Management of Meteorological Variables and Wind Mapping
INTRODUCTION
Once established the feasibility for the installation of wind farms
in a determined country or region from the political, legal and economic
point of view, the next step is to deeply study the geographic region
about which the
wind potential is intended to be analyzed.
In order to determine which region is the most adequate to start the
studies, what must be known is the distribution of the atmospheric capes
in the area, the direction or main directions of the winds and the
local conditions of the area, as the obstacles (buildings, trees, etc.),
the ground surface and the orography of the area. In the present
conditions of the Argentine Republic, such study must be based on
reports or previous analyses which could be available or which have
to be done, on
reports by the National Meteorological Service and satellite images,
among others. It is important to say that nowadays there is not a unique
wind map of the Argentine Republic, which would be the basic instrument
for any kind of consult or preliminary study. The analysis of this
generic information with which we count on at present only gives a
generic data and it must be considered as such.
It is also advisable to count on the local assessment of a
meteorologist, who can give a better interpretation as regards historic
values of the region, wind tendencies, pressure, average temperature and
humidity, as well as data concerning the meteorological phenomena which
usually take place in the area (such as rain and/or snow storms,
extreme temperatures, strong winds, etc.)
Once this preliminary study has been done a series of processes must
be followed so as to know the area in detail and which, finally, allow
to get a scientific and meteorologically sustained answer to the
question How much wind can we expect in the determined area?
So as to answer the previous question, it must be taken into account
that the wind conditions for an area are defined by the wind profiles of
this area, the average wind speed and direction, the wind speed
distribution and direction, and the wind daylight and seasonal patterns.
DEVELOPMENT
It must be considered that to determine the period in which the
measurement in the area will be done, the lasting of that period depends
on the kind of project that is intended to be carried out. If the
intention is to develop a complete wind map of a region, it must be
considered the measurement taking for at least 10 years (i.e.,
long-term); otherwise, if it is a preliminary analysis of the wind
resource, it must be considered the realization of the measurement, at
least, for a year in its initial phase (i.e., short and medium-term).
After this, the quantity and setting of the anemometers to be
installed must be defined, taking into account that it is advisable the
average surface monitored by each anemometer to be of 2500 km
2. Technically, it is recommended the use of head anemometers, calibrated every 6 months in a certified
wind tunnel.
Once calibrated and installed the anemometers in the region, it is
advisable that they work, for their optimal performance, during nearly 4
weeks before the measurement starts, without their data to be
considered for the study which has to be done. These data, must only be
taken into account so as to be able to study the correct equipment
calibration and the acquisition process of data, as well as the correct
functioning of the electronic equipments of meteorological measurement
and data store.
Calibrating the anemometers every 6 months and doing a bimonthly
follow-up of each of them in the field during the data collection
period, will minimize the error introduction or the loss of data. The
errors in this kind of wind study must be understood as a very complex
factor and can lead to the complete failure of the whole wind project.
Taking into account that the energy found in the wind is proportional to
the cubic wind speed (E~V
3) and that, according to Betz’s
law, theoretically the 59.3% of the wind energy can be extracted, the
measurement that are done on the “wind resource” must be very accurate
and free of possible errors.
Considering that the wind which is further from the surface has more
speed and less turbulence, due to the fact that it is not affected by
obstacles from the land, it is advisable to carry out the measurement as
high as the standards allow. In general, it is advisable to carry out
in the same spot two measurements at different heights, at 10 and at 30
meters, though measurements have been done with meteorological masts
placed even at 50 or 100 meters high.
Once the measurement network of meteorological data has been
installed on the land, the analysis of the air turbulence must be
carried out. This analysis must be done measurement the vertical
movement of the air (through the use of ultrasound anemometers), as well
as the air temperature.
It is important to take into account the density of the air in the
region, due to the fact that the air density in warmer regions lowers,
and in colder regions it increases. It must be considered that it is
better for the production of wind energy regions in which the air
density is as high as possible, i.e., regions with cold temperatures
(example: Argentina Patagonic region).
Air Density in
Normal
Conditions of
Pressure and
Temperature: 1.225 Kg. /m
3.
Normal
Conditions of
Pressure and
Temperature: 1013 hP and 20˚C
(NCPT)
Data Collection and Processing
Considering that the meteorological data obtained is the “raw
material” of the project and having used anemometric stations properly
calibrated, installed and verified, the processing phase must begin,
having a clear idea of what information must be obtained when this phase
ends.
Because of that, and before the data processing, it is important to
define adequate policies and protocols which allow to manipulate the
information and to process it with highest levels of security and
efficiency:
- It is advisable to establish the frequency for the data collection in the electronic equipments of the anemometers in 1 Hz.
- The meteorological values obtained must be averaged every 10 minutes (some anemometers allow to do this average internally).
- The policies of getting, collecting and transmitting the data
coming from the anemometers installed in the measurement field must be
defined.
It will be essential to do
height extrapolations, which allow
to estimate the winds that finally will be used for the wind electric
energy production[5]. To extrapolate the winds there are two different
equations:
1. Hellmann’s equation:
This equation allows to extrapolate the winds at a second height (h
2) though it is usually used only as an approximation.
v = wind speed
h = height above the ground [m]
α = Hellmann’s Exponent (For example: in Germany α=0.16)
2. Logarithmic Profile equation:
This equation must be applied only on average values, not on
individual values, and must be used with measurements that imply
long-term periods.
v = wind speed [m/s]
h = height from the ground [m]
d = thickness of the moving cape [m]
Z0 = ground surface
So as to be conservative, in the analysis and interpretation of any
of these equations, an error margin of +/- 10% must be considered.
The data processing in the first phase implies to obtain :
1. Weibull’s Curve.
f = density of frequency
v = wind speed (center of class) [m/s]
A = scale parameter [m/s]
c = shape parameter (note: c is k)
There is a relationship between Weibull’s parameters and the mean wind speed:
Increasing parameter
c of Weibull with the height (empiric) Weibull c
2 = c
1 + 0.008 (h
2 – h
1)
2. Study of wind drafts
3. Maximum and minimum wind speeds
4. Compass card of the region
EVALUATION OF THE WIND RESOURCE
What is a wind map:
It is a representation of the magnitude and the direction of the
winds of a region in graphic form, using cartography with a scale and
determined symbolism.
Kinds of data needed
The data which is needed to draw the wind map of a region are of
varied source and, depending on the method applied to do the job, they
will have to be of different kind, having each method their compulsory
data entry well defined. In this way, at the moment of developing the
wind map which data is available must be reveled and in what way they
can be used to apply which method.
Nevertheless, and not considering the method to be applied, the data
necessary for the mapping can be summarized in the following list:
- Anemometric measurement or surface measurement.
- Orographic data.
- Topographic data.
- Data of land use/natural coverage.
- Satellite images.
The data measured on surface is of vital importance, due to the fact
that it can be used to obtain the wind map of a region as well as to
validate the results obtained through other methods which do not use
measurements as entrance. On the other side, the surface data is still
the most accurate at the moment of doing the project.
PARTS OF A WIND MAP
Data
The most frequent data represented on the map for a determined height
are the mean wind speed (measured in m/s), the mean wind direction
(expressed in arrows or characteristic symbols of plotting in
meteorology), the mean energy density (measured in W/m
2), the
frequencies distribution, the compasses cards, the Weibull (A y k)
parameters, the studies on wind drafts and the studies of turbulence,
among others. Besides, the results must present not only the average
historic data, but also the seasonal regimens and the daylight and night
cycles of the resource.
There is another data which is used as entrance for the wind map
models, but which can become very useful to be used and represented as a
summary of the outcome. These are the ground surface map, the land use
and vegetal coverage map, and topographic maps.
All these data will be represented at different heights, being
nowadays the most common 30 and 50 m; though there are also atlases
which represent the information at 10, 25, 30, 50, 75, 80, 100, 125 and
200 m. Really, once the calculus have been done and knowing how the wind
profile behaves for an area, the values can be easily extrapolated in
height through methods as the ones mentioned above.
Wind classes definition: Whatever the data represented on the wind map is, the objective is always the same: to reveal the wind potential in an area.
One of the data which is usually represented is the quantity of energy than can be obtained from a region.
This is measured in W/m
2 and there is a table of equivalencies between the wind speed and power, which is used in the USA, called Wind Class [1].
Models
In order to build wind maps data and models are needed. The models
will be all those processes (programs, algorithms, methods) which allow
to draw the wind behavior and distribution in an area or given region.
Once determined which ones will be the models to use and collected
all the necessary data to feed the model, both things combine to become a
wind map. In some cases, the models can be combined between themselves
to get a more accurate result.
Kinds of climatic scales and their models: The models can be
of macro scale, known as synoptic scale (more than 2000 km); meso scale
(2 to 2000 km) or micro scale (up to the 2 km).
The most commonly used for the wind resource evaluation are those of
meso and micro scale, both of them can be used separated or in
combination. In general, the most common experiences are those in which
both models are used together.
Generally, the models used –independently of the scale- can be of
numerical or statistic type. In the case of the numerical models, are
based in a group of more or less complex equations which model the
physics reality of the climatic phenomena.
On the other side there are statistic models, which are characterized
for applying principles of statistics and probabilities to solve the
problem of how winds behave. Some of these methods are based on
principles of traditional statistics and others use modern techniques of
artificial intelligence, for example.
General numerical models: the numerical models can be
classified in three different categories according to the way in how
they model the reality (accuracy with which their equations model the
physics behavior of the winds).
- Solving the fundamental equation models.
- Simplified physics models.
- Statistics analysis models.
Solving the fundamental equation models
These are models which solve the general equation of the flux
movement of Navier-Stokes [3]. They include the description of the
topography, of effects of the surface ground, they allow to model
complex thermal effects and use geographic information, through the GIS
systems. These are called
meso scale models.
They allow the atmospheric representation or simulation in greater
detail, at the same time they allow the modeling of a wider area than
the rest of the numerical methods. These consider all –or almost all-
the important meteorological phenomena. On the other side, they do not
depend on data measured on surface. Known examples: KAMM (Karlsruhe
Atmospheric Mesoscale Model, from the homonym university in Germany),
MM5 (Mesoscale Model version 5 of NCAR/Penn - National Center for
Atmospheric Research/ Pennsylvania), ETA (generated model every 12 hours
created by the NCEP - National Center for Environmental Prediction and
used by the National Meteorological Service of the Argentine republic)
and MatMeso, among others.
At the same time, this kind of model requires the use of other
methods so as to achieve a greater resolution and surface measurement if
it is wished to validate that the outcome of the method is correct in
all the cases.
Classification of the meso scale phenomena(Fujita, 1986)
- Alfa Mesoscale (a): they have a dimension of between 200 and
2000 km with phenomena which can last between 6 hours and 2 days, as
small hurricanes and weak anticyclones.
- Beta Mesoscale (b), which counts with sizes of between 20 and
200 Km. lasting between 30 minutes and 6 hours; there can be fields of
local winds, mountain winds, breezes from the continent and the sea,
connective complexes of meso scale and big electric storms.
- Gamma Mesoscale (c) of an estimated size of between 2 and 20 km,
lasting between 3 and 30 minutes, representing phenomena like most of
the electric storms and big size tornados.
In order to achieve a collection of wind resource data using a meso
scale method the following steps must be followed: first, wind data and
measures must be collected in height. In general, measurements of radio
sound are used, though the measurements on surface can be considered to
calibrate the model and estimate errors. The model is executed to
simulate the winds of 10 to 15 years and, depending on the power of the
calculus available and the region to be modeled, the resulting grid ca
be between 1 and 5 Km. It is also possible to obtain a greater accuracy
if a micro scale model is executed or one which allows a greater
resolution within each point of the grid, for example the WAsP or
WindMAP. After the execution of the model, the map of the wind resource
is traced. In this map the data mentioned above can be represented.
Simplified physics models
They use a more reduced group of equations and –due to this- they
model a smaller quantity of climatic phenomena. They are used to trace
wind maps in low or medium complexity surfaces, getting maps equally
useful and accurate, but requiring a lot lower potential of calculus.
The advantages of this kind of methods are that they function with
anemometric seasonal data of surface, with no need of height data and,
besides, they are ideal for low complexity surfaces.
As a counterpart, their disadvantages are that they do not model the
reality completely, they can only represent some aspects of the wind
behavior and other meteorological variables. Then, they are not capable
of modeling complex meteorological phenomena, but very important ones,
as the breeze from the sea or the continent, or the wind produced by
thermal effects, like the mountain winds; they do not take into account
the splitting of the air flux produced by the irregular surface. It
depends on anemometric measurements on surface, what implies that if the
measurements are not enough or they are done in a wrong way, the model
will generate an incorrect result. The anemometric non reliable
measurements can not be used without using correction techniques which
can introduce new errors in the calculus.
Models based on GIS
These kind of models are based on completely different functioning
principles. For their functioning they use wind measurements in height
which are extrapolated to low altitude. Moreover, they are based on the
GIS (Geographical Information System) technology for the collection of
data and the drawing of the part of the region to be analyzed.
In 1995 the NREL - National Renewable Energy Laboratory started to
develop a new method of wind mapping based on the GIS technology. The
model is called WRAM (Wind Resource Assessment Model). It produces maps
of great quality and was used to develop the wind maps of several union
states (North Dakota, South Dakota and Vermont; part of Minnesota, Iowa
and Nebraska); apart from several international atlases like Dominican
Republic, Mongolia, Philippines and regions of Chile, China, Indonesia y
Mexico. This method needs of wind values previously calculated and,
really, it is no other thing than a method of representation, more than
of calculus.
Models from the point of view of the principles
From the point of view of the physic-mathematics principles, the numericalal models are classified in:
- Based on the Jackson-Hunt’s theory
- Based on the uniform mass model
In the first case, these models tend to satisfy the Navier-Stokes’
equations [3]. Their basic characteristic is the description of two
fundamental principles: the mass conservation and the moment
conservation. Due to this, this kind of model is very sophisticated and
has a very good output: an error among the 8 and the 10%.
In the case of the models based on the mass uniform model, they only
describe (different from the previous ones) the mass conservation. They
are less sophisticated and has a similar output –under determined
conditions- to the most complex models. Examples of this kind of model
are the WindMAP and the WAsP.
It can be deduced from the description of both models that the mass
conservation principle is the most important determinant of the wind
variation, always referring to surfaces of low or moderated complexity.
Graphics of the combined models
The graphic shows the steps to develop a wind map using a meso scale
method and one of micro scale together, as the Wind Atlas style.
EXAMPLES OF THE MOST KNOWN MODELS
- KAMM (Karlsruhe Atmospheric Mesoscale Model) [meso scale] [4]
- Wind Atlas Analysis and Application Program (WAsP) [Simplified] [4]
- MesoMAP [meso scale] [7]
- WRAM Method [GIS] [8]
- WindMAP [Simplified] [7]
- WindSCAPE [Mix]: Raptor [micro] + TAPM [meso]
WIND MAP EXAMPLE: EUROPE
WIND MAP EXAMPLE: EUROPE OFFSHORE
WIND MAP EXAMPLE: DENMARK
CONCLUSIONS
One must be conservative in the interpretation not only of the data
obtained as a consequence of the measurements done in the field by the
measurement equipments but also with the extrapolations which are done,
in height as well as on the surface. It is convenient to estimate
between a 10% and a 20% less in the obtained data, and with those values
to do the calculus and estimations.
Finally, the report of the
“wind potential” of the region must present a technical and meteorologically sustained detail of the following information:
- The preliminary analysis of the region. (In this case it is advisable to count with the wind map of the country)
- Equipment installation process.
- Wind Mapping.
- Results and final report.
It does not matter what kind of wind project will be started, the
evaluation phase of the potential of a region is one of the most
important ones. According to its result the feasibility or not of a
future project will be determined; also which is the best place within a
region to establish a new wind complex.
The wind maps (atlas, resource evaluations, or whatever name they are
assigned) are fundamental instruments to start any work of planning the
installation of a wind farm. But all of them depend, at the same time,
on fundamental incomes which will allow their creation: the
meteorological data, of whatever kind they are.
REFERENCES
- [1]. Wind Energy Danish Assoc. WindPower.org. Wind class standard definitions “Wind Class”. 11/Feb/2004, <http://www.windpower.org/es/stat/unitsw.htm>
- [2]. Brower, M., B. Bailey, and J. Zack. The New US Wind Resource Atlas [cdrom]. In: European Wind Energy Conference & Exhibition 2003. [Madrid], European Wind Energy Association, 2003.
- [3]. Cambridge University Press. Foundations of Fluid Mechanics. Navier-Stokes Equations [on line]. 14/Aug/2004. <http://www.navier-stokes.net/>
- [4]. Frank, H. P., O. Rathmann, N. G. Mortensen, and L. Landberg.
The Numericalal Wind Atlas: The KAMM/WasP Method. [Roskilde, Denmark]:
Information Service Department, RisØ National Laboratory, June 2001.
- [5]. Gasch, R., and J. Twele. Wind Power Plants. Fundamentals, Design, Construction and Operation. [Berlin, Germany]: Solarpraxis AG, 2002.
- [6]. Manwell, J. F., J. G. McGowen, and A. L. Rogers. Wind Energy Explained: Theory, Design and Application. [West Sussex, England]: John Wiley & Sons Ltd, 2002.
- [7]. Brazil Mining and Energy Ministry. Mapas do Potencial Eólico Anual [cdrom]. In: Atlas Do Potencial Eólico Brasileiro. [Brasilia, Federative Republic of Brazil], e-dea Technologies/ Christianne Steil, 2001.
- [8]. Nielsen, J., S. Innis, and K. Pollock. Renewable Energy Atlas of the West. <http://www.EnergyAtlas.org>
- [9]. RisØ National Laboratory. Wind Energy Department. Wind Resource Atlas for Denmark. [Denmark]: 23/Jan/2004. <http://www.risoe.dk>
Eng. Luis Mariano Faiella
Eng. Alejandro J. Gesino
Research & Development Area
Argentine Wind Energy Association
www.argentinaeolica.org.ar
Croatian Center of Renewable Energy Sources (CCRES)