & Yaw C/C Figure 7.Law of the completeness party for geared WTFor the controller C/C, it is to control operation of the processing unit, depending on the speedand direction of the wind. It is broken down into component acquisition to "take wind speed"and a command to "stop the transmission of mechanical energy of rotation" of the processingunit. The realization of all functions of the WT passes mainly by the transit of three functionaltypes of flows: [8]As wind energy systems are complex, some techniques such as the block diagrams decomposethe system into components. These methods can be used to allocate reliability, by translatingthe objective reliability of the overall system into specific objectives for components that areeasier to control.To model the reliability of a system must analyze its performance by identifying the differentinteractions between the main components. For this we use diagrams based on the energyflows that show each component as a separate block, and these blocks and their interactionscan be combined either in series, parallel or series-parallel.The control is performed on all components of the WT for optimizing its performance;however, after a small failure component pitch or yaw in normal weather conditions, the WTsystem is able to continue functioning in a situation non-optimal, this assumption is valid untilthe failure mode affects only the pitch and/or yaw. So in this case these two components canbe considered as blocks in parallel with the other components considered, if anothercomponent in series is affected when these two components must be connected in series. Theaggregation of the six components in series derives a simple Markov model with two statesOk and Ko.4.1 Geared-drive conceptThe components blade, gearbox, generator and converter, can be combined in a singletransformation unit block called U with equivalent failure and repair rates, the main pathconsists of U is the only path to success system independently of the parallel channels createdby the pitch and orientation systems. 155
  7. 7. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME Pitch U Orientation Figure 8.Reliability block diagram of geared-drive WTBased on diagrams of reliability established a three-component system could be considered.As such a system to "n" components, 2n states show all possible performance states, thesestates could be categorized in three states Ok, Degraded, and Ko. It is evident that only ifthese three components of system are in their Ok state would result in system Ok state too.As long as the pitch or yaw system, or both, are in their Ko state only, the WT could continueits non-optimal performance, which is named Degraded state here. The order of thecomponents will respectively (blade, gearbox, generator, converter, pitch, and yaw). Anydysfunction in one of the four components of U lead state Ko of the system WT regardless ofthe state of the pitch and yaw.4.2 Direct-drive conceptThe same procedure could be conducted for direct-drive concept WT. In this type of WTs,there is no gearbox, but the power electronic converter is fully rated, which is shown withdifferent block symbol, and a synchronous multi-pole generator is used, which could bewound rotor or permanent magnet excited.The aggregation of components in the main path could be named UD, which shows directtransformation unit. The three-components consist of UD, pitch and yaw, would have eight-state diagram, which could be reduced to a three-state model.The first interpretation is that, because of a reduced number of components resulting from theabsence of the gearbox, the direct-drive concept has a better availability index than the gearedgenerator concept. But account must be taken of the dependency on other factors, includinggenerator and power electronic converter reliabilities in the two concepts. The gearbox andpartially rated converter combination should be compared with the fully rated converter in thetwo concepts, as should the synchronous multi-pole generator be compared with doubly fedinduction generator.5. CALCULATION OF TRANSITION PROBABILITIES5.1 ModelingFor all other components of WT, a two-state model, similar to Figure 3, could be constructedwith equivalent of failure and repair rates, calculated based on their components and the typeof interconnection between these components, e.g. series or parallel. Data from the failure andrepair rates of the two WTs considered and various components were collected from Europeansurveys.LWK data include failure and repair rates of major components during the study period. Itis then possible to calculate the failure and repair rates of each concept. Reliability data forboth WTs chosen are based on data from LWK, and are listed in (Table 2). 156
  8. 8. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME Table 2.Reliability data of systems considered [9], [10] Vestas 39/500 Enercon E40 λ(f/year µ(rep./year) λ(f/year µ(rep./year) ) ) Blade 0,162 265,3 0,240 135 Gearbox 0,168 269,2 - - Generator 0,085 170,7 0,354 143,7 Converter 0,254 508,1 0,317 430,7 Pitch 0,095 559,9 0,292 512 Yaw 0,097 436,7 0,116 348,3The Markov graph derived from the eight states for a geared-drive WT is shown below: Ok µU OK U OK P (1) λP OK O µo µp λo Degraded µp OK U µo OK U OK U KO P (2) K KO P (3) OK P (4) OK O λo KO O λP KO O µU λU µU λU λU Ko KO U KO U KO U µU KO P (6) OK P (8) KO P (7) OK O KO O KO O λU KO U OK P (5) OK O Figure 9.State–space diagram of geared-drive WT.5.2 Calculation procedureIf components are independent, system state probabilities can be found by the product of unitstate probabilities. If components are not independent then: − Write an equation for each of n system states using frequency balance. − Any n-1 equations together with can be solved to find state probabilities. n − ∑ Pi = 1 i= 1Equations arranged in matrix form: The state probabilities can be obtained by solving BP = CWhere B: matrix obtained from the transpose of transition rate matrix R by replacing theelements of an arbitrarily selected row k by 1s, R: matrix of transition rates such that itselement rij =λ ij 157
  9. 9. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEMEλij: constant transition rate from state i to jP: column vector whose ith term Pi is the steady–state probability of the system being in stateiC: column vector with kth element equal to one and other elements set to zero.Transition matrix R: -(λ o +λ p +λ u ) λP 0 λo λu 0 0 0 µp -(λo +λu +µo ) λo 0 0 λu 0 0 0 µo -(λ u +µo +µ p ) µp 0 0 λu 0 µo 0 λP -(µo +λp +λu ) 0 0 0 λu µu 0 0 0 -µ u 0 0 0 0 µu 0 0 0 -µ u 0 0 0 0 µu 0 0 0 -µ u 0 0 0 0 λu 0 0 0 -λ u• Calculating the probability of the operating state Ok:We will calculate the determinant ∆ of the matrix B:Calculating the probability of the operating state P୓୩ :We put 1 in the first line of column 8 and all the other they are allowed to 0 because itcorresponds to the operating state: ∆ Ok P O k = P1 = (10) ∆• Calculating the probability of the degraded state:We calculate the ∆degraded , we put 1 in rows 2, 3, 4 of the column 8 and all the others allowed itto 0 because they correspond to the states (2, 3, 4), which are appropriate to the degradedstate. Pd eg rad ed = P 2 + P3 + P 4 ∆ degraded Pdegraded = (11) ∆• Calculating the probability of the failure state PKo :There are two ways to calculate:Or through the system is stochastic where: PK o = 1 -PO k -Pd e g ra d e dOr by the conventional method, the calculating determinant ∆ Ko :We put 1 in the states which correspond to the failure states of where: P K o = P5 + P6 + P 7 + P8 ∆ Ko PK o = (12) ∆ 158
  10. 10. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME6. QUALIFICATION OF SOLUTIONS The qualification criteria of a system are: the performance (criteria), availability andcost. These three criteria form the main components of the quality factor of asystem defined by ISO: [11] C r .availability IQ= (13) C TotalThe identification of performance is achieved in Phase functional analysis, it requires ananalysis of external environments, they are expressed by the functional specification calls"assessment criteria" level expresses the limit values. Cost is all costs incurred, depending onthe level, this cost can include the costs of use and destruction [15]. The estimation of theperformance and cost requires the development of models of system components and externalenvironments. The reliability of a system can be calculated by determining that of eachcomponent that constitutes it.6.1 The assessment criteriaThe criterion for assessing the service function (converting energy aerodynamics intoelectrical energy) is the energy produced per year (Epa). The power aerodynamics availablein a site per unit area, where: 1 Par =V.Pd = ρV 3 (14) 2The site can be characterized by the frequency distribution of wind speeds over a year. It iscustomary to represent this distribution by the Weibull distribution. It is a function with twoparameters k and c, the probability density function over a year, where: K K -1   V   K   V   -  f(V )=   .  .e   C  (15)  C   C k: shape parameter that characterizes the distribution of the wind, and c: scale parametercharacterizing the velocity. The available energy per year per unit area on the site is: 8760 ρ Vf 3 E pa = . . ∫ V .f(V).C p .ηg .A.dV (16) 1000 2 Vi6.2 The costThe cost models proposed in this study cover aspects of manufacturing and design of windsystems. The models used are outcome studies [12], [13]. The cost of wind system is equal tothe sum of unit costs of the components that constitute it. nc CTE = ∑ Cci (17) i=1nc: number of components (for this study nc = 6 for geared-drive, 5 to direct).Cci: Cost of component i in $. 159
  11. 11. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME• Blade Cost 3P =3×3,1225.R 2,879 (18)• Gearbox three stages planetary C ost M =16,45.P 1,249 (19)• Generator for geared-drive WT Cost G =65.P (20)• Generator for direct-drive WT Cost G =219,33.P (21)• Converter Cost C =79.P (22)• Pitch Cost P =2,28(0,2106.D 2,6578 ) (23)• Yaw Cost o =2(0,0339.D 2,964 ) (24)P: machine rating, D: diameter of the rotor.7. SYNTHESES OF RESULTS The use of failure rates and repair provided by (Table 2) of the two selected turbinesused to calculate transition probabilities of the two models derived from different conceptsconsidered. Table 3.Transition probabilities of the two WTs studied. POK PDegraded PKO Vestas 39/500 0,91 0,0004 0,0896 Enercon E40 0,889 0,0008 0,1102The geared-drive WT Vestas 39/500 is available as direct-drive WT Enercon E40 for thispower range.The probability that these two concepts are in a degraded state is very small compared to otherstates. And changes to the architecture of interaction between components of WTs arerequired to increase the number of states in the state degraded in favor of the state Ko, andtherefore increase further system availability. 160
  12. 12. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEME Table 4.Different results of the two WTs studied. .Different Vestas 39/500 Enercon E40 Blade($) 48489 52155 Gearbox($) ($) 38653 - Generator ($) 32500 109665 Converter($) ($) 39500 39500 Pitch($) 8131 8697 Yaw($) 3525 3800 Total($) 170798 213817 Epa(Kwh) 7787 8192 Availability lability 0,9104 0,8898 0.05 0.04 0.03 0.02 0.01 0 IQ Vestas V39/500 0.0415 Enercon E40 0.0341 Figure 10.Quality factor of the two WTs considered QualityAccording to (Figure 10), the Vestas V39/500 has a better quality indicator than Enercon E40, ,and although the latter has fewer components. Then remarkable values exceeded theavailability and quality factor for the geared-drive concept, can be a tendency of choice for geared drivethis type of concept.8. CONCLUSIONThis study supports such a choice of solutions in this important phase in the life cycle of aproduct by an analysis based on the criteria of greater weight in determining the quality of the alysissystems. The quality index calculated in this paper allows excluding invalid solutionstherefore not send tests on physical prototypes as solutions that are more able to succeed with succethe least modifications.It is not possible to conclude definitively whether the direct-drive or geared-drive WT are the drivemost reliable, but the proposed method of analysis shows a way to compare the two conceptsreliability point of view. The analysis indicates the importance of data reliability of analycomponents in determining the overall reliability. 161
  13. 13. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 1, January - February (2013) © IAEMEBased on these data and models of reliability, the availability analysis of these concepts couldbe made to improve the decisions, and thus help to the choice of solutions for this designphase in order to improve future designs.The reliability analysis of WT stresses the importance of gathering and processing reliabilitydata from wind farms around the world. As more reliability field data become available, moreaccurate judgments could be made about different concepts, design improvements andmaintenance strategies.The approach to the design of the gearbox was changed in recent years, after the technicalstandard AGMA 6006 is introduced to the gearbox, which should improve the reliabilityindices for the future of geared-drive WT. [15]BIBLIOGRAPHIES[1] Sallaou. M, Thèse « Taxonomie des connaissances et exploitation en conceptionpréliminaire » –application à un système éolien-. ENSAM CER Bordeaux. 2008[2] Sallaou. M, Pailhès. J, Nadeau. J.P, « Taxonomie des connaissances en conceptionpréliminaire », CFM 2009, 02-03/08/2009, Marseille, France.[3] Arabian-Hoseynabadi. H, Tavner. P.J. Oraee. H, “Reliability comparison of direct-drive andgeared drive wind turbine concepts”. Wind Energ. 2010; 13:62–73 c 2009 John Wiley & Sons,Ltd. DOI: 10.1002/we.[4] Vestas, GE and Enercon Data sheets. Available from manufacturer’s websites:http://www.vestas.com ; http://www.enercon.de/en/home.htm ; (All accessed 11 July 2009).[5] Tavner. PJ, Xiang J, Spinato F. “Reliability analysis for wind turbines”. Wind Energy 2007;10: 1–18. Published online 12 July 2006 in Wiley Inter-science DOI: 10.1002/ we.204.[6] Billinton. R, Allan RN, “Reliability Evaluation of Engineering Systems”, (2nd edn). PlenumPress: New York, 1996.[7] Savransky. S.D, "Engineering of creativity: Introduction to TRIZ Methodology of InventiveProblem Solving", CRC Press, 2000.[8] Jérôme. P, Sallaou. M, Nadeau. J. P, Fadel. G. M, “Energy Based Functional Decompositionin Preliminary Design”, Journal of Mechanical Design, copyright© 2011 by ASME, May 2011,Vol. 133/051011-1.[9] LWK Schleswig-Holstein, Germany. (Accessed 29 June 2009): http://www.lwksh.de/cms[10] WS (WindStats). [Online] Available (Accessed 29 June 2009): http://www.windstats.com[11] Spinnler. G, «Conception des machines Principes et applications». Presses Polytechniques,Université Remands: 2001[12] Harrison. R. Jenkins. G. “Cost Modeling of Horizontal Axis Wind Turbines”, (Phase2),ETSU W/34/00170/REP, University of Sunderland, 1994.[13] Fingersh. L, Hand. M, Laxson. A. Technical Report NREL/TP-500-40566 December 2006.[14] ANSI/AGMA/AWEA 6006-A03,”Standard for Design and specification of gearboxes forwind turbines”; Published by the American National Standards Institute.[15] Zaghar. H, Sallaou. M, Chaaba. A, “Preliminary design support by integrating a reliabilityanalysis for wind turbine”, 2012,4,233-240 doi:10.4236/epe.2012. 44032 Published Online July2012 (http:/www.SciRP.org/journal/epe)[16] Haider M. Husen , Laith O. Maheemed and Prof. D.S. Chavan, “Enhancement Of PowerQuality In Grid-Connected Doubly Fed Wind Turbines Induction Generator” InternationalJournal of Electrical Engineering & Technology (IJEET), Volume 3, Issue 1, 2012, pp. 182 - 196,Published by IAEME. 162

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