U.S. patent application number 09/802044 was filed with the patent office on 2002-01-03 for control system for a wind power plant.
Invention is credited to Weitkamp, Roland.
Application Number | 20020000723 09/802044 |
Document ID | / |
Family ID | 7634034 |
Filed Date | 2002-01-03 |
United States Patent
Application |
20020000723 |
Kind Code |
A1 |
Weitkamp, Roland |
January 3, 2002 |
Control system for a wind power plant
Abstract
Control system for a wind power plant A control system for a
wind power plant comprises sensor means for the detection of
measurement values to be used for direct or indirect quantification
of the current loading and/or stress of the turbine occurring in
dependence on the local and meteorological conditions. Downstream
of said detection means, an electronic signal processing system is
provided, operative to the effect that the power reduction required
in the optimized condition of the wind power plant will be
restricted to obtain optimum economical efficiency under the
current operating conditions, both in cases of winds in the range
of the nominal wind velocity and in cases of high wind
velocities.
Inventors: |
Weitkamp, Roland; (Belm,
DE) |
Correspondence
Address: |
Michael J. Mallie
BLAKELY, SOKOLOFF, TAYLOR & ZAFMAN LLP
Seventh Floor
12400 Wilshire Boulevard
Los Angeles
CA
90025-1026
US
|
Family ID: |
7634034 |
Appl. No.: |
09/802044 |
Filed: |
March 7, 2001 |
Current U.S.
Class: |
290/44 |
Current CPC
Class: |
F05B 2270/332 20130101;
F03D 7/042 20130101; F05B 2270/20 20130101; F03D 7/0292 20130101;
F03D 7/0276 20130101; Y02E 10/723 20130101; F05B 2270/1016
20130101; F05B 2270/32 20130101; F05B 2260/821 20130101; Y02E 10/72
20130101; F05B 2270/331 20130101; F05B 2270/504 20130101; F03D
7/043 20130101; F05B 2270/322 20130101; F03D 7/048 20130101 |
Class at
Publication: |
290/44 |
International
Class: |
F03D 009/00; H02P
009/04 |
Foreign Application Data
Date |
Code |
Application Number |
Mar 9, 2000 |
DE |
100 11 393.1 |
Claims
1. A control system for a wind power plant, comprising: sensor
means for sensing measurement values to be used for direct or
indirect quantification of the current loading or stress, or both,
of the turbine occurring depending on the local and meteorological
conditions, and downstream of said sensor means, an electronic
signal processing system operative to the effect that the power
reduction required in the optimized condition of the wind power
plant will be restricted to obtain optimum economical efficiency
under the current operating conditions, both in cases of wind in
the range of the nominal wind velocity and in cases of high wind
velocities.
2. The control system according to claim 1 wherein the wind power
plant is designed for blade adjustment in the direction of the
feathered pitch (pitch-type plant).
3. The control system according to claim 1 wherein the wind power
plant is a stall or active stall plant.
4. The control system according to claim 1 wherein the wind power
plant is designed for variable-speed operation or for at least two
fixed operating speeds.
5. The control system according to claim 1 wherein the measurement
values monitored by said sensor means include one or a plurality of
the values of the operating data from the group including the rotor
speed, the generator speed, the electric power, the generator
rotational moment, the blade angle, the blade angle adjustment
rate, the wind velocity and the wind direction.
6. The control system according to claim 1 wherein the measurement
values monitored by said sensor means include accelerations in the
rotor blades and/or the nacelle and/or the tower.
7. The control system according to claim 1 wherein the measurement
values monitored by said sensor means include stretching on
representative points of the components (e.g. the blade roots,
rotor shaft, the nacelle base, the base of the tower) or
deformations in elastic bearings.
8. The control system according to claim 1 wherein the measurement
values monitored by said sensor means include data of the wind
field in or before the rotor plane.
9. The control system according to claim 1 wherein the measurement
values monitored by said sensor means include measurement data from
other wind power plants supplied via a network.
10. The control system according to claim 1 wherein, using a signal
processing system, the measurement values monitored by said sensor
means are processed into actual spectra (online rainflow counting)
or actual distribution functions.
11. The control system according to claim 1 wherein, using a signal
processing system, damages of the components are computed from the
actual spectra.
12. The control system according to claim 1 wherein, using a signal
processing system, desired spectra or desired distribution
functions are computed from externally supplied data on the economy
of the turbine.
13. The control system according to claim 1 wherein, using a signal
processing system, current energy generating costs (online Cost Of
Energy COE) are computed from the evaluated externally supplied
data.
Description
BACKGROUND OF THE INVENTION
[0001] The annual energy output to be obtained by a wind turbine
decisively depends, apart from the performance of the generator as
installed, on the rotor diameter. Thus, for increasing the
efficiency, it is desirable to use rotors of the largest possible
size. However, when enlarging the rotor diameter while otherwise
operating the plant under the same conditions, difficulties arise
because the stresses acting on the rotor, the nacelle, the tower
and the foundation will increase at least by the second power of
diameter. Presently usual ratios between the performance of the
generator as installed and the rotor area (rating) are in a range
from 460 to 330 W/m.sup.2, the latter value pertaining to
pitch-regulated turbines optimized for inland use.
[0002] According to an approach frequently used in wind energy
technology, an existing turbine to be used in sites with weak winds
can be retrofitted to have a larger rotor diameter, with the
switch-off speed being lowered from e.g. 25 m/s to 20 m/s to
safeguard that the stresses will remain in the allowable range.
[0003] Further, in plants with blade adjustment (pitch-type
plants), it is a usual practice to adjust the rotor blades towards
the direction of the feathered pitch already before the rated power
is reached, thus reducing the stresses (particularly those acting
on the tower).
[0004] According to a more complex and longer-known approach for
reducing the above mentioned stresses, the rotational speed of the
rotors and/or the power output of the turbine can be decreased in
case of high wind velocities. For technical reasons (design of the
transmission and/or generator and/or converter), decreasing the
rotational speed of the rotors will have the effect that the power
output is reduced at least according to the same ratio. Since,
however --as widely known (cf. for instance "The Statistical
Variation of Wind Turbine Fatigue Loads", Riso National Laboratory,
Roskilde DK, 1998)--the largest part of the high stresses that tend
to shorten the lifespan will occur at high wind velocities, the
above approach is successfully used particularly at inland
locations for improving the efficiency of wind energy plants.
Particularly at inland locations, use can thus be made of larger
rotors which during the frequent low wind velocities will yield
higher energy outputs but upon relatively rare high wind velocities
will have to be adjusted correspondingly.
[0005] Further, the state of the art (DE 31 50 824 A1) includes an
opposite approach for use in a wind turbine with fixed rotational
speed, wherein, during high wind velocities with merely low
turbulences, the power output of the turbine can supposedly be
increased beyond the rated power by adjusting the rotor blade angle
through evaluation of signals from a wind detector.
SUMMARY OF THE INVENTION
[0006] The above outlined known approach of reducing the power
output in case of high wind velocities makes it possible--e.g. in a
variable-speed pitch plant with a control algorithm for controlling
the rotor speed on the basis of the pitch angle averaged over
time--to obtain very high ratios between the rotor diameter and the
generator performance without an accompanying increase of component
fatigue as compared to conventionally designed turbines. A rating
of 330 to 280 W/m.sup.2 can be obtained and is economically
reasonable especially at inland locations.
[0007] For reasons of safety, the design of the towers of wind
power plants is on principle determined on the basis of very
unfavorable assumptions (e.g. high wind turbulences and maximum
wind distribution in the designed wind zone); therefore, in the
majority of locations, considerable safety margins of the power
output are left unused in the turbines. Thus, the problem exists
how these normally existing safety margins can be utilized for
improving the efficiency of the turbine.
[0008] According to the instant invention, this object is fulfilled
by performing, by means of an already existing or additionally
installed sensor arrangement with connected signal processing
system in the wind power plant, a direct or indirect quantification
of the current turbine stresses. By comparison with allowable
stresses (or correlating values) detected by computation or
empirically, the turbine will always be operated with a rotor speed
and a power yield which are optimized under the economical
aspect.
[0009] Other than in the normally used state of the art wherein the
operational control process is provided to control the blade angle
and/or the rotational speed according to fixed functions in
dependence on power, blade angle or wind velocity, this novel
control process is to be performed only to the extent required due
to the local conditions or meteorological conditions at the
respective point of time to thus obtain optimum efficiency.
[0010] A simple algorithm suited for the above purpose is based on
the statistical evaluation of one, a plurality or all of the
measurement values (e.g. rotor speed, generator performance, pitch
angle, pitch rate, wind velocity and wind direction) mentioned
among those operating data which are anyway continuously detected
in many present-day wind power plants (e.g. variable-speed pitch
plants).
[0011] In the present context, the term "statistical evaluation" is
meant to include at least the continuous detection of the minimum,
maximum and average values and the standard deviation for a
plurality of sliding time intervals .DELTA.t (30 s to 60 min.).
More-complex statistical evaluations of the operating data or the
derivations thereof will result in a more successful control. Since
wind is a stochastically distributed value, a reasonable detection
and arithmetical representation of the measurement values can be
performed only by means of distribution and probability functions
or spectra. On the basis of measurements or simulation
computations, the correlation coefficients of the statistical data
relative to the local and meteorological conditions and the current
stresses on the components can be determined with sufficient
accuracy. For instance, the average pitch angle and the average
rotor speed for a given turbine configuration are in direct
relation to the average wind velocity; the standard deviation of
the two former values allows for a conclusion on the turbulence
intensity (gustiness) of the wind. Thus, besides the directly
measured operating data, also important stress data (e.g. the blade
bending moment and the thrust acting on the tower) can be
statistically evaluated, These actual distributions of the stresses
or of the values directly related thereto are compared to desired
distribution functions which have been obtained by computation or
empirically. These desired functions can be detected for each
location as suited for the specific application and be stored in a
data memory of the control system.
[0012] An example of a preferred embodiment of the control system
using the inventive control strategy will be explained in greater
detail hereunder in connection with the accompanying drawing.
BRIEF DESCRIPTION OF THE DRAWING
[0013] The sole drawing is a block diagram of the control system
using the control strategy according to the instant invention.
DESCRIPTION OF A PREFERRED EMBODIMENT
[0014] In the block diagram, angular boxes are meant to represent
signal processing systems or computing modules of a larger software
package installed in a signal processing system. Laterally rounded
boxes represent input data for the control system, irrespective of
whether these data are measured on the turbine or supplied from an
external source. Boxes curved on top and bottom represent data
stores containing all data which are required for the execution of
the control algorithm and are made available through the internal
data detection or analysis, or are supplied from external data
sources. Elements represented in solid lines are absolutely
required for the control system; elements represented in dotted
lines are optional components which improve the function of the
control system and thus allow for a higher energy yield even though
they will cause an increasing complexity of the control
concept.
[0015] Schematically shown to the left of the vertical dash-dotted
line in the left half of the drawing is a schematic representation
of the control systems used according to the state of the art. The
input values are the operating values provided to be permanently
detected by the measurement sensors, such as the rotor and
generator speeds n.sub.R and n.sub.G, respectively, the electrical
power P.sub.el, the generator torque M.sub.G, the blade or pitch
angle .theta. and the pitch rate .theta.', and the wind velocity
v.sub.w and the wind direction v.sub.dir. On the basis of these
measurement values, the turbine is controlled according to an
algorithm implemented in the main computer for operating the plant
(standard control). The regulated quantities are the pitch angle
.theta. and/or the generator moment M.sub.Gsoll (e.g. also by
selection of the generator stage in asynchronous turbines with
switchable polarity). The control loop wherein, by means of the
actuators, the desired values are turned into actual values which
then will be detected as operational values to be used as control
input values as schematically indicated, has been omitted from the
block diagram for better survey.
[0016] According to the state of the art, additional measurement
values (e.g. temperatures, hydraulic pressures, tower head
accelerations, oil level and wear indications) allow for the
detection of certain conditions of the plant and, if required, will
result in shut-down of the turbine.
[0017] In the inventive control system, the operating data are
subjected to a statistical data pick-up and are stored as spectra
or distributions in a data store. Optionally, In the so-called
loading model, the statistical operating data are converted into
statistical stress data by means of the correlation functions
obtained in the simulation computations.
[0018] More-complex algorithms are based on additional measurement
values which are more closely related to the stresses, and such
algorithms allow for a distinctly more precise detection of the
existing distribution of stresses and thus for a closer approach to
the limiting values dictated by the respective design, thus
obviating the need for the safety margins necessitated in simple
algorithms.
[0019] The sensors on the turbine can be provided, inter alla, as
acceleration sensors on the tower head and the rotor blades, and/or
wire strain gauges on representative points of the support
structure (e.g. on the blade roots, rotor shaft, base of the
tower).
[0020] By inclusion of additional wind-field data which in the
ideal case characterize the undisturbed on flow before the rotor,
the control behavior can be considerably improved. Generally, for
this purpose, use can be made of laser-optical and/or acoustic
(ultrasonic) measuring methods which are suited both for
measurements on individual points in the wind field and for
measurements of complete wind profiles or wind fields in the rotor
plane or also far before the rotor plane. A further improvement of
the control behavior is accomplished by linking the control systems
of the different turbines of a wind park to each other; the
considerably enlarged data base obtained in this manner will
safeguard a faster but still statistically reliable response of the
control systems.
[0021] All of the detected spectra or distributions will be stored,
preferably classified according to operating year, average wind
velocity and turbulence intensity.
[0022] Upon sufficiently accurate determination of the stresses
through detection of stress data, it appears reasonable to
transform the stress changes into so-called Markov matrices by use
of known counting methods or on the basis of the average values
(online rainflow counting). To this end, microchips which have
already entered the stage of industrial production are available
from the field of aviation and space technology.
[0023] The distributions which have been measured or have been
computed from the measurement data are compared to the desired
distributions of the same values. For this purpose, data on design,
planning and financing are externally collected, input into the
system and stored in a data store. Using an economy model, the
desired distributions are derived from these data. Design data
include e.g. the allowable loading distributions for the individual
components; an example of the planning data is the expected wind
distribution at the location; and the financing data include, in
addition to the overall project costs, the current credit costs,
the energy profits required according to the financing plan, and
the current charges for power supply. Monthly updates of these data
per remote monitoring can be used for immediate adaptation of the
control system to changes of the basic conditions, e.g. to changes
of the charges for power supply or of the financing costs, new
recognitions on the allowable stresses on the components, or even
improved control algorithms. Data on the supraregional annual wind
distribution make it possible, on the one hand, by comparison with
the measured wind distribution at the location, to perform a
correction of the planning data; on the other hand, in less
favorable wind years, the turbine can be operated by use of a
"sharper" power characteristic curve for keeping up with the
requirements of the financing plan.
[0024] In the operating level control unit, the thus obtained
desired distributions are compared with the actual distributions.
This way, the optimum operating level under the current
meteorological and local conditions is computed. The regulated
quantities .theta..sub.opt (blade angle) and M.sub.Gopt and
n.sub.Gopt (generator moment and generator speed, respectively) are
to be understood as preset average values while, on the other hand,
the current desired values supplied by the standard control system
for adjustment to wind turbulences may temporarily deviate from
these average values,
[0025] With the availability of such a control system, it may be
advisable to operate the turbine with higher power yield in the
first years of operation in order to lower the financing costs as
quickly as possible, whereas, in later years, a low-stress
operation with reduced energy yield and a resultant lengthened
lifespan may be considered optimum under the economic aspect.
[0026] In the ideal case, the above described control system is
improved by the feature of an on-line detection of the current
energy generating costs (Cost Of Energy COE). For this purpose, it
is required that the loading model is combined, downstream thereof,
with a stress model for the individual components of the plant (a
restriction to the main components, i.e. the rotor blades, the
transmission, the generator, the converter and the tower will be
sufficiently accurate), and with a damage model. The stress model
transforms the loading distributions into stress distributions on
representative points of the components and is based on the methods
applied in the design of the components. The results from finite
element calculations can be summarized e.g. by consideration of
merely a small number of compliance factors for some critical
points. The damage model compares the existing loading influences
(e.g. Woehier lines) and thus computes the current component
damage. (The damage of a component permits conclusions on the
remaining lifespan). Therefore, the damage model has to rely on a
data base of the material or component behavior which is made
available from an external source and should be of a modular type
so as to be adaptable to the most up-to-date recognitions (e.g.
Woehler tests on original components, practical experiences from
the serial production) in the course of the lifespan of the
turbine. Since, in the present state of the art, particularly the
material behavior has to be estimated on a very conservative basis
due to lack of a sufficient data basis, the above adaptation
feature offers a wide potential for yield increase.
[0027] If the damage model has been suitably refined to allow for
an online calculation of the damage and thus also of the damage
rate for the important main components, the results of such
calculation can be easily used for determining an equivalent damage
rate for the whole turbine (Equivalent Damage Rate, EDR). The
equivalent damage rate (unit: US$/h) is a measure for the costs per
time unit incurred by damage in the current operating condition of
the turbine. The current energy generating costs can then be
obtained by dividing the sum of the EDR and the other operating
costs by the current power fed into the grid.
[0028] On this ideally refined level of the control strategy
wherein the economical efficiency of the wind turbine is reduced to
the decisive characteristlc factor "cost of energy COE", the
efficiency model has to be adapted to determine, as a value for
comparison to the current COE, the maximum allowable COE where the
turbine is still allowed to be operated. Should the current COE
values be too high in situations with weak winds, the turbine will
be taken off the grid. Should the current COE values be too high in
situations with high wind velocities, the operating level control
unit will lower the excessive stresses by suitably controlling the
turbine, thus decreasing the COE value. Thus, by the above online
COE determination, the optimum operating level with the lowest
possible COE values can be obtained for the current local and
meteorological conditions by use of a simple control loop. On this
optimum operating level, if the COE values are higher than the
maximum allowable COE value determined by the efficiency model, the
turbine will be brought to a standstill until more-favorable
conditions occur (e.g. lower turbulences or lower wind velocity).
Thus, during low turbulences, the turbines can supply power still
in case of much higher wind velocities than had been possible in
the state of the art.
[0029] As a further possible component, schematically illustrated
in the right-hand edge region of the drawing to the right of the
vertical dash-dotted line, a short-time control unit may be
provided for reduction of temporary loading peaks. The input data
of said unit include loading data and optionally also wind field
data, which--other than in the operating level control unit--are
not evaluated statistically but subjected to a current value
analysis; in a signal processing model also referred to as a
loading prognosis, predictions can thus be made on loading peaks
which will be reduced by the short-time control unit through
limitation the pitch angle or the rotor speed.
[0030] Therefore, particularly when using of data of neighboring
wind power plants located upstream relative to the wind direction,
the loading of the plant and thus also the current COE value during
wind velocities above the nominal wind are massively reduced;
notably, turbines located behind other turbines in the wind
direction can react exactly and with a suitable delay on wind
occurrences which have been registered in the turbine arranged
upstream. Thus, the unavoidable disadvantages (trailing
turbulences) for the following turbines can be compensated for.
[0031] For guaranteeing that the available potential of the plant
will not be reduced in case of a possible failure of one component
of the above control system, the operating control system should
preferably be designed such that the standard control system
illustrated on the left side of the drawing is separated, under the
hardware aspect, from the other components of the operating level
control unit. Thus, should the operating level control unit be not
available, the turbine will nonetheless remain connected to the
grid, even though it will then be subjected to the power limitation
for high wind velocities as provided by the state of the art.
[0032] The described control strategy is by no means limited to the
illustrated preferred embodiment for a variable-speed pitch plant
but is in its essence also useful for pitch plants designed for
fixed speeds or pole reversal, or for stall or active stall
plants.
[0033] Further, a large number of specific details and refinements
of the system can be contemplated (additional measurement values,
damage modules for further components of the plant etc.), all of
them following the basic idea of determining the optimum operating
time under the current local and meteorological conditions.
* * * * *