Pergamon Microelectron. Reliab., Vol. 35, Nos 9-10, pp. 1285-1307, 1995
Copyright © 1995 Elsevier Science Ltd Printed in Great Britain. All rights reserved
0026-2714/95 $9.50+.00
RELIABILITY ANALYSIS IN WIND TURBINE ENGINEERING
A.J. Seebregts 1, L.W.M.M. Rademakers 1, and B.A. van den Horn 1
Abstract Wind turbines are being designed in accordance with deterministic design rules. As wind turbines increase in size and power, these rules may not be adequate to ascertain a safe and well balanced design. Wind turbine industry can take advantage of the safety and reliability practices in e.g. aerospace, nuclear and offshore industry. These practices include System Reliability (such as FMECA, Event Sequence Analysis and Fault Tree Analysis) and Structural Reliability methods. The approach to introduce Probabilistic Safety Assessment (PSA) which incorporates these reliability methods into wind turbine engineering will be described. By means of two recent case studies, the applicability, benefits, and limitations of these methods will be illustrated.
1 .Introduction
Wind turbines are being designed in accordance with deterministic design
rules, e.g. [Van Hulle, 1991, IEC, 1992, Stare et al., 1991, RISO, 1992,
Germanisher Lloyd, 1993]. These rules concern the design of main
components e.g. blades, hub, and tower, and the design of safety
systems. As wind turbines increase in size and power, these rules may
not be adequate to ascertain a safe and well balanced design. They
neither facilitate the quantification of the degree of conservatism in the
applied safety margins nor explicitly address the reliability and safety of
the wind turbine. While in the past, small wind turbines could be
developed with trial and error, this approach seems not adequate for the
development of large wind turbines. A failure of a large wind turbine may
have severe consequences. The approach of trial and error is also not
adequate for mass produced wind turbines. Numerous design
modifications realized after installation appear to be very expensive for
Netherlands Energy Research Foundation ECN, P.O. Box 1, NL- 1755 ZG Petten, The Netherlands
1285
1286 A.J. Seebregts et at.
manufacturers. For the development of large or mass produced wind
turbines, analytical and systematic tools to improve safety and reliability
become more and more important. Even with the additional costs of a
PSA, it is expected that the cost benefit ratio of such an analytical and
systematical approach is better than the traditional trial and error
approach.
Furthermore, the local and national authorities ask more and more for an
evaluation of the safety and risks of industrial activities. In the
Netherlands for instance, this evaluation should include a quantitative
judgement of safety and risk. Criteria for safety and risks are defined in
[VROM, 1990]. For the siting of new wind turbine parks, the safety and
risk should be evaluated also, as part of a so called 'Environmental Impact
Report' [MER Commission, 1993]. Moreover, on a competitive market,
utilities will easier choose wind turbine designs for which a safety and
risk analysis has been performed, as an advantage compared to those for
which no such analyses have been performed.
Thus, the application of PSA seems inevitable to assess the risk of wind
turbines or wind turbine parks. In the past, several reliability analyses
have been performed for wind turbines with a limited scope. Applied
methods were FMEA [USDOE, 1979, Bollmeier, 1981], Fault Trees
[Petersen et al., 1990], and environmental risk assessment (conditional
upon blade failure) [Montgomerie, 1982, Turner, 1986]. The PSA
methodology outlined here integrates these and other methods to enable
a more complete assessment of a wind turbine design.
2. Development phases for introduction of psa
To introduce the PSA methods into wind turbine engineering,
following development phases have been or are to be carried out:
the
Reliability analysis 1287
Phase 1 : Development of Methodology
The feasibility of reliability based methods in wind turbine engineering has
recently been demonstrated in the project 'PSA of Wind Turbines'
[Rademakers et al., 1992, 1993], carried out under a joint contract of
NOVEM (Netherlands Agency for Energy and Environment) and the CEC
DG-XII (Commission of the European Communities DG XII for Science,
Research, and Development), see section 3.1.
Phase 2: Verification of Methodology
ECN is presently performing a project called 'Reliability Analysis and
Design Review of the NEWECS-45'. The NEWECS-45 wind turbine is the
only 1 MW machine installed in the Netherlands. It is equipped with two
lightweight glass fibre reinforced plastic rotor blades, an integrated drive
train and a soft tower design. Furthermore, the machine has some unique
control features, namely fast blade pitch adjustment and variable rotor
speed. The machine is in operation since 1985. During the first period of
operation, a measurement program has been performed, so the system
performance and characteristics are known. Furthermore, operating
experience is documented in log books and failure registration forms over
the full period. The availability, and thus the actual energy production,
appears to stay far behind the preliminary estimates, due to technical
troubles. One objective of the study is to increase the availability, to
assess the reliability of important components, and to reduce the
maintenance costs. The other objective is to refine and improve the
methodology for PSA of wind turbines. This project will be finished in
1994.
Phase 3: Technology Transfer
The groups that can benefit from the PSA methods are designers and
manufactures of wind turbines, utilities, and certifying bodies. In wind
turbine industry, the knowledge about these methods is now mostly
1288 A.J. Seebregts et al.
present at research institutes. The best way to transfer knowledge is by
means of case studies tailored to the specific interests and needs of the
different groups. In the Netherlands, case studies are planned on the
short term. ECN has recently performed an analysis of an American wind
turbine, the AOC 15/50 [Carter et el., 1993], see section 3.2.
Phase 4: Development of Guidelines, Standards, and Criteria
ECN wil l take initiatives to introduce the PSA methods in the national and
international wind turbine standards. These methods should be used to
further underpin the currently used safety factors, to detail the
requirements for wind turbine safety, and the design of safety systems.
The development of guidelines, standards, and criteria will be done in
close cooperation with other international research institutes and
manufacturers.
3. Methodology and examples
3.1 LW 15/75 Case Study
The methodology has been applied on a mass produced, medium size
wind turbine, the LAGERWEY LW 15/75 design [Rademakers et el.,
1993], see Fig. 1. It describes how to assess the safety, reliability, and
availability in a more integrated and quantitative way, very much
structured analogously to PSAs for Nuclear Power Plants [IAEA, 1992].
The case study has focused on safety and availability mainly. The extent
to which the methodology can be implemented in the current design
practices on the short term and the areas that require further research
have also been indicated. The subsequent tasks and are briefly discussed
below.
Task 1: Description of System Design and Operation
Before starting a detailed analysis of a wind turbine, it is necessary for
the reliability analyst(s) to become familiar with the specific wind turbine.
Reliabil i ty analysis 1289
, 101 I t l
[. Rotor
2. Blades
3. Gcazbox
4. Generator
5. Yaw ruolor
6. Wind vane 7. Nacelle 8. Step 9. Tower
tO. Worm geart~x of yaw drive
Figure 1- Main components of the LW 15/75
This should result in a detailed description of the system design and
operation, including maintenance, test and inspection procedures, and
design modifications. State Diagrams and Event Trees have been used to
explain the control and safety actions.
The Lagerwey LW 15/75 wind turbine is equipped with an upwind, two
bladed rotor that has a diameter of 15.6 m. The rated electrical power of
75 kW is produced with an asynchronous generator at wind speeds
between 3 and 30 m/s. The power control is realized by pitch control of
the blades towards feather position in combination with a variable rotor
speed. This power control method requires a fairly complex electrical
1290 A.J. Seebregts et al.
system, which is tuned with the passive blade pitch control mechanism.
It is recommended by the manufacturer to shut-down the turbine
manually at wind speeds over 30 m/s by yawing the nacelle such that the
rotor is at 150 degrees towards the wind direction. The nacelle is placed
on a steel tower of a length that can be either 24, 30 or 36 meter. In
order to ensure safe operation the wind turbine is equipped with two
independent and diverse safety systems, viz. a passive blade pitching
mechanism, and a yaw mechanism.
Generally, the control systems of the LW 15/75 have to keep the wind
turbine within its design limits during normal operation and to ensure
electrical energy is generated and supplied to the grid in an efficient
manner. In case of a failure or in case of abnormal external conditions,
the control systems in combination with the safety systems have also to
keep the turbine within its design envelope to prevent damage or unsafe
operation. For a clear description of the wind turbine operation, a State
Diagram has been made. A distinction has been made between
Operational (O), Transitional (T), and Damaged (D) Modes. The State
Diagram enables a clear presentation for the relationships between the
different wind turbines modes (or states), see Fig. 2.
The safety systems of the LW 15/75 will be activated in case of the
following events: an overspeed situation, excessive vibration, overload of
the generator, loss of load, too high inverter temperature, and abnormal
cable twist which have all been considered in the case study. In case of a
normal shut-down (T4), the nacelle will be yawed out of the wind; the
yaw motor is activated by the grid. In case of an emergency shut-down
(TS), the yaw motor is powered directly by the generator. This happens
for instance during grid failure (S5).
Task 2: FMECA
From the FMECA, a set of critical component failures and initiating events
has been derived. This survey has been used to check the measures the
Reliability analysis 1291
° .
Re~t
" ~ "'"",,,\\ Su~-up I St°P I
J
AVAILABLE . - " I "4
!
I N o r m a l
- - $ h u ¢ - d o w n
Emc~ncy Shut-dovm
l Figure 2: State Diagram of the LW 15/75.
manufacturer has taken to prevent these failures and events from
happening or to reduce the likelihood. Since Lagerwey has a long term ex-
perience with this type of turbine, most of the preventive measures
conceived during the FMECA had already been realized, either as a design
modification, or by changing the maintenance procedures.
Task 3: Event Sequence Analysis and System Modelling
The event sequence analysis involved safety actions leading to
unavailability of the wind turbine. The analysis has focused on the
1292 A.J. Seebregts et al.
operational modes 'Idling', 02, and 'Energy Production', O3, and on the
transitional modes 'Normal Shutdown', T4, and 'Emergency Shutdown',
T5. These modes are the most important with respect to the
unavailability and safety of the wind turbines. For the event sequence
analysis and system modelling, techniques have been used like event
trees, see Fig. 3, and fault trees, respectively.
From the qualitative analyses, unbalances were found in the design of
safety systems. Excessive vibration had the lowest level of defence, viz.
a single failure.
Task 4: Data Collection and Parameter Estimation
Maintenance and failure data have been derived partially from
maintenance sheets, audits, and logbooks. In addition, generic data
contained in reliability data handbooks, European, and American wind
turbine databases, and engineering judgment have been used to finally
arrive at the parameters required for the quantification process (see next
task) and to compare the specific LW 15/75 failure data with. The
operational data have been derived from logbooks, measurements, and
function tests. The data of 11 turbines have been collected and analyzed,
representing operational experience of about 26 years. Limitations
showed up in the current practices of data collection. Not all types of
data required for reliability purposes have been recorded. Despite these
shortcomings, both useful qualitative and quantitative information has
been derived from the available operational experience. In general, the
component failure frequencies of the LW 15/75 compared favourably to
the reported generic wind turbine data.
Task 5: System Reliability Quantification
The fault trees and event trees developed in Task 3 have been quantified
with the failure rates, initiating event frequencies, and downtimes,
estimated in Task 4. Estimates have been obtained of safety system
Reliability analysis 1293
unavailabilities and wind turbine unavailability. Components contributing
to the safety system unavailabilities have been ranked according to their
importance in order to identify possibly weak points in the LW 15/75
design, to highlight unbalances, and to indicate effective areas for
improvement. The end states of the event trees have been quantified by
multiplying the probabilities of the successive events, see Table 1 and
Fig. 3.
Table 1: Initiating Events and Frequencies of End States
Initiating Event Frequency [/yr]
Frequency End State [/yr]
Shutdown Not Shutdown Not Shutdown No Damage Partial Damage Severe Damage
$10verspeed 0.65 6.5E-1
$2 Excessive Vibration 0.95 9.3E-1
$3 Inverter Temperature 0.038 3.8E-2
$4 Inverter Control 0.23 2.2E-1
$5 Grid Failures 3.12 2.98
$6 Generator Overload 0.42 4.0E-1
Total 5.408 5.21
3.2E-3
2.3E-2
4.7E-4 4.2E-6
1.1E-2 9.6E-5
1.4E-1 1.2E-3
2.3E-2 2.1E-4
0.17 0.028
Yaw System
Pitch Control System
End State:
$5. Grid failures (3.12/yr)
StlCC~k~
I (0.956)
failm~
(0.9911)
I (0.044)
(0.0089)
Figure 3: S5 event tree quantification
S-ND (3.0 ~)
NS-PD (0.14/yr.)
NS.SD (0.0012/yr)
1294 A.J. Seebregts et al.
The results show an estimated severe damage frequency of 1 per 35
wind turbine operating years. Partial damage with no safety implications
occurs approximately once in 6 years. Successful shut-downs occur 5
times per year. Especially failure of the detection units (e.g. tachometer
and vibration detection) contribute to the damage frequencies. This is
because there is no redundancy in these components.
Task 6: Structural Reliability
The possible application of probabilistic techniques for the assessment of
the structural integrity of wind turbine components has been investigated.
For the structural reliability analysis, four levels can be identified [de
Kraker et al.]:
• Level O: A deterministic analysis based on fixed data, a deterministic
(high) load, a deterministic (low) strength, and an 'overall-safety' factor.
• Level I: Intended for routine design use. For each stochastic variable, a
certain unfavourable value is chosen, the so-called characteristic value,
usually based on a 5% confidence limit. In addition, a set of partial safety
factors is applied, which establish the margin between load and strength
for the various cases to be considered. This approach is yet commonly
used in wind engineering.
• Level I1: An approximative analysis based on the so-called 'f irst
order/second moment' principle. Briefly, what it amounts to is that only
the mean value and the standard deviation of each stochastic variable are
taken into account, linearization being applied when necessary. Level II
approximations are used to provide a basis for Level I procedures. Level II
studies aim to underpin the partial safety factor of a Level I analysis as
soundly as possible. Moreover, they are used for special and important
structures for which an above-normal standard of reliability is considered
essential, e.g. offshore structures.
• Level II1: Comprises complete and exact analyses using analytical or
numerical procedures or Monte Carlo simulations. Level III analyses
Reliability analysis 1295
generally demand too much computational effort to be practical for
dealing with major problems due to the large number of stochastic
variables to be considered. The scope for applying them exists mainly in
verifying and complementing Level II approximations.
To demonstrate structural reliability applications on wind turbines, fatigue
failure of the tower foot has been selected. Normally, only the stochastic
nature of the wind speed is incorporated in a deterministic fatigue
analysis. A probabilistic analysis provides a manner to deal with the
stochastic behaviour of the most important problem variables more
realistically than with the use of prescribed safety factors. The procedure
for a probabilistic fatigue analysis of the tower foot is based on
[Karadeniz et al., 1984, Ang and Tang, 19841. A reliability function Z
must be selected in a deterministic way as to establish that Z < 0
corresponds to fatigue failure and Z >_ 0 to non-failure, and the limit state
is given by Z = 0. Z is related to the Miner sum D and Z = 1 - D has
been chosen. After the distributions are selected and the reliability
function is defined, the failure integral must be calculated. The most
accurate computational procedure for the probabilistic fatigue analysis is
presented in Fig. 4.
load structure material properties (wind) (wind turbine) (fatigue)
~ b a s ~ l e s
D
Figure 4: Determination D and the fatigue failure probability.
1296 A.J. Seebregts et al.
When the influence of the uncertainties in load, geometry and material
properties are considered, it is possible to make a frequency table for D.
This can be achieved by the combination of every possible value of the
basic variables in the calculation of D. Subsequently, a distribution of D
has to be selected and the statistical parameters have to be determined.
The probability of fatigue failure can be expressed as
and can be determined for the IogC-value associated wi th a line in the
WShler-diagram. A normal distribution is selected for IogC in
correspondence wi th off-shore industry. However, it is practically not
possible to evaluate the frequency table for D, because the load
calculations wi th SWIFT [Winkelaar, 1992] and PHATAS-II [Lindenburg,
1992] are too t ime-consuming. Therefore, the failure integral (1) is
approximated wi th the Mean Value Approach (MVA), which is a simple
application of a Level II method.
In a general formulation for MVA, the reliability function is a funct ion of
the problem variables including a number of stochastic variables here
given the designation X1, )(2 ..... X,. The stochastic variables are assumed
to be uncorrelated, mutually independent and normally distributed wi th
known mean values/1,- and standard deviations a;. When Z is linearized in
the mean values of the stochastic variables, the mean value #z and the
standard deviation az of Z can then be approximated by the expressions
~/Z =Z(~ /1 ,/J2, • • " ,/Jn ) = 1 -D (Pl ,P2, • • • ,P,) = 1 -Po (2)
az = az (p l ,gz . . . . . p,)ai i .1
The partial derivatives in (3) cannot be determined analytically and are
Reliability analysis 1297
therefore numerically approached
az ~ Z(/zl ,#2,... ,p;+o;, . . . ,p , ) -#z = .bZ~ (4)
In this particular case, the partial derivatives in (3) can be approximated
by _ a z ~ D(IJ1 , I J 2 , . . . , I J i + o ' i , . . . , P , ) - P o = A D i (5)
a Xi a i (>,
The standard deviation of Z is then given by
Oz = i ;-' (6)
and the reliability index B can be written as
= __Pz = 1 - P o
az I ; (71 (AD;)2
=1
Now, the failure
derived
probability of the welding in the tower foot can be
P~ = q)N(-B ) (8)
where (I)N is the standard normal cumulative distribution function. For
positive # it appears that the larger p, the larger the safety. The
importance factors a7 are defined by the squares of the direction cosines
of # and can be expressed as: = (~Oi)2 (9}
var Z
They are a measure for the percentage of variability due to each random
variable.
1298 A.J. Seebregts et al.
A selection has been made of wind parameters, wind turbine parameters,
and fatigue parameters which are considered to be stochastical instead of
fixed and deterministic. Table 2 lists the parameter means and standard
deviations, which have been derived from measurements or based on
engineering judgment.
Tabel 2: Stochastic variables and results
i Designation xl Pi ai (a/p) i
1 Turbulence alU~o 19.28 % 1 % 0.052 intensity
2 1st tower f,~., 0.97 Hz 0.049 Hz 0.050 e i g e n f r e q u e n c y
3 maximum lift C~,,= 1.60 0.04 0.024 coefficient
4 torsion spring Mp,=h,,= 730 Nm 50 Nm 0.068
5 load level Model 1.0 0.125 0.125 uncertainties
6 wall thickness t,,= 10 mm 0.5 mm 0.050
7 constant of S-N logo 12.511 0.207 0.017 c u r v e
8 annual average U,,, 7.28 m/s 0.728 m/s 0.100 wind speed
i Po + L~9i EO, =
1 0.2225 0.0009
2 0.1818 0.0001
3 O.1770 0.0003
4 0.2081 0.0002
5 0.2748 0.0067
6 0.2235 0.0009
7 0.3109 0.0139
8 0.3124 0.0142
Po = 0.1930
Pz = 0.8070
a z = 0.1929
/9 = 4.18
Pc = 1.4E-5
The importance factors are displayed in Fig. 5.
It appeared that the fatigue coefficient IogC and the average annual wind
speed Uo., are by far the most important sources of variability, followed
Reliability analysis 1299
by the model uncertainties.
o/r.~,, 2.3% model uncertainties
log C
37.3%
18.0%
4
_-_ _~_ _ _ " - ~ _ |
~ 0.6% M~m~,(4) 0.7% C,._. (3)
38.3% 0.3% f,,,, (2)
u= 2.s% t . (l)
Figure 5: Importance factors obtained with MVA
Summarizing, MVA in addition to the currently used deterministic design
rules gives qualitative insights in the uncertainties of the fatigue damage
calculations. MVA appeared to have limitations, but a further application
of probabilistic design techniques is strongly recommended. The speed of
the load calculation codes and the probabilistic techniques need to be
improved for actual implementation in the design and certification
process.
However, the process of identifying components, failure modes, and a list
of uncertain parameters for each combination is expected to be more
troublesome and time-consuming than the actual calculational procedure.
The first emphasis should therefore be on this initial step, because it also
affects the results of the current deterministic structural analyses. In
addition, Monte Carlo procedures, in particular Latin Hypercube Sampling
(LHS) [Imam, 1984], is worthwhile investigating. Although perhaps time-
consuming, this procedure has advantages compared to Level II methods
like MVA, viz.:
- parameters can be varied simultaneously and correlations can be
HR 35 :9 /10 -G
1300 A.J. Seebregts et al.
taken into account;
- PF can be derived directly and is not dependent of a (non-robust)
definition of Z; and
- no assumptions are needed on the normality of parameter or PF
distributions.
For more details, see [Rademakers, 1993] or [Van den Horn, 1993].
Task 7: Interpretation and Discussions of the Results
It has been concluded that there are unbalances in the safety systems
design. Excessive vibration of the nacelle had the lowest level of defence
(only the yaw system) and contributed the most to the severe damage
frequency. If safety is to be improved, modifications can best be focused
on the improvement of the detection units. A strong improvement of the
wind turbine availability can be made by, under certain conditions,
automatic resetting, which causes the downtimes to decrease. The
presented estimates for the safety system unavailabilities, the wind
turbine unavailability, and the damage frequencies should be considered
as approximate values because of the data and modelling uncertainties.
The results are based on assumptions which depend on certain external
conditions, as given by the site of the wind turbine, and operating
procedures. These assumptions may be different for other sites. The
event tree and fault tree models can be easily recalculated for those sites,
if site specific data is available. Sensitivity analyses have been performed
to show the robustness of the conclusions.
The system reliability analysis results are valid for the so-called 'useful
life' period where failures are random and component failure rates are
more or less constant. Reported gross failures (from other than the 1 1
units) which have resulted in hazardous situations appeared to be caused
not by random failures during the useful life period, but were mostly the
result of unexpected situations not foreseen in the design stage.
Especially, activation of the yaw mechanism at high wind speeds was
Reliability analysis, 1301
found to be critical. In early designs, this situation led to excessive
vibrations and high loads. The phenomena causing these effects were not
known in the design phase. A load and operation monitoring programme
together with the analysis of more load situations are strongly
recommended to gain more insights in the dynamic behaviour of the
turbine and to reduce the occurrence of these failures. To improve the
safety at high wind speeds, it is recommended to enhance the yaw
mechanism or to add an extra safety device. Otherwise, it is
recommended to install an anemometer that causes automatic shut-down
at lower wind speed.
3.2 AOC 15/50 Case Study
Atlantic Orient Corporation (AOC, USA) is presently developing the AOC
15/50 wind turbine. This turbine is derived from an existing mass
produced wind turbine, the ENERTECH 44. Based on experienced failures
of this design, AOC has conceived design modifications to enhance the
structural integrity, to improve the reliability and to reduce the
maintenance costs. This update led to some unique and innovative
features, viz. an integrated gearbox design, the tip brake design, and the
procedures for normal and emergency shut down. Since the AOC 15/50
is at the very end of the design phase and at the beginning of the testing
phase, ECN has performed a qualitative reliability analysis in close
co-operation with personnel of AOC [Carter et al., 1993]. In addition, the
safety systems have been assessed qualitatively. Tasks 1, 2, and 3 have
been performed. The major part of the analysis consisted of an FMECA of
the improved and innovative components and systems. The transitional
modes, e.g. start up, normal shut down, and emergency shut down, have
been analyzed with event trees to determine possible critical items in
these event sequences. The analyses are yet not finished so only partly
results can be given here. The FMECA:
- estimated the likelihood, and thus the criticality, of failure modes
1302 A. J. Seebregts et al.
of innovative components rather high. Reliability demonstration
testing and prototype testing must prove that the actual likelihood
of a failure mode is lower than the first estimate; and
indicated that no active protection system had to be installed to
prevent excessive cable twist. This is required by e.g. the Dutch
certification criteria [Stam et al., 1991]. From the reported failures
of the similar ENERTECH 44 design, it appeared that the likelihood
of cable twist is very low, which could be underpinned from
reliability demonstration testing of the power cable. Furthermore,
no effect with a high severity could be conceived. The criticality of
this failure mode was thus rather low.
lead to unsafe
In addition to the FMECA, the event tree analyses:
- did not identify any single failure that could
operation of the turbine; and
- completed the list with load situations
situations presented in the current
appeared to be too generic for this specific turbine.
and showed that load
deterministic standards
4. Uncertainties and acceptance
in areas where new techniques are introduced, people must be convinced
of the added value of the new methodology. E.g., for Psa for nuclear
power plants [hirschberg, 1992], there is sometimes criticism on the
usefulness of these techniques because of the uncertainties. For wind
turbine application, similar uncertainties exist. The most important
insights provided by a psa are engineering ones, i.e., those related to the
identification of potential design weaknesses. In many cases, once such
insights have been obtained the value of the predicted frequencies
involved becomes less important. Such 'relative' results of psas are
usually not undermined by the numerical uncertainties involved.
Moreover, it should be noted that one of the strengths of psa is to show
the limitations and uncertainties that still exist. One rarely observes this in
Reliability analysis 1303
the standard deterministic analyses. In addition, the systematic nature of
the process already leads to valuable insights and a better understanding
of the design just by doing the exercise. Of course, the (numerical)
results of psas should also be used with caution both in the design,
regulatory and certification process. Probabilistic analyses applied for
regulatory and certification purposes have been introduced in other indus-
tries after a period of familiarization and obtaining experience. For wind
turbine industry, requirements should also not be hastened, and the
emphasis should first be on the qualitative analyses.
5. Conclusions and recommendations
based on the experiences of the Iw 15/75 and aoc 15/50 case studies,
the following conclusions can be drawn on the methodology:
feasibility
the short term benefits of system reliability analysis (thorough system
description, state diagrams, fmeca, event tree and fault tree analysis)
have been proven. Probabilistic analyses constitute a necessary
supplement to the existing deterministic analyses and design rules in
order to achieve a more balanced and safe design. Qualitative analysis
methods can and should be applied immediately.
Limitations
in addition to deterministic analyses, probabilistic analysis techniques are
not the only means to further enhance safety and reliability. There is still
a fundamental lack of knowledge of physical phenomena in wind turbine
engineering that may cause hazardous situations, e.g. excessive
vibrations. Even when these phenomena are known, quite often they
cannot be adequately modelled with the current computer codes. It is
therefore highly recommended to perform analyses of additional load
situations during the design stage and to use measurement, test and
1304 A.J. Seebregts et al.
monitoring programmes during the early operational phase of a wind
turbine. The results of these programmes can be used for updating the
design process.
Data collection and analysis
in view of limitations in the current practices of data collection, priority
must be given to a systematic collection of data, not only concerning
maintenance and failure data (component failures, downtimes, failure
causes, etc.) but also concerning operational data (external conditions,
starts and stops, etc.). Computerized data collection systems are
recommended to prevent these time-consuming, partly manual efforts.
Qualitative insights and trends can be derived very easily. On the longer
term, reliability data for quantitative analyses (e.g. optimizing
maintenance procedures) can be obtained. Each manufacturer must set
up his own data collection system, preferably computerized. Such a data
base can play an important role in the planning of maintenance and for
the improvement of reliability and availability of the considered wind
turbine. A central data base with accidents and incidents must be
maintained to assess the safety and risks for the environment, to adjust
the rules for siting, and to sharpen the current design rules.
Certification
on a short term, the certification institutes can especially benefit from
qualitative analysis methods. The systematic approach and presentation,
e.g. state diagrams and event trees enable a direct insight in the
operation of the considered wind turbine. Fmecas performed by the
designers provide a survey of critical events which the certification
institutes can review during the certification process. At this moment, the
critical events are often conceived by the certification institutes
themselves in a more or less unstructured way. They should therefore ask
at least for the results of an fmeca. In addition, quantification of the
Reliability analysis 1305
safety system unavailabilities will be necessary for evaluating safety
concepts that differ from the deterministic safety concept as described in
the dutch certification criteria.
Safe operation of a wind turbine is not only determined by its design and
manufacturing process but also by the operating, maintenance and
inspection procedures. These procedures are considered in the
certification process but only in a limited fashion. During the operating
phase of a wind turbine, no check is made to see if these procedures are
applied correctly and to see if the wind turbine is in a 'healthy' state. In
the certification process, more attention should be paid to these
procedures, preferably by asking for checklists and using reliability
analysis techniques.
Structural reliability
although the demonstrated mva for the structural reliability analysis of
mechanical components appeared to have limitations, a further
application of probabilistic design techniques is strongly recommended.
The application of the mva in addition to the currently used deterministic
design rules gives qualitative insights in the uncertainties of the fatigue
damage calculations. Fruitful discussions in wind turbine industry which
must lead to a wider acceptance and introduction of probabilistic design
techniques can be generated only if these techniques are wider applied,
parallel to the improvement of the methodology and the identification and
quantification of uncertain parameters. In the near future, more advanced
probabilistic techniques should be used to further underpin or adjust the
currently used safety factors.
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