Antakya bölgesi rüzgar karakteristiğinin incelenmesi

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mühendislikdergisi

Cilt: 3-9

Dicle Üniversitesi Mühendislik Fakültesi Mart 20145, 1,

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ø. Mert, C. .DUDNXú)3HNHU

Investigation of wind characteristics

for Antioch

Extended abstract

Rapidly increased the environmental pollution, global population and exhausted reserves of consuetudinary resources have become matters of social and economic concern to individuals and scientists since the '70s. With the rising costs of traditional energy resources, alternative renewable sources of energy are playing more important role. Actually, there is the many types of renewable energy resources such as hydro, solar, wind, biomass, geothermal, wave and tide energy. Among of them, the wind energy is maybe the cleanest, inexhaustible and popular source of energy. But wind energy has several disadvantages and one of them is that winds are inherently random. Wind power prediction processes give the information of how much wind power can be expected at which point of time in the determined time interval. However, these processes required the short and long-term wind characteristics and other measurements at a given location. In this respect, obtained wind speed, direction, humidity, pressure values and surface roughness information can provide fundamental and valuable information for the assessment of wind power energy availability and give knowledge for economic viability of a wind energy conversion system and also wind farm design. Turkey has important wind energy potential in the Akdeniz region, especially coasts of southern Anatolia. In this study, wind energy potential was statistically analyzed based on the data that are measured wind speed on a daily basis. Wind data obtained from the Directorate of Hatay Meteorological Station located Antioch which is central town of Hatay in southern Turkey, near the border with Syria in years between 2002 and 2009. A precise determination of probability distribution for wind speed data is the most important issue in statistically evaluating wind speed energy potential of a region. In generally, wind speed distribution have generally modeled by the 3-parameter Generalized Gamma , 2-parameter Gamma , inverse Gaussian, 2-parameter Lognormal , 3-parameter Beta, singly truncated from below Normal, distributions derived from the Maximum Entropy Principle, and conventional or bimodal (two component mixture) Weibull distribution functions etc.. But the wind energy potential of Antioch was investigated by Weibull Distribution that is popular

on the modeling of wind speed and Log-normal distribution function which is previously untested in Antioch. In the estimation of parameters of Weibull and log-normal distribution, the Maximum Likelihood Estimation (ML) and the Least Square Method (LSM) were used as the parameter estimation technique. The value of the Weibull shape parameter c is between 2.71 and 3.07 m/s, while the scale parameter k varies between 1.96 and 2.09 for ML method. When the LSM method is used, c is calculated between 2.61 and 2.96 m/s, while the scale parameter k varies between 2.34 and 2.53. If ML method use, the yearly values of Log-normal VFDOH SDUDPHWHU ı UDQJH EHWZHHQ DQG  :KHQ/60PHWKRGSUHIHUUHGıYDULHVEHWZHHQ and 0.57. The lowest value of the Log-normal location parameWHUȝDUH0/-LSM) and found in the year 2009, while the highest values were 0.84 (ML) and 0.86 (LSM), which occurred in the year 2004. There are various tests used for evaluating the accuracy of the forecasted wind distributions obtained from various statistical functions. Both methods were evaluated by using error analysis that DUH FRHIILFLHQW RI 'HWHUPLQDWLRQ 5ð DQG WKH Average Square Root Sum of the Squares Error (RMSE). The highest root mean square error (RMSE) value was found as 0.020014 for the Log-normal distribution function by the ML method. The lowest RMSE value was calculated as 0.016242 by LSM method. Additionally these values were calculated 0.012081(ML) and 0.014582(LSM) for WKH :HLEXOO GLVWULEXWLRQ 2WKHU KDQG WKH 5ð YDOXHV obtained using Log-normal distribution function are %98 in both methods, while the 2 value is %99 for the Weibull distribution. The Weibull and Log-normal approximations of the actual probability distributions of wind speed for the whole year have close results. However, the best performance has been demonstrated by Weibull distribution with the ML method. The analysis results also showed that the maximum monthly wind speed occurs in the summer months while the months of winter have the lowest mean wind speed. The Weibull distribution provided better power density estimations in all months than the Log-normal distribution. As a result of this research when the wind turbines have low cut-in speed, were preferred, wind energy potential of Antakya was statistically found to be encouraging for production of electrical energy.

Keywords: Antioch, Weibull – Log-normal

distribution, Least square method, Maximum likelihood estimation, Wind energy.

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(OGH HGLOHQ VRQXoODU LVH LVWDWLVWLNVHO

oDOÕúPDODUGD VÕNOÕNOD NXOODQÕODQ 52_belirleme

NDWVD\ÕVÕ YH 506( RUWDODPD KDWD NDUHOHUL WRSODPÕ N|N GH÷HUOHUL KHVDSODQDUDN HQ GúN KDWD\DVDKLSGD÷ÕOÕPDUDúWÕUÕOPÕúWÕU

Weibull ve Log-QRUPDO'D÷ÕOÕP )RQNVL\RQODUÕ

/LWHUDWUGH HQ VÕN NXOODQÕODQ GD÷ÕOÕPODUGDQ ELULVL LNL SDUDPHWUHOL :HLEXOO GD÷ÕOÕP IRQNVL\RQXGXU 5]JDU KÕ]Õ LoLQ LNL SDUDPHWUHOL :HLEXOOGD÷ÕOÕPÕQÕQJHQHOLIDGHVL _V_ck k w _c e V c k V f / 1 ) ( ¸ ¹ · ¨ © § ₍₂₎

úHNOLQGHGLU %XUDGD fw(V), J|]OHPOHQHQ U]JDU

KÕ]Õ V¶QLQ RODVÕOÕN IRQNVL\RQX F U]JDU KÕ]Õ LOH D\QÕ ELULPH VDKLS |OoHN SDUDPHWUHVL YH N LVH

ER\XWVX] úHNLO SDUDPHWUHVLGLU :HLEXOO

GD÷ÕOÕPÕQÕQELULNLPOLRODVÕOÕNIRQNVL\RQXLVH _V _ck w V F₍ ₎ ₁_exp / (3)

úHNOLQGH LIDGH HGLOPHNWHGLU 2UWDODPD U]JDU KÕ]ÕSURILOLYHHQHUMLSRWDQVL\HOLQLQEHOLUOHQPHVL LoLQ :HLEXOO SDUDPHWUHOHUL RODQ c ve k¶QÕQ EXOXQPDVÕ JHUHNOLGLU c ve k parametrelerinin tahmin edilmesi ile birlikte RUWDODPDU]JDU KÕ]Õ ise; ¸ ¹ · ¨ © § * 1 1 k c VWeibull (4)

úHNOLQGH KHVDSODQDELOLU. Burada, VWeibull

RUWDODPD U]JDU KÕ]ÕQÕ ī…) ise Gamma fonksiyonunu ifade eder. Gamma fonksiyonunun genel ifadesi ise EúLWOLN LOH verilebilir.

(7)

$QWDN\DE|OJHVLU]JDUNDUDNWHULVWL÷LLQFHOHQPHVL dx x e t x t1 0 ) ( f

³

* (5) c ve k SDUDPHWUHOHULQLQKHVDSODQPDVÕQGDQVRQUD RUWDODPDU]JDUJF\R÷XQOX÷X ) 3 1 ( 2 1 3 k c Pw U * (6) ile hesaplanabilir. BuUDGD \R÷XQOXN NJ P3₎

olup hesaplamalarda 1.225 kg /m3 kabul

HGLOPLúWLU

1RUPDO GD÷ÕOÕPÕQ NROD\ YH |]HOOLNOHULQLQ L\L ELOLQPHVLQGHQ GROD\Õ QRUPDO GD÷ÕOPÕú ROPD\DQ GD÷ÕOÕPODUÕQ GD X\JXQ ELU G|QúPOH QRUPDO GD÷ÕOÕPDX\GXUXOPDVÕ\ROXQDJLGLOLU%XDPDoOa ORJDULWPLN G|QúP \D\JÕQ RODUDN NXOODQÕOÕU Log-QRUPDO GD÷ÕOÕPGD UDVWJHOH GH÷LúNHQLQ VDGHFHSR]LWLIGH÷HUOHUDODELOGL÷LYHGD÷ÕOÕPÕQÕQ SR]LWLIoDUSÕNOÕ÷ÕROGX÷XLoLQEXGD÷ÕOÕPSUDWLNWH NDUúÕODúÕODQ ELUoRN GH÷LúNHQOHUH L\L X\PDNWDGÕU hONHYH%DUDQ5).

Log-QRUPDO GD÷ÕOÕPÕQ RODVÕOÕN \R÷XQOXN

fonksiyonu, 2 2 2 ) (ln 2 1 ) ( V P S V V normal Log e V x f (7)

úeklinde verilmektedir. Burada, P yer

parametresi ve V|OoHNSDUDPHWUHVLGLU2UWDODPD U]JDUKÕ]ÕLVH ) 2 ( 2 V P e VLognormal (8)

úHNOLQGH YHULOPHNWHGLU 2UWDODPD U]JDU JF \R÷XQOX÷XLVH 3 ) 2 ( 2 2 1 P V Ue P_L (9)

olarak ifade edilmektedir.

Hata analizi

%X oDOÕúPDGD NXOODQÕODQ \|QWHPOHU LNL IDUNOÕ KDWD KHVDEÕ IRUPO LOH DQDOL] HGLOPLúWLU

Bunlardan birincisi R2_{beOLUOHPH NDWVD\ÕVÕ}

IRUPOROXS(úLWOLN¶GDYHULOPLúWLU

¦

_n i i n i i i y y x y R 1 2 1 2 ) ( ) ( 1 (10)

øNLQFL KDWD IRUPO LVH (úLWOLN ¶GH YHULOHQ +DWD .DUHOHUL 7RSODPÕQÕQ .DUHN|N 506( olup;

¦

n i i i x y RMSE 1 5 . 0 2₎ ) ( 1 ( (11)

Burada Q J|]OHP VD\ÕVÕ \¶OHU RUWDODPD JHUoHN GH÷HUOHU YH [¶OHr Weibull ve Log-normal GD÷ÕOÕPÕLOHKHVDSODQDQU]JDUKÕ]ÕGH÷HUOHULGLU /LWHUDWUGHLVH52_{GH÷HULHQE\N\DGD506(}

GH÷HUL HQ NoN GD÷ÕOÕP IRQNVL\RQX HQ L\L GD÷ÕOÕPIRQNVL\RQXRODUDNNDEXOHGLOPHNWHROXS EX NULWHUOHUH J|UH KDWD DQDOL]L \DSÕOPDNWDGÕU ($NGD÷YG.

$UDúWÕUPDVRQXoODUÕ

%X oDOÕúPDGD 5]JDU KÕ]Õ YHULOHUL $QWDN\D merkezde yer alan Meteoroloji Genel 0GUO÷QHDLW2WRPDWLN0HWHRURORML*|]OHP øVWDV\RQX WDUDIÕQGDQ yerden P \NVHNOLNWH |OoOPúWU 5]JDU KÕ]Õ Gk DUDOÕNODUOD |OoOHUHN VDDWOLN RUWDODPDVÕ VWDQGDUW VDSPDVÕ DúÕUÕ PD[ YH PLQ GH÷HUOHUL ND\ÕW HGLOPLúROXS- \ÕOODUÕDUDVÕQGDNLVHNL] \ÕOOÕN G|QHPL NDSVDPDNWDGÕU P \NVHNOLNWH GNDUDLOH|OoOHQVDDWOLNRUWDODPDU]JDU KÕ]ÕYHULOHULQHLOLúNLQIUHNDQVGD÷ÕOÕPÕRUWDODPD U]JDU KÕ]Õ YH RUWDODPD Jo \R÷XQOXNODUÕ ùHNLO ùHNLOYHùHNLO¶GHJ|UOPHNWHGLU

5]JDU KÕ]Õ YHULOHUL |QFHOLNOH 0/ \|QWHPL VRQUDVÕQGD LVH /60 \|QWHPL NXOODQÕODUDN \ÕOOÕN RODUDNGH÷HUOHQGLULOPLú0/YH/60\|QWHPleri ile tahmin edilen Weibull ve Log-normal GD÷ÕOÕPODUÕQD DLW SDUDPHWUHOHUL YH EXQODUD ED÷OÕ RODUDN \ÕOOÕN RUWDODPDU]JDU KÕ]Õ RUWDODPDJo \R÷XQOX÷XLOHVWDQGDUWVDSPDGH÷HUOHUL7DEOR YH7DEOR¶GHYHULOPLúWLU

(8)

:HLEXOOGD÷ÕOÕPÕ için En Küçük Kareler (LSM) \|QWHPL GDKD NoN VWDQGDUW VDSPD GH÷HULQH VDKLS ROGX÷X LoLQ GDKD EDúDUÕOÕ ROGX÷X Tablo 1’de görülmektedir. $\QÕ WDEORGD c ( ölçek SDUDPHWUHVL¶QLQ HQ NoN m/s en fazla 3.03 m/s ROGX÷Xk úHNLOSDUDPHWUHVL¶nin ise en NoN HQ E\N ROGX÷X da J|UOPektedir.

0/ YH /60 NXOODQÕODUDN KHVDSODQDQ /RJ-QRUPDOGD÷ÕOÕPÕQDDLWı|OoHNSDUDPHWUHVL)’nin HQNoNHQE\NYHP (yer-konum SDUDPHWUHVL HQ NoN HQ E\N ROGX÷X da 7DEOR¶GHJ|UOmektedir.XOODQÕODQ her iki parametre kestiriP\|QWHPLQLQGH- \ÕOODUÕ DUDVÕ $QWDN\D E|OJHVL U]JDU YHULOHUL LoLQ ELUELULQH \DNÕQ VWDQGDUW VDSPD\D VDKLS ROGX÷X GROD\ÕVÕ\OD EDúDUÕOÕ ROGX÷X J|UOPHNWHGLU Tablo 1. 0/YH/60PHWRGODUÕLOHKHVDSODQDQ:HLEXOOYH/RJ-QRUPDOGD÷ÕOÕPODUÕQÕQSDUDPHWreleri Parametre -<ÕO 2002 2003 2004 2005 2006 2007 2008 2009 Weibull ML c 2.90 3.03 3.07 3.05 3.07 2.88 2.85 2.71 k 2.09 2.09 2.12 1.96 1.96 1.99 2.03 2.03 2UW+Õ] 2.57 2.68 2.72 2.70 2.72 2.56 2.53 2.40 2UW5]*o<R÷ 18.98 21.62 22.16 23.52 24.04 19.62 18.62 16.0 Std. Sapma 1.29 1.35 1.35 1.44 1.45 1.34 1.31 1.24 Weibull LSM c 2.79 2.92 2.96 2.93 2.95 2.77 2.76 2.61 k 2.53 2.47 2.53 2.34 2.28 2.46 2.34 2.40 2UW+Õ] 2.47 2.59 2.63 2.59 2.62 2.45 2.44 2.32 2UW5]*o<R÷ 14.46 16.99 17.38 17.72 18.64 14.46 14.78 12.3 Std. Sapma 1.05 1.12 1.11 1.18 1.22 1.07 1.11 1.03 Log-normal ML ı 0.53 0.54 0.55 0.58 0.59 0.55 0.57 0.55 ȝ 0.80 0.84 0.84 0.83 0.83 0.79 0.77 0.72 2UW+Õ] 2.56 2.69 2.70 2.70 2.73 2.55 2.54 2.40 2UW5]*o<R÷ 10.29 11.86 12.09 12.09 12.48 10.12 9.99 8.51 Std. Sapma 1.47 1.57 1.37 1.69 1.76 1.50 1.56 1.44 Log-normal LSM ı 0.52 0.53 0.52 0.56 0.57 0.54 0.56 0.55 ȝ 0.80 0.84 0.86 0.83 0.83 0.78 0.77 0.72 Ort. HÕ] 2.55 2.67 2.70 2.68 2.71 2.53 2.52 2.39 2UW5]*o<R÷ 10.10 11.64 12.07 11.83 12.16 9.97 9.79 8.35 Std. Sapma 1.43 1.52 1.51 1.64 1.69 1.47 1.52 1.41 Tablo 2. 'D÷ÕOÕPODUDJ|UHRUWDODPDJo\R÷XQOXNODUÕ

<ÕO 3Y*|]OHP'H÷HUOHULQH*|UH Weibull ML Weibull LSM Log-normal ML Log-normal LSM 2UW*o<R÷:/ m2₎ 2UW*o <R÷:P2₎ 2UW*o <R÷:P2₎ 2UW*o <R÷:P2₎ 2UW*o <R÷:P2₎ 2002 10.2 10.35161371 9.25413 10.2944 10.10468182 2003 11.6 11.83708804 10.6783 11.8593 11.64048793 2004 11.9 12.29300053 11.1100 12.0853 12.07272355 2005 11.7 12.06615488 10.6808 12.0947 11.82954692 2006 11.7 12.30711923 10.9775 12.4760 12.15685154 2007 9.9 10.23227334 9.0590 10.1156 9.969065708 2008 9.4 9.878472265 8.9148 9.9889 9.793559843 2009 8.0 8.501113978 7.6182 8.5125 8.349001823

(9)

$QWDN\DE|OJHVLU]JDUNDUDNWHULVWL÷LLQFHOHQPHVL

2002- \ÕOODUÕ DUDVÕQGDNL U]JDU YHULOHULQH J|UH HOGH HGLOHQ KDWD DQDOL]L VRQXoODUÕ 7DEOR ¶GH YHULOPLúWLU <DSÕODQ KDWD DQDOL]OHULQH J|UH HQ \NVHN 52 _{%99 ( Weibull ML ) en az ise}

%98 ( Log-QRUPDO 0/ GH÷HUOHUL 506( LoLQ en az 0.012081 ( Weibull ML ) en fazla 0.020014 ( Log-normal ML) GH÷HUOHUL HOGH HGLOPLúWLU

Tablo 3. 2002-\ÕOODUÕLoLQKDWDDQDOL]L

7DUWÕúPDYHVRQXoODU

%X oDOÕúPDGD +DWD\ LOL $QWDN\D E|OJHVLQGHNL 2002- \ÕOODUÕ DUDVÕQGDNL \ÕOOÕN SHUL\RW ER\XQFD GN DUDOÕNODUOD ND\GHGLOHQ U]JDU

YHULOHUL %|OJH 0HWHRURORML 0GUO÷

WDUDIÕQGDQ HOGH HGLOPLúWLU (OGH HGLOHQ YHULOHU DQDOL]HGLOPLúYHQHWLFHVLQGHU]JDUKÕ]ÕYHULOHUL LoLQ U]JDU KÕ] GD÷ÕOÕPlarÕ RODVÕOÕN \R÷XQOXN fonksiyonu X\JXODPDVÕ ve parametre tahmini \DSÕOPÕúWÕU øVWDWLVWLNVHO DQDOL]OHUGH :HLEXOO GD÷ÕOÕPÕ YH /RJ-QRUPDO GD÷ÕOÕPODUÕ LoLQ 0DNVLPXP 2ODELOLUOLN 7DKPLQL YH (Q .oN .DUHOHU0HWRGXROPDN]HUHLNLIDUNOÕSDUDPHWUH NHVWLULPWHNQL÷LNXOODQÕOPÕúWÕU<DSÕODQDQDOL]OHU neticesinde, parametre tahmin tekniklerinden ML-0DNVLPXP RODELOLUOLN WHNQL÷LQLQ :HLEXOO GD÷ÕOÕPÕLoLQYHHQNoNNDUHOHU\|QWHPLQLQGH Log-QRUPDO GD÷ÕOÕPÕ LoLQ GDKD L\L VRQXoODU YHUGL÷L EHOLUOHQPLúWLU $\QÕ ]DPDQGD EX SDUDPHWUH NHVWLULP WHNQLNOHULQH J|UH RODVÕOÕN

\R÷XQOXN IRQNVL\RQODUÕQGDQ /RJ-normal

GD÷ÕOÕPÕQÕQ $QWDN\D E|OJHVL - \ÕOODUÕ DUDVÕQGDNL PHYFXW U]JDU KÕ] YHULOHULQH J|UH :HLEXOO GD÷ÕOÕPÕQD EHQ]HU VRQXoODU RUWD\D NR\GX÷X WHVSLW HGLOPLúWLU 5]JDU SRWDQVL\HOL DoÕVÕQGDQ oDOÕúPDQÕQ HQ |QHPOL VRQXoODUÕ úX

úHNLOGH |]HWOHQHELOLU Zeminden 10 m

\NVHNOLNWH\DSÕODQ|OoPOHUQHWLFHVLQGH\NVHN U]JDU KÕ]ODUÕ \D] D\ODUÕQD GHQN JHOHQ +D]LUDQ YH (\OO D\ODUÕ DUDVÕQGD RUWDODPD m/s ile 4.6 PV DUDVÕQGD PH\GDQD JHOPHNWHGLU .DVÕP YH

$UDOÕND\ODUÕQGDLVHRUWDODPD m/s ve 1.4 m/s JLEL GúN GH÷HUOHU J|]OHQPHNWHGLU %|OJHGH J|]OHPOHQHQ U]JkU KÕ]ODUÕ .DVÕP D\ÕQGD PLQLPXP YH 7HPPX] D\ÕQGD LVH PDNVLPXP GH÷HUH XODúPDNWDGÕU 2UWDODPD U]JDU HQHUMLVL potansiyeli J|]OHP \DSÕODQ E|OJH LWLEDUL\OH RUWDODPD HQ \NVHN GH÷HU :P2_olarak

EXOXQPXúWXU 0DNVLPXP Jo 7HPPX] YH PLQLPXP Jo .DVÕPGD HOGH HGLOPHNWHGLU 5]JDUÕQ HQ JoO ROGX÷X \|QOHU LVH NX]H\

kuzey-GR÷X NX]H\NX]H\-GR÷X YH

JQH\JQH\-EDWÕ¶GÕU5]JDUWUELQOHULQLQ de bu \|QOHUGH NXUXOPDVÕ HQHUML WDúÕ\DQ U]JDUODUÕQ

\DNDODQPDVÕQÕ VD÷OD\DFDNWÕU <DSÕODQ

DUDúWÕUPDODU QHWLFHVLQGH U]JDU |OoPOHULQLQ yapÕOGÕ÷Õ $QWDN\D PHUNH]LQLQ U]JDU HQHUMLVL

SRWDQVL\HOLQLQ FHVDUHW YHULFL ROGX÷X

GH÷HUOHQGLULOPHNWHGLU %|OJH U]JDU

SRWDQVL\HOLQLQ PHUNH]H \DNÕQ úHEHNH\H GLUHN RODUDN ED÷OÕ ROPD\DQ D\GÕQODWPD VLVWHPOHUL WDUÕPVDO DUD]LOHULQ VXODQPDVÕ JLEL HOHNWULN YH mekanLN X\JXODPDODUGD NXOODQÕODELOHFH÷L X]XQ YDGH GH WHNQRORMLQLQ JHOLúLPL YH WUELQ PDOL\HWLQGHNL D]DOPD\D ED÷OÕ RODUDN úHEHNH\H GHGHVWHNYHUHELOHFH÷L|QHULOPHNWHGLU

Semboller

A : Alan (m2₎ c :HLEXOO|OoHNSDUDPHWUHVL(ms-1₎ FW(V) : Weibull birikPLúRODVÕOÕNIRQN fW(v) :HLEXOOGD÷ÕOÕPIRQNVL\RQX fLog-normal(V) : Log-QRUPDOGD÷ÕOÕPIRQNVL\RQX : Gamma fonksiyonu K :HLEXOOúHNLOSDUDPHWUHVL N 7RSODPGDWDVD\ÕVÕ PW :HLEXOOGD÷ÕOÕPÕLoLQRUWDODPDJo \R÷XQOX÷X(Wm-2₎

PL : Log-normal GD÷ÕOÕPÕLoLQRUW. Jo

\R÷XQOX÷XWm-2₎ P(V) 2UWU]JDUJFSRWDQVL\HOL(W) ȡ +DYDQÕQ\R÷XQOX÷XNJm-3₎ ı : Standart sapma (ms-1₎ V 5]JDUKÕ]Õ(ms-1₎ y 2UWDODPDJHUoHNGH÷HUOHUPV x : Weibull-Log-QRUPDOGD÷ÕOÕPÕLOH hesaplanan RUWKÕ]GH÷HUOHULPV ML : Maks. Olabilirlik Tahm. (EYO) LSM (Q.oN.DUHOHU<|QWHPL R² %HOLUOHPH.DWVD\ÕVÕ

RMSE : 2UW+DWD.DUHOHUL7RSODPÕQÕQ Karekökü

2ODVÕOÕN'D÷ÕOÕP

Fonk. WEIBULL LOG-NORMAL

METOD ML LSM ML LSM

R2 _99% _99% _98% _98%

(10)

ø. Mert, C. .DUDNXú)3HNHU P : Log-QRUPDOGD÷ÕOÕPÕLoLQ\HU parametresi V : Log-QRUPDOGD÷ÕOÕPÕLoLQ|OoHN parametresidir V 2UWDODPDU]JDUKÕ]Õ(ms-1₎ Weibull V :HLEXOOGD÷ÕOÕPÕQDJ|re RUWDODPDKÕ]PV-1₎ normal Log V : Log-QRUPDOGD÷ÕOÕPÕQDJ|UH RUWDODPDKÕ](ms-1₎

Kaynaklar

ANGD÷ ,S. A., Dinler, A., MHQWHú ù6 (2007). 5]JDU .DUDNWHULVWL÷LQLQ $QDOL]i, ÕY.

<HQLOHQHELOLU(QHUML.D\QDNODUÕ6HPSR]\XPX,23-29.

$NSÕnar E. K. ve $NSÕnar S., (2004). Determination of the wind energy potential for Maden-Elazig, Turkey, Energy Conversion and Management, 45, 18-19, 2901-2914.

$NSÕQDU ( . (2006). Statistical Investigation of Wind Energy Potential, Energy Sources Part A,

28, 9, 807-820.

%LOJLOL 0 ùDKLQ % YH .DKUDPDQ $ (2004). Wind Energy Potential in Antakya and øVNHQGHUXQ5HJLRQV7XUNH\Renewable Energy,

29, 1733-1745.

dHOLN $ 1 (2003). øVNHQGHUXQ %|OJHVLQH $LW 5]JDU +Õ]Õ 9H *o <R÷XQOX÷XQXQ dHúLWOL 0RGHOOHU.XOODQDUDNøVWDWLVWLNVHO2ODUDN$QDOL]L

,,<HQLOHQHELOLU(QHUML.D\QDNODUÕ6HPSR]\XPX,

ø]PLU

Eskin, N., Artar, H. ve Tolun, S., (2008). Wind (QHUJ\ 3RWHQWLDO RI *|NoHDGD ,VODQG LQ 7XUNH\

Renewable and Sustainable Energy Reviews, 12,

839-851.

*|NoHN0%D\ONHQ$YH%HNGHPLUù Investigation of Wind Characteristics and Wind Energy Potential in Kirklareli, Turkey,

Renewable Energy, 32, 1739-1752.

Hepbasli, A., Ozdamar, A. ve Ozalp, N., (2001). Present status and potential of renewable energy sources in Turkey, Energy Sources, 23, 33–50.

Karsli, V. M. ve Gecit, C., (2003). An investigation on wind power potential of Nurdagi-Gaziantep, Turkey, Renewable Energy, 28, 823–830. Ozerdem B., Ozer S. ve Tosun M., (2006).

Feasibility study of wind farms: A case study for Izmir, Turkey, Journal of Wind Engineering and

Industrial Aerodynamic,94, 725-743.

Ozgener, O. and Hepbasli, A. (2002). Current status and future directions of wind energy applications in Turkey, Energy Sources, 24, 1117–1129. g]JU 0$ (2006). KWDK\D 5]JDU

.DUDNWHULVWL÷LQLQ øVWDWLVWLNVHO $QDOL]L Ye Elektrik hUHWLPLQH 8\JXODQDELOLUOL÷L Doktora Tezi, 2VPDQJD]L hQLYHUVLWHVL )HQ %LOLPOHUL (QVWLWV (VNLúHKLU

Sahin, B. ve Bilgili, M., (2009). Wind Characteristics and Energy Potential in Belen-Hatay, Turkey, International Journal of Green

Energy, 6, 157-172

Sahin, B., Bilgili, M., ve Akilli, H., (2005). The Wind Power Potential of the Eastern Mediterranean Region of Turkey, Journal of

Wind Engineering and Industrial Aerodynamics, 93, 171-183.

Sen, Z. ve Sahin, A., (1997). Regional assessment of wind power in Western Turkey by cumulative semivariogram method, Renewable Energy, 12, 169–177.

7UNL\H 5]JDU (QHUMLVL %LUOL÷L 785(% 7UNL\H U]JDU HQHUMLVL LVWDWLVWLN UDSRUX

http://www.alternatifenerji.com/wp- content/uploads/turkiye-ruzgar-enerjisi-istatistik- raporu-2012-turkish-w%C4%B1nd-energy-statistics-report-2012.pdf , (03.03.2013). Ucar, A. ve Balo, F., (2009). Investigation of Wind

Characteristics and Assessment of Wind-Generation Potentiality in Uludag-Bursa, Turkey,

Applied Energy 86, 333-339.

Ulgen, K. ve Hepbasli, A., (2002). Determination of Weibull Parameters for Wind Energy Analysis of Izmir, Turkey, International Journal of Energy

Research, 26, 495-506.

hONH $ %DUDQ 7 (2005) .|SUoD\ \ÕOOÕN DNÕP YHULOHULQH X\JXQ RODVÕOÕN GD÷ÕOÕP fonksiyonu ve NXUDNOÕN DQDOL]L $QWDO\D <|UHVL øQúDDW