511:
particular requirement from a wind modelling point of view is the inclusion of all local features such as trees, hedges and buildings as turbine hub-heights range from as little as 10m to 50m. Wind modelling approaches need to include these features but very few of the available wind modelling commercial software provide this capability. Several work groups have been set up around the world to look into this modelling requirement and companies including
Digital Engineering Ltd (UK), NREL (USA), DTU Wind Energy (Denmark) are at the forefront of development in this area and look at the application of meso-CFD wind modelling techniques for this purpose.
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52:
136:
operating data from commissioned wind farms, the accuracy of wind resource maps in many countries has improved over time, although coverage in most developing countries is still patchy. In addition to the publicly available sources listed above, maps are available as commercial products through specialist consultancies, or users of GIS software can make their own using publicly available GIS data such as the US National
Renewable Energy Laboratory's High Resolution Wind Data Set.
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Wind farm modeling software aims to simulate the behavior of a proposed or existing wind farm, most importantly to calculate its energy production. The user can usually input wind data, height and roughness contour lines, wind turbine specifications, background maps, and define objects that represent
431:
Wind flow modeling methods calculate very high-resolution maps of wind flow, often at horizontal resolution finer than 100-m. When doing fine resolution modeling, to avoid exceeding available computing resource, the typical model domains used by these small-scale models have a few kilometers in the
236:
Because wind is variable year to year, and power produced is related to the cube of windspeed, short-term (< 5 years) onsite measurements can result in highly inaccurate energy estimates. Therefore, wind speed data from nearby longer term weather stations (usually located at airports) are used to
407:
Wind data management software assists the user in gathering, storing, retrieving, analyzing, and validating wind data. Typically the wind data sets are collected directly from a data logger, located at a meteorological monitoring site, and are imported into a database. Once the data set is in the
510:
In recent years a new breed of wind farm development has grown from the increased need for distributed generation of electricity from local wind resources. This type of wind projects is mostly driven by land owners with high energetic requirements such as farmers and industrial site managers. A
139:
Although the accuracy has improved, it is unlikely that wind resource maps, whether public or commercial, will eliminate the need for on-site measurements for utility-scale wind generation projects. However, mapping can help speed up the process of site identification and the existence of high
135:
Wind prospecting can begin with the use of such maps, but the lack of accuracy and fine detail make them useful only for preliminary selection of sites for collecting wind speed data. With increasing numbers of ground-based measurements from specially installed anemometer stations, as well as
227:
and other, more wind-specific regression methods can be used to fill in the missing data. These correlations are more accurate if the towers are located near each other (a few km distance), the sensors on the different towers are of the same type, and are mounted at the same height above the
201:(usually at airports). This data is used to adjust the onsite measured data so that the mean wind speeds are representative of a long-term period for which onsite measurements are not available. Versions of these maps can be seen and used with software applications such as
62:
High resolution mapping of wind power resource potential has traditionally been carried out at the country level by government or research agencies, in part due to the complexity of the process and the intensive computing requirements involved. However, in 2015 the
474:
environmental restrictions. This information is then used to design a wind farm that maximizes energy production while taking restrictions and construction issues into account. There are several wind farm modeling software applications available, including
432:
horizontal direction and several hundred meters in the vertical direction. Models with such a small domain are not capable of capturing meso-scale atmospheric phenomena that often drive wind patterns. To over come this limitation
411:
Many data logger manufacturers offer wind data management software that is compatible with their logger. These software packages will typically only gather, store, and analyze data from the manufacturer's own loggers.
444:
Wind flow modeling software aims to predict important characteristics of the wind resource at locations where measurements are not available. The most commonly used such software application is WAsP, created at
408:
database it can be analyzed and validated using tools built into the system or it can be exported for use in external wind data analysis software, wind flow modeling software, or wind farm modeling software.
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Multiple meteorological towers are usually installed on large wind farm sites. For each tower, there will be periods of time where data is missing but has been recorded at another onsite tower.
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35:
Modern wind resource assessments have been conducted since the first wind farms were developed in the late 1970s. The methods used were pioneered by developers and researchers in
75:(version 1.0) to provide freely available data on wind resource potential globally. The Global Wind Atlas was relaunched in November 2017 (version 2.0) in partnership with the
415:
Third party data management software and services exist that can accept data from a wide variety of loggers and offer more comprehensive analysis tools and data validation.
249:
permitting in the US, and costs. The power law and log law vertical shear profiles are the most common methods of extrapolating measured wind speed to hub height.
121:. However, these country wind resource maps have been largely superseded by the Global Wind Atlas in terms of data quality, methodology, and output resolution.
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The hub heights of modern wind turbines are usually 80 m or greater, but developers are often reluctant to install towers taller than 60m due to the need for
683:
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are installed. Data from these towers must be recorded for at least one year to calculate an annually representative wind speed frequency distribution.
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1006:
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The above global and country mapping outputs, and many others, are also available via the Global Atlas for
Renewable Energy developed by the
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Wind data analysis software assist the user in removing measurement errors from wind data sets and perform specialized statistical analysis.
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In addition to 'static' wind resource atlases which average estimates of wind speed and power density across multiple years, tools such as
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To calculate the net energy production of a wind farm, the following loss factors are applied to the gross energy production:
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provide time-varying simulations of wind speed and power output from different wind turbine models at an hourly resolution.
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under an initiative launched by ESMAP in 2013 focused on developing countries. This followed a previous initiative of the
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adjust the onsite data. Least squares linear regressions are usually used, although several other methods exist as well.
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Since onsite measurements are usually only available for a short period, data is also collected from nearby long-term
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The following calculations are needed to accurately estimate the energy production of a proposed wind farm project:
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Bailey, Bruce H.; McDonald, Scott L.; Bernadett, Daniel W.; Markus, Michael J.; Elsholz, Kurt V. (April 1997).
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quality, ground-based data can shorten the amount of time that on-site measurements need to be collected.
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265:(the height of vegetation or buildings). Wind flow modeling software, based on either the traditional
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in
Denmark. WAsP uses a potential flow model to predict how wind flows over the terrain at a site.
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83:
40:
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To estimate the energy production of a wind farm, developers must first measure the wind on site.
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465:) calculations instead, which are potentially more accurate, particularly for complex terrains.
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27:. Accurate wind resource assessments are crucial to the successful development of wind farms.
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is used to calculate the gross electrical energy production of each turbine in the wind farm.
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Wind power developers use various types of software applications to assess wind resources.
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are gaining acceptance in the wind industry. For offshore measurement campaigns, floating
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Al-Yahyai, Sultan (Jan 2012). "Nested ensemble NWP approach for wind energy assessment".
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684:"Establishing floating lidar as the standard for offshore wind resource measurements"
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When the long term hub height wind speeds have been calculated, the manufacturer's
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634:"Using bias-corrected reanalysis to simulate current and future wind power output"
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Correlations between long term weather stations and onsite meteorological towers:
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Wind speeds can vary considerably across a wind farm site if the terrain is
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Vertical shear to extrapolate measured wind speeds to turbine hub height:
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737:"Comparing WAsP and CFD wind resource estimates for the "regular" user"
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Energy production using a wind turbine manufacturer's power curve:
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117:(SWERA) project, which was launched in 2002 with funding from the
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Pereira, R; Guedes, Ricardo; Silva Santos, Carlos (2010-01-01).
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589:"NREL: Dynamic Maps, GIS Data, and Analysis Tools - Wind Data"
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approach, is used to calculate these variations in wind speed.
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Wind flow modeling to extrapolate wind speeds across a site:
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data on wind and other renewable energy resources effort.
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Measurements collected by remote sensing devices such as
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Staffell, Iain; Pfenninger, Stefan (1 November 2016).
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developers estimate the future energy production of a
86:, which is in the process of being updated under the
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217:Correlations between onsite meteorological towers:
97:Examples of country wind resource maps include the
128:(IRENA), which brings together publicly available
682:Patschke, Erik; Zwick, Sarah; Gottschall, Julia.
55:Wind resource map for the Philippines, from the
783:
105:, and a series of wind maps published by the
82:Another similar international example is the
8:
375:. Unsourced material may be challenged and
790:
776:
768:
659:
649:
395:Learn how and when to remove this message
115:Solar and Wind Energy Resource Assessment
103:Wind Resource Atlas of the United States
520:
305:blade degradation from ice/dirt/insects
753:
742:
126:International Renewable Energy Agency
7:
1220:
569:National Renewable Energy Laboratory
373:adding citations to reliable sources
290:Application of energy loss factors:
558:"Wind Resource Assessment Handbook"
529:"RE Resource Mapping | ESMAP"
457:are similar applications that use
111:United Nations Environment Program
14:
1231:
1219:
1208:
1207:
1195:
667:
506:Medium scale wind farm modelling
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261:(hilly) or there are changes in
427:Atmospheric simulation modeling
314:curtailments due to grid issues
194:systems have become standard.
65:Technical University of Denmark
565:Subcontract No. TAT-5-15283-01
1:
1104:Blade element momentum theory
308:high/low temperature shutdown
269:linear approach or the newer
1094:2020s in wind power research
722:10.1016/j.renene.2011.06.014
651:10.1016/j.energy.2016.08.068
459:computational fluid dynamics
1114:Energy return on investment
119:Global Environment Facility
1282:
688:Power and Energy Solutions
543:"Global Atlas Gallery 3.0"
326:
1189:
1161:Variable renewable energy
299:wind turbine availability
177:relative humidity sensors
67:, under framework of the
1181:Wind resource assessment
447:Risø National Laboratory
311:high wind speed shutdown
69:Clean Energy Ministerial
19:is the process by which
17:Wind resource assessment
88:New European Wind Atlas
1176:Wind profile power law
1171:Wind power forecasting
752:Cite journal requires
611:"awea.org | Resources"
296:wind turbine wake loss
90:project funded by the
59:
1202:Wind power portal
323:Software applications
157:Meteorological towers
54:
1007:Consulting companies
815:Airborne wind energy
369:improve this section
337:Wind data management
329:Wind energy software
1236:Additional portals:
1166:Virtual power plant
999:Wind power industry
877:Lists of wind farms
661:20.500.11850/120087
436:is sometimes used.
99:Canadian Wind Atlas
84:European Wind Atlas
41:wind power industry
39:, where the modern
469:Wind farm modeling
440:Wind flow modeling
419:Wind data analysis
225:linear regressions
199:reference stations
60:
47:Wind resource maps
1253:
1252:
845:on public display
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302:electrical losses
73:Global Wind Atlas
57:Global Wind Atlas
43:first developed.
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1240:Renewable energy
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617:. Archived from
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716:(1): 150–160.
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644:: 1224–1239.
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910:Aerodynamics
745:cite journal
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691:. Retrieved
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619:the original
615:www.awea.org
614:
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597:the original
593:www.nrel.gov
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572:. Retrieved
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367:Please help
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209:Calculations
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151:Measurements
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96:
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61:
34:
16:
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480:Meteodyn WT
455:WindStation
451:Meteodyn WT
283:power curve
169:temperature
161:anemometers
1266:Wind power
1146:Laddermill
1099:Betz's law
1044:including
977:Yaw system
869:Wind farms
820:By country
807:Wind power
799:Wind power
574:2009-01-28
515:References
488:Windfarmer
385:April 2014
165:wind vanes
107:World Bank
77:World Bank
21:wind power
356:does not
263:roughness
25:wind farm
1260:Category
1214:Category
1087:Concepts
1053:Goldwind
1017:Software
970:Darrieus
965:Savonius
930:Floating
915:Airborne
857:panemone
852:Windmill
840:Turbines
835:Offshore
693:21 March
484:Openwind
476:ZephyCFD
173:pressure
1226:Commons
1063:Senvion
1040:GE Wind
1035:Enercon
982:bearing
935:Nacelle
825:History
496:WindSim
492:WindPRO
377:removed
362:sources
259:complex
228:ground.
37:Denmark
31:History
1245:Energy
1078:Vestas
1073:Suzlon
1058:Nordex
945:QBlade
925:Design
638:Energy
498:, and
175:, and
113:, the
101:, the
987:drive
950:Small
561:(PDF)
192:LiDAR
188:LiDAR
184:SODAR
1136:HVDC
1124:grid
758:help
695:2024
500:WAsP
453:and
360:any
358:cite
267:WAsP
186:and
718:doi
656:hdl
646:doi
642:114
463:CFD
371:by
271:CFD
247:FAA
130:GIS
1262::
749::
747:}}
743:{{
714:37
712:.
686:.
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591:.
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502:.
494:,
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