MOIT Vietnam Wind Atlas Report 18Mar2011

8/10/2019 MOIT Vietnam Wind Atlas Report 18Mar2011

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463NEWKARNERROAD|ALBANY,NY12205

awstruepower.com|[email protected]

PREPAREDBY

AWSTruepower,LLC

CLASSIFICATION

FORPUBLICRELEASE

REVIEWSTANDARD

SENIORSTAFF

WIND

RESOURCE

ATLAS

OF

VIETNAM MARCH18,2011

PREPAREDFOR

AWSTRUEPOWER,LLC,SOCIALISTREPUBLICOFVIETNAM


2/17

Page2WindResourceAtlasofVietnam

AWSTruepower,LLC March18,2011

DISCLAIMER

Acceptanceofthisdocumentbytheclient isonthebasisthatAWSTruepowerisnot inanywaytobe

held responsible for theapplicationorusemadeof the findingsand that such responsibility remains

withtheclient.

KEY

TO

DOCUMENT

CLASSIFICATION

StrictlyConfidential Forrecipientsonly

Confidential Maybesharedwithinclientsorganization

AWSTruepowerOnly NottobedistributedoutsideAWSTruepower

ClientsDiscretion Distributionattheclientsdiscretion

ForPublicRelease Norestriction

KEY

TO

REVIEW

STANDARD

Standard Standardreviewlevel.

SeniorStaff

Reviewed

by

senior

staff.

DueDiligence Highestlevelofscrutiny.


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TABLE

OF

CONTENTS

EXECUTIVE SUMMARY 4

INTRODUCTION 5

METHOD 5

RESULTS 9

WIND RESOURCE POTENTIAL OF VIETNAM 15

VIETNAM windExplorer 15

CONCLUSIONS AND RECOMMENDATIONS 17


4/17



EXECUTIVE

SUMMARY

In2002,theMinistryofIndustryandTrade(MOIT)andElectricityofVietnam(EVN)releasedVietnam:

RenewableEnergy

Action

Plan,

or

REAP,

a10

year

program

aimed

at

expanding

the

use

of

renewable

energysourcesinVietnam.AspartofitsefforttoadvancewindenergyundertheREAP,theMinistryof

IndustryandTrade(MOIT),withthesupportoftheWorldBank,awardedacontractinOctober2007to

carryoutaWindResourceAssessmentatSelectedSitesinVietnam.Theproject,performedbyateam

includingGPCO(Canada),AWSTruepower(USA),andENERTEAM(Vietnam),withPECC3(Vietnam)asa

subconsultant,ledtotheselectionofthreepromisingwindprojectsites,followedbyatwoyearwind

monitoringprogram,whichwascompletedattheendof2010.

Inearly2010,MOIT,with the supportof theWorldBank,awardeda contract toAWSTruepower to

createanewWindResourceAtlasofVietnam.Themaingoalofthisprojectwastoupdatetheprevious

WindEnergyResourceAtlasofSouthEastAsia (2001)using stateoftheartmethods verifiedby the

latestavailablewindmeasurements. Inaddition, theprojectaimed tomake thewind resourcemaps

availableto

developers

and

other

interested

groups

through

an

interactive

web

site.

To accomplish this objective, AWS Truepower ran a mesoscalemicroscale modeling system called

MesoMapoverVietnam, producingmaps ofmeanwind speeds at 60m, 80m, and 100mwith a

horizontal spatial resolution of 200m. AWS Truepower validated thewindmaps by comparing the

predictedspeedswithmeasuredvaluesfromninetowers, includingeighttalltowers instrumentedfor

windenergyassessment.Thepredictedmeanwindspeedsat80mwereonaverage0.24m/slessthan

theobservedmeanwindspeedsprojectedtothesameheight,andthestandarddeviationofthebiases

was0.84m/s.Basedonthesefindings,thestandarderrorofthemapsisestimatedtobe0.8m/s.

Accordingtothenewmaps,themostpromisingareasforwinddevelopment inVietnamarealongthe

southern and southcentral coasts and inmountain gaps in central Vietnam. Along exposed coastal

pointsofsouthcentralVietnam,themeanwinspeedat80mheightispredictedtoreach6.5m/sto7.0m/s.Anotherareaofbetterthanaveragewinds(5.0m/sto6.0m/s)isalongthecoastnearCanTho.A

thirdareaofsignificantinterest(6.0m/sto6.5m/s)isthebroadmountaingapwestofBinhDinhalong

theDacLacandGiaLaiprovincialborder.Farther to thenorth, thebestwind resourcesareconfined

mainlytothecoastnearQuangBinhandsoutheastofHaNoi.

TheWindResourceAtlasofVietnam ismadeavailable throughan internetbasedplatformcalled the

VietnamwindExplorer.Usingthisinterface,registereduserscanbrowsethewindspeedmapsandclick

toviewvaluesofmeanwindspeed,elevationandroughness,aswellasviewchartsofmeanwindspeed

by month and frequency by direction. The site is administered by MOIT and will served by AWS

Truepowerforthreeyears.

The accuracy of thewind resourcemaps could be improved through continued data gathering and

analysis.AWSTruepower recommendsanewmeteorologicaldatagatheringcampaign to supplement

therecentlyconcludedMOITwindresourceassessmentproject.Monitoringshouldbefocusedinareas

ofpotential importance forwindenergydevelopment, andespecially areas thathavenotpreviously

beenpreviouslymonitoredundertheMOITprogram.


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INTRODUCTION

In2001,AWSTruepower,thenunderthenameTrueWindSolutions,createdtheWindEnergyResource

AtlasofSouthEastAsiaundercontracttotheWorldBank.Thepurposeoftheatlaswastofacilitatethe

development of wind energy both for utilityscale generation and distributed power by providing

informationonthemagnitudeanddistributionofwindenergyresources.Theatlasprovidedwindspeed

mapsand

meteorological

characteristics

for

four

countries:

Cambodia,

Laos,

Thailand,

and

Vietnam.

An

analysis accompanying the atlas suggested thatof the four countriesVietnamhas the greatestwind

energygeneration.

In2002,theMinistryofIndustryandTrade(MOIT)andElectricityofVietnam(EVN)releasedVietnam:

RenewableEnergyActionPlan,orREAP,a10yearprogramaimedatexpandingtheuseofrenewable

energysources inVietnam.Inrecentyears,underREAPandrelatedpolicy initiatives,severalthousand

megawattsof renewableenergyprojectshavebeen installed inVietnam,with theencouragementof

theGovernmentofVietnam.Thevastmajorityofthisdevelopmenthasbeenintheformofhydropower.

AspartofitsefforttoadvancewindenergyundertheREAP,theMinistryofIndustryandTrade(MOIT),

with the support of theWorld Bank, issued in 2005 a Request for Proposals for a Wind Resource

Assessmentat

Selected

Sites

in

Vietnam.

After

acompetitive

process,

the

project

was

awarded

in

October2007toateamconsistingofGPCO(Canada,teamleader),AWSTruewind(USA)andENERTEAM

(Vietnam),withPECC3 (Vietnam)asasubconsultant.Theobjectiveoftheprojectwasto identifyand

assesscandidatewindproject sites to facilitate thedevelopmentofapilotwindenergyproject.This

addressed twobarriers towindenergydevelopment identified in theREAP: inadequateawarenessof

the technologies, inparticular their costsandperformance;and a lackofharddata concerningwind

resources.1Theprojectledtotheselectionofthreepromisingwindprojectsites,followedbyatwoyear

windmonitoringprogram,whichwascompletedattheendof2010.2

Bytheendof2009,afterjustoneyearofmeasurementhadbeencompleted,itwasobservedthatthe

WindAtlasofSoutheastAsiahadprobablyoverestimatedthewindresourceatthesethreesites,andby

implication

in

other

regions

of

Vietnam.

Partly

in

response

to

this

finding,

in

early

2010,

MOIT,

with

the

supportoftheWorldBank,awardedacontracttoAWSTruepowertocreateanewWindResourceAtlas

ofVietnam.Themaingoalof thisprojectwas toupdate theassessmentofVietnamswind resources

using stateoftheart methods verified by the latest available windmeasurements. In addition, the

project aimed tomake thewind resourcemaps available todevelopers andother interested groups

throughaninteractivewebsite.

ThisreportdescribesthemethodsusedtodeveloptheWindResourceAtlas,presentsthewindmaps,

updatesestimatesofthewindresourcepotential,anddescribestheinteractivewebsitethathasbeen

created,whichiscalledtheVietnamwindExplorer.

METHOD

TheWindResourceAtlasofVietnamwascreatedusingAWSTruepowersMesoMapsystem.Thissystem

wasdevelopedtomapthewindresourcesoflargeregionsatahighlevelofdetailwithgoodaccuracy.

1Vietnam: Renewable Energy Action Plan, ESMAP Technical Paper 021, World Bank (Washington, DC, 2002), p.

10.

2Reference final WRA report


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TheWindEnergyResourceAtlasofSoutheastAsiawas its firstmajorapplication.Thepresentproject

wascarriedoutusinganupdatedversionthatachieveshigherresolutionandimprovedaccuracy.

Themappingprocess issummarized inFigure1 (read left to right).The followingsectionsdiscuss the

processindetail.

Figure1.SchematicoftheMesoMapsystemusedtoproducetheWindResourceAtlasofVietnam.The

diagramisreadlefttoright.

MesoMap

Components

TheMesoMapsystemhasthreemaincomponents:models,databases,andcomputersystems.

Models

At the core of the MesoMap system is MASS, a numerical weather model that has been

developedoverthepast20yearsbyAWSTruepowerspartnerMESO, Inc.,bothasaresearch

toolandtoprovidecommercialweatherforecastingservices.3MASSsimulatesthefundamental

physicsof

the

atmosphere

including

conservation

of

mass,

momentum,

and

energy,

as

well

as

themoisturephases,and itcontainsa turbulentkineticenergymodule thataccounts for the

effectsofviscosityandthermalstabilityonwindshear.Adynamicmodel,MASSsimulatesthe

evolutionofatmosphericconditions intimestepsasshortasafewseconds.Thiscreatesgreat

computational demands, especiallywhen running at high resolution. Hence MASS is usually

coupledtoasimplerbutmuch fasterprogram,WindMap,amassconservingwindflowmodel

developed by AWS Truepower.4 Depending on the size and complexity of the region and

requirements of the client,WindMap is used to improve the spatial resolution of theMASS

simulationstoaccountforthelocaleffectsofterrainandsurfaceroughnessvariations.

DataSources

MASS uses a variety of online, global, geophysical and meteorological databases. The main

meteorological inputs are reanalysisdata, rawinsondedata, and land surfacemeasurements.Thereanalysisdatabasethemostimportantisagriddedhistoricaldatasetproducedbythe

3Manobianco,J.,J.W.ZackandG.E.Taylor,1996:Workstationbasedrealtimemesoscalemodelingdesignedforweather

supporttooperationsattheKennedySpaceCenterandCapeCanaveralAirStation.Bull.Amer.Meteor.Soc.,77,653672.

EmbeddedequationsaredescribedinZack,J.,etal.,1995:MASSVersion5.6ReferenceManual.MESO,Inc.,Troy,NY.4Brower,M.C.,1999:ValidationoftheWindMapModelandDevelopmentofMesoMap,Proc.ofWindpower1999,American

WindEnergyAssociation,Washington,DC.

Mesoscale

Simulations

(MASS)

Microscale

Simulations

(WindMap)

Geophysical

Data

MetData

Validate/

Adjust

WindMaps

Databases


7/17



USNationalCenters forEnvironmentalPrediction(NCEP)andNationalCenterforAtmospheric

Research (NCAR).5Thedataprovideasnapshotofatmosphericconditionsaroundthewordat

all levelsoftheatmosphere in intervalsofsixhours.Alongwithrawinsondeandsurfacedata,

thereanalysisdataestablishtheinitialconditionsaswellaslateralboundaryconditionsforthe

MASSruns.TheMASSmodel itselfdetermines theevolutionofatmosphericconditionswithin

theregionbasedontheinteractionsamongdifferentelementsintheatmosphereandbetween

theatmosphereandthesurface.Thereanalysisdataareonarelativelycoarsegrid(about210

kmspacing).Toavoidgeneratingnoiseattheboundariesthatcanresultfromlargejumpsingrid

cellsize,MASSisruninseveralnestedgridsofsuccessfullyfinermeshsize,eachtakingasinput

the output of the previous nest, until the desired grid scale is reached. The outermost grid

typicallyextendsseveralthousandkilometers.

The main geophysical inputs are elevation, land cover, vegetation greenness (normalized

differential vegetation index, or NDVI), soil moisture, and seasurface temperatures. The

elevationdatausedbyMASSandWindMaparefromtheShuttleRadarTopographicalMission

(SRTM), an international project spearheaded by theNationalGeospatialIntelligenceAgency

(NGA) and the National Aeronautics and Space Administration (NASA).6 The horizontal grid

spacingof

this

data

set

is

3arc

seconds,

or

about

90

m.

The

source

of

land

cover

data

was

the

28.5m resolution GeoCover LC data set generated byMDA Federal from Landsat Thematic

Mapper imagery.TheNDVIandseasurfacetemperaturedatawerederivedfromthesatellite

basedAdvancedVeryHighResolutionRadiometer (AVHRR),andhaveaspatialresolutionof1

km.7All geophysical data sets employed by themodels are projected and resampled to the

spatialresolutionofthesimulations,asneeded.

ComputerandStorageSystems

The MesoMap system requires a very powerful set of computers and storage systems to

producedetailedwindresourcemapsinareasonableamountoftime.TomeetthisneedAWS

Truepowerhascreatedadistributedprocessingnetworkconsistingof80IntelDualQuadCore

Xeon processors (640 total cores) and 100 terabytes of hard disk storage. Since each day

simulatedby

aprocessor

is

entirely

independent

of

other

days,

aproject

can

be

run

on

this

systemupto640timesfasterthanwouldbepossiblewithanysingleprocessor.

TheMappingProcess

TheMesoMapsystemcreatesawind resourcemap inseveralsteps.First, theMASSmodelsimulates

weather conditions over 366 days selected from a 15year period. The days are chosen through a

stratifiedrandomsamplingschemesothateachmonthandseasonisrepresentedequallyinthesample;

only the year is randomized. Each simulation generateswind andotherweather variables (including

temperature, pressure, moisture, turbulent kinetic energy, and heat flux) in three dimensions

throughout themodeldomain, and the information is stored athourly intervals.When the runs are

finished,the resultsaresummarized in files,whicharethen input into theWindMapprogram forthe

final

mapping

stage.

The

two

main

products

are

usually

(1)

color

coded

maps

of

mean

wind

speed

and

powerdensityatvariousheightsabovegroundand (2)data filescontainingwindspeedanddirection

frequencydistributionparameters.

5Robert Kistler et al., The NCEP/NCAR Reanalysis, Bulletin of the American Meteorological Society (2001).

6For more information, see http://www2.jpl.nasa.gov/srtm/.

7See http://edcwww.cr.usgs.gov/products/landcover/glcc.html.


8/17



Once completed, the maps and data are compared with available land and ocean surface wind

measurements,andareadjustedifsignificantdiscrepanciesareobserved.Thebestsourceofvalidation

data istalltowers instrumented forwindenergyassessment.Standardmeteorologicalstations,which

are generally onmuch shorter towers, can also be used, alongwith remotely sensed data such as

satellitebasedseasurfacewinds.Thevalidationisusuallycarriedoutinthefollowingsteps:

1.

Stationlocations

are

verified

and

adjusted,

if

necessary,

by

comparing

the

quoted

elevations

and stationdescriptionsagainst theelevationand landcovermaps.Where thereareobvious

errors inposition, thestationsaremoved to thenearestpointwith thecorrectelevationand

surfacecharacteristics.

2.

The observedmean speed andpower are adjusted to the longterm climatenorm and then

extrapolated to themap height using the power law.Often, for the tall towers, little or no

extrapolation isneeded.Wheremultileveldataareavailable, theobservedmeanwind shear

exponent is used. Where measurements were taken at a single height, the wind shear is

estimatedfromavailableinformationconcerningthestationlocationandsurroundings.

3.

Thepredictedandmeasured/extrapolatedspeedsarecompared,andthemapbias(mapspeed

minusmeasured/extrapolated

speed)

is

calculated

for

each

point.

If

there

are

enough

towers,

themeanbiasandstandarddeviationofthebiasesiscalculated.(Itisimportanttonotethatthe

biasandstandarddeviationmayreflecterrorsinthedataaswellasinthemaps.)

4.

Themapsareadjustedtoreduceobserveddiscrepancies.Thegoaloftheadjustment isnotto

eliminateerrorsateverypointwherethere isameasurement,buttoaddresspatternsofbias

affectingsubstantialregions.

Accuracy

TheMesoMapsystemhasbeenvalidatedaccordingtothemethoddescribedaboveusingdatafromwell

over3000 stationsworldwide.Themaperrormargin (thestandarderrorof thedistributionofbiases

betweenthepredictedandobservedmeanspeeds)typicallyrangesfrom0.2m/sto0.8m/satamean

speed

at

a

height

of

80

m.

Because

the

errors

tend

to

be

only

weakly

related

to

mean

wind

speed,

they

tendtobelarger,inpercentageterms,atlowwindresourcesitesthanathighwindresourcesites.

Thefollowingfactorscanaffecttheaccuracyofthewindmaps:

Finitegridscaleofthesimulations

Errorsinassumedsurfacepropertiessuchasroughness

Errorsinthetopographicalandlandcoverdatabases

Limitationsofthemodelsemployed

Thefinitegridscaleofthesimulationsresultsinasmoothingofterrainfeaturessuchasmountainsand

valleys.For

example,

amountain

ridge

that

is

2000

m

above

sea

level

may

appear

to

the

model

to

be

only 1600 m high. Where the flow is forced over the terrain, this smoothing can result in an

underestimationof themeanwind speedorpowerat the ridge top.Where themountainsblock the

flow,ontheotherhand,thesmoothingcanresult inanoverestimationoftheresource,asthemodel

understatestheblockingeffect.Theproblemoffinitegridscalecanbesolvedbyincreasingthespatial

resolutionofthesimulations,butatacostincomputerprocessingandstorage.

While topographic data are usually reliable, errors in the size and location of terrain features

nonethelessoccurfromtimetotime.Errorsinthelandcoverdataaremorecommon,andusuallyresult


9/17



from themisclassificationofaerialor satellite imagery.Whereverpossible,AWSTruepoweruses the

mostaccurateanddetailedlandcoverdatabases.

Assuming the land cover types are correctly identified, there remains uncertainty in the surface

propertiesthatshouldbeassignedtoeachtype,andespeciallythevegetationheightandroughness.A

forest,forexample,mayconsistofavarietyoftreesofvaryingheightsanddensity,leafcharacteristics,

andother

features

affecting

surface

roughness.

An

area

designated

as

cropland

may

be

devoid

of

trees,

oritmaybebrokenupintofieldsseparatedbywindbreaks.Uncertaintiessuchasthesecanberesolved

onlybyvisitingtheregionandverifyingfirsthandthelandcoverdata.Howeverthisisnotpracticalwhen

(asinmostMesoMapprojects)theareabeingmappedislarge.

Last, limitations in the model equations, and especially in the parameterization of subgridscale

meteorological phenomena such as turbulence and convection, can produce significant errors in

simulatedwindspeeds.Sucherrorsareanunavoidableconsequenceofthestateoftheartofnumerical

weatherprediction.

RESULTS

The standardMesoMapconfigurationwasused increating theWindResourceAtlasofVietnam.The

mesoscale model, MASS, was run with a horizontal grid spacing of 2.5 km. The microscale model,

WindMap,wasrunwithahorizontalgridspacingof200m.SRTMwasthesourceoftopographicdata,

andGeoCoverLCprovidedthelandcoverdata.Inconvertingfromlandcovertosurfaceroughness,the

roughness length values shown in Table 1were assumed. (We believe these values to be typical of

conditions inVietnam;however, the true roughnesscouldvaryagreatdealwithineachclass.)Mean

windspeedmapswerecreatedforthreeheightsaboveground:60m,80m,and100m.Thesemapsare

presented inFigures2,3,and4. Inaddition,data filesofestimatedmeanwind speedbymonthand

estimatedfrequencyandenergybydirectionweregenerated.

Table1.Landcovertypesandcorrespondingsurfaceroughnesslengthvaluesemployedincreatingthe

WindResourceAtlasofVietnam.

Land Cover Type Surface Roughness

Length (m)

Coniferous Forest 2.25

Deciduous Forest 1.875

Shrub land/Transitional 0.375

Cropland/Grassland 0.15 & 0.10

Wetland 0.20 & 1.125

Bare rock/Soil 0.05

Built-up Environment 0.75

Water 0.001

Wind

Resource

Maps

Asinmosttropicalandsubtropicalregions,theprevailingsynopticscalewindsinVietnamarerelatively

weak.Thedominantinfluencesarethesummerandwintermonsoons,whicharecreatedbydifferences

intemperaturebetweentheAsianlandmassandthesurroundingoceansseabreezesonavastscale.


10/17



The summer monsoon induces a counterclockwise circulation around southern and eastern Asia,

resulting in generally southerly and westerly winds in Vietnam. The winter monsoon creates the

oppositecirculation,resultinginmainlynortherlyandeasterlywinds.

Becauseoftheweakambientwinds,themostpromisingareasforwinddevelopmentinVietnamoccur

wheretheterrainconcentratesthewindflow.SeveralsuchareasarevisibleinthemapsinFigures2,3

and4.

Starting

in

the

south,

the

relatively

good

wind

resource

along

exposed

coastal

points

of

south

centralVietnam,especiallybetweenHoChiMinhCityandKhanhHoa,isduemainlytodeflectionofthe

monsoon winds, especially in summer, around the Southeast Asian landmass, and secondarily to

localizedseabreezes.Themeanwindspeedat80mheightatthesepointsispredictedtoreach6.5m/s

to7.0m/s.Farthersouththereisanotherareaofbetterthanaveragewinds(5.0m/sto6.0m/s)along

thecoastnearCanTho.ThethirdareaofsignificantinterestisthehighlandswestofBinhDinhalongthe

DacLacandGiaLaiprovincialborder,wherechannelingthroughabroadmountaingap isexpectedto

resultinmeanwindspeedsof6.0m/sto6.5m/s.

Movingnorth, relativelywindy areasaremainly confined to the coast,notablynearQuangBinhand

southeastofHaNoi.Theseareduemainly to seabreezes. Inaddition, the forcingofwindsover the

mountains

along

the

Laotian

border

in

central

Vietnam

is

predicted

to

produce

relatively

good

winds

alongtheridgelines.

Asidefromtheseareas,themaps indicatethatmostoftherestofVietnamexperiencesrelatively low

windspeedsrangingfromlessthan3.0m/sto5.0m/sat80m.

Comparison

with

Observations

AWSTruepowervalidatedthewindmapsbycomparingthepredictedspeedswithdatafrom9towers,

including8talltowers instrumentedforwindenergyassessment(three fromtheMOITwindresource

assessment project and five from a private source) and one standardmeteorological stationwhich

passedourqualitycontroltests.TheresultsareshowninTable2.Insummary,thepredictedmeanwind

speedsat80mareonaverage0.24m/s,or4%, lessthantheobservedmeansprojectedtothesame

height;the

standard

deviation

of

the

biases

is

0.84

m/s,

or

13%

of

the

projected

observed

mean.

Thesedeviationsareatthehighendofthenormalrange fortheMesoMapsystem.Thiscouldreflect

problems with either the simulations or the observations, or both. Among other issues, it was not

possibletoverifytheexactlocations,instrumentheights,ordataqualityofthefiveproprietarytowers.

Furthermore, because of a lack of suitable longterm reference measurements, the mean speed

estimates are basedon the period ofmeasurement,whichmay not reflect longterm conditions. In

addition, the relative paucity of highquality meteorological observations and the regions complex

terrainandactiveweathersystemsmakethisregionchallengingfornumericalweathersimulations.

Theerrormarginofthewindresourcemapsisdifficulttoestimatewithconfidencegiventhefairlysmall

number of comparison stations. Based on the limited findings and experience in other regions,we

estimatethe

standard

error

to

be

0.8

m/s.


11/17



Table2.ComparisonofmeanpredictedandobservedwindspeedsatninestationsinVietnam.

Name Latitude LongitudeStation

Type

Top Sensor

Height (m)

Observed

80m Wind

Speed (m/s)

Predicted

80m Wind

Speed (m/s)

Bias

Phan Rang 11.4316 108.9851 Tall Tower 60.1 6.46 7.06 0.60Phan Thiet 11.0760 108.4517 Tall Tower 60.1 6.27 6.79 0.52

Play Cu 13.7511 107.9941 Tall Tower 60.1 6.32 6.50 0.18

Proprietary Tall Tower 60 -1.67

Proprietary Tall Tower 60 0.18




Tan Son Hoa Airport 10 3.54 3.94 0.40

Average 6.31 6.07 -0.24

Standard

Deviation0.84

Guidelines

for

Interpreting

and

Using

the

Maps

Users of the Wind Resource Atlas of Vietnam should be aware that the mean wind speed at any

particular locationmaydepartsubstantially fromthepredictedvalues,especiallywheretheelevation,

exposure,or surface roughnessdiffers from thatassumedby themodel,orwhere themodelscale is

inadequatetoresolvesignificantfeaturesoftheterrain.Thissectionprovidesguidelinesforinterpreting

andadjustingthewindspeedestimatesinthemaps.

1. Themapsassumethatalllocationsarefreeofobstaclesthatcoulddisruptorimpedethewindflow.

Obstacle doesnot apply to trees if they are common to the landscape, since their effects are

alreadyaccounted for in thepredictedspeed.However,a largeoutcroppingof rockorabuilding

wouldpose

an

obstacle,

as

would

anearby

shelterbelt

of

trees

or

abuilding

in

an

otherwise

open

landscape.Asaruleofthumb,theeffectofsuchobstaclesextendstoaheightofabouttwicethe

obstacleheightandtoadistancedownwindof1020timestheobstacleheight.

2. Generallyspeaking,pointsthat lieabovetheaverageelevationwithinagridcellwillbesomewhat

windierthanpointsthat liebelowit.Aruleofthumb isthatevery100m increase inelevationwill

raisethemeanspeedbyabout0.51m/s.Thisformula ismostapplicabletosmall, isolatedhillsor

ridgesinflatterrain.

3. Themeanwindspeedcanbeaffectedbythesurfaceroughnessuptoseveralkilometersaway.Ifthe

roughnessismuchlowerthanthatassumedbythemodel,themeanwindspeedmaybehigher,and

viceversa.


12/17



Figure2. WindspeedmapofVietnamforaheightof60m.


13/17





14/17





15/17



WIND

RESOURCE

POTENTIAL

OF

VIETNAM

Basedonthenewwindresourcemaps,AWSTruepowerupdateditsestimatesofthedevelopablewind

resourcepotentialofVietnam.Thiswasdone in several steps.First,areas likely tobeunsuitable for

development were identified. These included areas with slopes exceeding 20%, internationally and

nationallyprotectedparksandnaturepreserves,wetlands,urbanareas,andwatercoursesandwater

bodies.The

remaining

areas

were

grouped

into

categories

according

to

predicted

mean

wind

speed

at

80mheight.Thedevelopableareawithineachspeedthresholdcategorywascalculated,andfromthis

thepotentialwindplantcapacitywasestimatedassumingameandensityof10megawatts (MW)per

squarekilometer.

The results are given in Table 3. It should be stressed that these values represent, at best, a very

approximate,highlevelestimateofthedevelopablepotential.Amongotherthings,economicviability,

localsitingconstraints,communityconcerns, locationsoftransmission linesandtransmissioncapacity,

andtheinfluenceoftopographyonwindturbinedensityhavenotbeenconsidered.

Table3.DevelopablewindenergypotentialbasedontheWindResourceAtlasofVietnam.Areas

deemedunlikelytobedevelopedasdescribedinthetexthavebeenexcluded.Allotherareasare

assumedfully

available

for

wind

development,

with

an

average

density

of

10

MW/km2.

MeanSpeedat

80mHeight

(m/s)

Estimated

Developable

LandArea(km2)

Percentageof

DevelopableLand

Approximate

Megawatt

Potential

9 1 0.00% 10

TOTAL 209,933 100.00% 2,099,333

VIETNAM

WINDEXPLORER

The Wind Resource Atlas of Vietnam is available through an internetaccessible portal called the

VietnamwindExplorer.Thistoolallowstheusersto:

Browsewind

speed

maps

at

heights

of

60

m,

80

m,

and

100

m

above

ground

level

at

ahorizontal

gridresolutionof200m

View latitude, longitude, mean wind speed, mean wind power density, Weibull A and k

parameters,elevationandroughnessforapointonthemapwhenalocationisclicked

Viewchartsofmeanwindspeedbymonthandfrequencybydirectionwhenalocationisclicked


16/17



The site is administered by MOIT and will be maintained by AWS Truepower for three years. The

followingscreenshotsillustratethefunctionalityofthewindExplorer.

Figure5.UserinterfaceforVietnamwindExplorerillustratingwindresourcemap,windrose,and

monthlydistribution.

Figure6. UserinterfaceforVietnamwindExplorerillustratingcoordinateentryfunctionality.


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CONCLUSIONS

AND

RECOMMENDATIONS

UndercontracttoMOITandwiththesupportoftheWorldBank,AWSTruepowerhasupdatedthewind

resource assessment ofVietnam using itsMesoMap system at a spatial resolution of 200m and at

heightssuitableformodern,utilityscalewindturbines.Theresultssupportthepreviousfindingthatthe

Wind Energy Resource Atlas of Southeast Asia (2001) overestimated wind resources in Vietnam.

However,the

windy

lands

analysis

performed

for

the

present

study

suggests

that

Vietnam

remains

an

attractive region forwind energydevelopment.A leading areaof interest is the southcentral coast.

MountaingapsbetweenLaosandVietnamaswellasothercoastalareasremainsubjectsofinterest.The

newWind Resource Atlas of Vietnam has beenmade accessible through the VietnamwindExplorer

portal,whichwillbeadministeredbyMOITandwillbeservedbyAWSTruepowerforthreeyears.This

should be valuable tool for wind project developers, government agencies, nongovernmental

organizations,andothersconsideringopportunitiesforwindenergydevelopmentinVietnam.

The accuracy of thewind resourcemaps could be improved through continued data gathering and

analysis.AWSTruepower recommendsanewmeteorologicaldatagatheringcampaign to supplement

therecentlyconcludedMOITwindresourceassessmentproject.Monitoringshouldbefocusedinareas

ofpotentialstrategicimportanceforwindenergydevelopment,andespecially inregionsthathavenot

been previously monitored as part of the MOIT program. As with all wind resource assessment

campaigns,internationalprotocolsconcerninginstrumentation,towerheight,datacollection,anddata

validationshouldbefollowed.Onceatleastayearofdatahasbeentaken,thenewmeasurementsmay

beusedtoadjusttheWindResourceAtlasofVietnameither inwholeor inpart.Thisshould increase

confidenceinthemapsandleadtoloweruncertainty.

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MOIT Vietnam Wind Atlas Report 18Mar2011

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