WIND ENERGY POTENTIAL OF COASTAL ERITREA: AN ANALYSIS OF SPARSE WIND DATA

Transcription

1 Solr Energy Vol. 66, No. 3, pp , 1999 Pergmon P II: S X(99) Elsevier Science Ltd All rights reserved. Printed in Gret Britin X/99/$ - see front mtter locte/ solener WIND ENERGY POTENTIAL OF COASTAL ERITREA: AN ANALYSIS OF SPARSE WIND DATA, *Lwrence Berkeley Ntionl Lbortory, MS , Berkeley, CA 94720, USA **Deprtment of Environmentl Studies, Sn Jose Stte University, Sn Jose, CA 95192, USA KAREN ROSEN*, ROBERT VAN BUSKIRK** nd KARINA GARBESI** Received 8 July 1998; revised version ccepted 15 Februry 1999 Communicted by DAVID MILBORROW Abstrct This pper describes n nlysis of historicl surfce wind dt for the smll country of Eritre, in northestern Afric. Winds in this region re directed by summer nd winter monsoons in ddition to diurnl lnd se effects. An nlysis of ntionl Eritren nd historicl Itlin wind records indicted mrginl wind resources in the centrl highlnds ner the Eritren cpitl of Asmer. An nlysis of wind speed records recorded t two sites in the southern port city of Aseb indicte men nnul 10-m wind speeds of 9.5 m s t the windier site. Surfce wind speed records for the Red Se suggest tht similr potentil my be found long the lower 200 km of the Eritren costline. Bsed on these findings, wind-generted electricity in this region should be substntilly cheper thn the current supply generted from imported diesel Elsevier Science Ltd. All rights reserved. 1. INTRODUCTION speeds over the southern Red Se is provided to ssist in predicting wind potentil long the The Eritren Deprtment of Energy is currently Eritren costline. investigting the vilbility of vriety of power sources needed to rebuild the Eritren infrstructure fter severl decdes of wr with Ethiopi. 2. STUDY AREA This report is bsed on study tht ws under- Eritre occupies the southernmost 1200 km of tken to supply the Eritren Deprtment of the western Red Se shoreline, including hundreds Energy with informtion bout wind-energy reof islnds ner the mjor ports of Mitsiw e sources in Eritre (Rosen, 1998). (Mssw) in centrl Eritre nd Aseb (Assb) in Some introductory studies of wind resources in the south (see Fig. 1). The cpitl, Asmer nd round Eritre hve previously been con- (Asmr), is locted in centrl Eritre on plteu ducted. Studies of the region surrounding the Red t over 2000 m elevtion. This high plteu nd Se nd Gulf of Aden hve issued promising the surrounding hillsides re known s the centrl results, especilly for costl res (Elliott nd highlnds. To the west nd est re the western Renne, 1987; Pllbzzer nd Gbow, 1991; nd costl lowlnds, respectively. The western Rdwn, 1987). Mulugett nd Drke (1996) lowlnds hve semirid climte nd consist conducted study of wind potentil for Ethiopi chiefly of desert hills nd svnn. On the estern tht included Eritre. Their nlysis included four border with the Red Se lies wide rid costl Eritren sites: three in the centrl highlnds, nd plin tht stretches the entire length of Eritre. one t Aseb on the southern cost. About 100 km south of the min Eritren port t This study reports men nnul wind speed Mitsiw e, the costl plin dips to 100 m below estimtes for nine sites not included in previous se level t the Dnkil Depression, n uninhbitstudies, including detiled wind ssessment ble desert tht divides the centrl highlnds in bsed on combined totl of 13 yers of wind the west from much smller rnge of mountins dt for two sites t the windy southern port city in the est. This second mountin rnge prllels of Aseb. In ddition, n nlysis of surfce wind the shoreline from the Dnkil Depression to beyond the Djibouti border, reching lmost 2000 Author to whom correspondence should be ddressed. m t its highest point. Tel.: ; fx: ; e-mil: The estimted popultion of Eritre is 3.6 kbrosen@lbl.gov million (Centrl Intelligence Agency, 1997). Of 201

2 202 K. Rosen et l. Fig. 1. Mp of Eritre showing topogrphy, mjor cities, the ntionl electricl grid, surrounding countries, nd mjor bodies of wter. tht number, roughly 20% inhbit the cpitl, from Mitsiw e to Asmer, nd then continue to Asmer. Although ccurte popultion counts for the south for combined length of bout 500 km other mjor cities re not vilble, it is estimted (see Fig. 1). A second grid with forml cpcity tht more thn hlf of the Eritren populce lives of 17 MW is locted t Aseb. In prctice, in the towns nd cities of the highlnds, due in however, the ctul genertion cpcity in Eritre prt to the wetter nd cooler climte found there. is pproximtely one hlf the forml genertion Becuse of the het nd ridity of the lowlnd cpcity becuse mny genertors re old nd res, settlements below 1000 m re reltively inefficient. sprse. The lrgest city in the costl lowlnds is Wind ptterns in the Red Se region re Aseb, port city of bout people locted controlled to lrge extent by two distinct t the southernmost tip of the Eritren costline, monsoons tht re seprted by 30 to 45 dys where summer tempertures verge C nd ech. During the Northest Monsoon from nnul rinfll verges bout 4 cm. November to Mrch, the combined effects of the The min ntionl electric grid hs forml Africn Equtoril Low nd the Siberin High cpcity of 40 MW. Trnsmission lines stretch pressure systems crete strong southest wind

3 Wind energy potentil of costl Eritre: n nlysis of sprse wind dt 203 Tble 1. Approximte (61 m s ) men nnul 10-m wind occuption in the erly 1930 s, dily verge wind speeds (MAWS) bsed on dt recorded t seven sttions in the Eritren highlnds nd western lowlnds, speeds were recorded t sttions long the Itlin- Sttion Geogrphicl coordintes MAWS built rilrod line from Mitsiw e to Keren. Men (m s ) nnul wind speeds t four of these sttions re Asmer N E 3 provided in Tble 2. Filfil N E 1 US Air Force Surfce Records ( ). Kerkebet N E 3 Twenty yers of hourly meteorologicl records Omhjer N E 2 Shmbiko N E 2 were vilble for severl Eritren cities, includ- Sh eb N E 2 ing Aseb ( E, N), for which dt Tsoren N E 2 set contining 13 discontinuous yers of observtions ( , ) ws obtined. The rithmetic men of wind speeds in this dt set tht is pulled through the nrrow Bb el Mndeb indicted men nnul wind speed of 8 m s t t the southern mouth of the Red Se. This wind Aseb. slows s it continues towrd Mitsiw e where it US Nvy Climtic Study of the Red Se. A converges with the ever-present northwest wind, 1982 climtic study of the Red Se conducted by result of the Azores High, t bout 168 north the United Sttes Nvy mpped monthly verges ltitude. Much of this ir mss is drwn south- with 18 sptil resolution. For seven of the 12 westwrd cross the Eritren highlnds towrd the months (October April), the report shows men Africn Low centered in southern Sudn. During nnul speeds of between 6 nd 10 m s off the the Southwest Monsoon from My to September, southern hlf of the Eritren costline. For the the Azores High nd the Pkistni Low cuse remining months (My September) the report surfce winds long the entire length of the Red indictes men wind speeds between 3 nd 5 Se to blow from the northwest down the length m s. of the Red Se nd out into the Gulf of Aden While these estimtes suggest tht wind re- (United Sttes Nvl Ocenogrphy Commnd sources in the highlnds my be indequte for Detchment, 1993). utility-scle wind genertion, one must keep in mind tht the highlnd sttions were not sited for 3. STUDY OVERVIEW wind prospecting purposes, nd so re unlikely to hve recorded the highest wind speeds in the In our initil serch, four sources of wind speed region. VnBuskirk et l. (1997) rgue tht the dt were found: recent Eritren dt, historicl chnneling of wind through the hills nd vlleys Itlin dt, United Sttes Air Force (USAF) of the highlnds is likely to crete res in which surfce records, nd US Nvl climtic study of wind speeds re significntly enhnced. The Eritthe Red Se. These dt sources re described ren Deprtment of Energy hs been collecting below. dditionl wind dt in the mountin psses ner Eritren dt ( ). In 1994, the Erit- Asmer in n ttempt to locte such sites. Estiren Deprtment of Wter Resources begn re- mtes bsed on preliminry mesurements indicording 15 min wind speed verges t seven cte the existence of sites with men nnul wind sttions locted in towns nd cities scttered speeds exceeding 5 m s. throughout the highlnds nd western lowlnds of Wind dt obtined for Aseb nd the Red Se Eritre. Less thn one yer of dt ws vilble produced more promising results thn did dt for for this study; however, rough (61 m s ) men centrl Eritre. The USAF surfce records for nnul wind speed estimtes were derived nd re Aseb indicted men nnul wind speed of 8 summrized in Tble 1. m s, while the Nvl report for the Red Se Itlin dt ( ). During the Itlin indicted men monthly wind speeds s high s Tble 2. Men nnul 10-m wind speeds (MAWS) bsed on historicl Itlin dt for four sttions in the Eritren highlnds, Sttion Geogrphicl coordintes MAWS (m s ) Asmer N E 2.7 Fghen N E 2.1 Keren N E 1.9 Mitsiw e N E 3.7

4 204 K. Rosen et l. 10 m s just off the southern cost. Although multi-yer dt set into two subsets corresponding electricity demnd in Eritre is highest in the to the two sesons. From this point on, My cpitl city of Asmer, we chose to pursue more September will be referred to s the summer detiled study of the Aseb re bsed on the wind seson while October April is referred to s the speeds recorded there. Anlyses of winds t two winter seson. Aseb sites nd of winds over the Red Se re Ech sesonl subset ws further divided cpresented below. cording to whether the observtions were recorded t the Airport or the Seport sttion. The 4. ASEB DATA AND ANALYSIS resulting four subsets were nlyzed independently. A preliminry sttisticl nlysis of the four The Eritren Civil Avition Deprtment min- dt subsets is presented in Tble 3. tins two meteorologicl sttions t Aseb, one t Although the number of observtions did not the Aseb Airport bout 15 km northwest of Aseb differ significntly on month to month bsis, 1 nd one t the Seport within the city. The observtion ptterns did vry widely on n hourly Airport sttion is locted in flt, open plin t bsis. Midnight nd erly morning observtions bout 10 m elevtion. The Seport sttion is t the were comprtively few, nd for the first eight shoreline, sheltered by buildings on the northwest yers were prcticlly non-existent. To compenside (see Fig. 2). ste for the fct tht more observtions were mde The wind speed observtions in the USAF dt during the dytime when wind speeds re highest, set for Aseb were estimted nd recorded by the four dt subsets were ech divided into eight personnel of the Eritren nd/ or Civil Avition 3-h bins tht were nlyzed seprtely. Becuse Deprtment. Although these wind speed estimtes records for lte evening nd erly morning hours were bsed on the rottion of stndrd 10-m were not recorded on regulr bsis until fter the nemometers, wind speeds were visully esti- observtion site ws moved to the Seport, six of mted by personnel rther thn mechniclly the 16 dt subsets for the Airport contined estimted by dt logger. A recent comprison insufficient dt for nlysis. Fig. 3 illustrtes the between simultneous humn wind speed esti- dt divisions nd the number of observtions in mtes nd 10-m nemometer redings showed n ech subset. verge error of 3% nd n verge bsolute error To derive the men nnul wind speed t the of 11%. Airport, it ws necessry to estimte men wind Until 1991, wether observtions recorded speeds for the :00, 0:00 nd 3:00 dt subsets. every 3 h were rchived by the United Sttes Air First, men vlues were clculted for the Airport Force Environmentl Technicl Appliction Cen- nd Seport dt subsets tht contined sufficient ter, 1986 (USAFETAC). Observtions reported dt. A sctter plot ws then creted using the before 1986 were tken t the Airport sttion, Airport vlues s the bscisss nd the Seport while observtions reported fter 1986 were tken vlues s the ordintes (see Fig. 4). Using regrest the Seport sttion. The Ntionl Climtic Dt sion nlysis, liner correltion ws derived Center (NCDC) provided dt set contining between the time-correlted pirs of men wind thirteen yers ( , ) of US 2 speeds t the two sttions (R ). Ech of the Air Force surfce observtions for Aseb. After three missing vlues for the two sesons were removing incomplete or otherwise inconsistent then clculted s m5 mms1 b, where mnd ms dt records, over 5000 observtions remined for re the men wind speeds t the Airport nd ech sttion. Seport, respectively, nd m , nd b 5 As discussed bove, wether ptterns t Aseb re the slope nd y-intercept, respectively, cn be divided into two distinct sesons. For this found in the regression nlysis. nlysis, men monthly wind speeds clculted by To provide ccurte nnul wind speed disthe United Sttes Nvl Ocenogrphy Commnd tributions for the two Aseb sites, it ws necessry Detchment (1993) were used to divide the entire once gin to estimte vlues for the empty dt bins t the Airport. Therefore, we plnned to clculte Weibull prmeters for the subsets with 1 The US Air Force dtbse did not indicte the existence of sufficient dt, nd then use them to estimte the two seprte sttions. An pprent chnge in men nnul Weibull prmeters for the subsets with insuffiwind speed nd observtion ptterns lte in 1986 lerted us to the sitution. The existence of the two sttions nd dte cient dt. From these estimted prmeters, of trnsition were ffirmed by visiting the two sttions nd model distributions for the empty subsets could reviewing the logs. then be constructed. At this point, however, it

5 Wind energy potentil of costl Eritre: n nlysis of sprse wind dt 205 Fig. 2. Mp showing the Airport nd Seport meteorologicl sttions t Aseb, where the US Air Force dt were recorded. becme cler tht the wind speed dtbse for to the observed distribution bove 0 m s, nd Aseb contined n unusully lrge number of clms re considered seprtely. This method clms. This presented problem becuse the tends to provide more conservtive estimte of stndrd Weibull distribution does not llow for men wind speed by ssuming tht the reported wind speed of 0. To resolve this problem, we frequency of clms is correct, wheres the stnemployed method described by Mulugett nd drd Weibull distribution ssumes tht the fre- Drke (1996) in which Weibull distribution is fit quency of clms is 0. This is prticulrly im- Tble 3. Results of preliminry sttisticl nlysis of US Air Force wind speed dt for Aseb Airport Seport Summer Winter Summer Winter No. of observtions Minimum (m s ) Mximum (m s ) Arithmetic men (m s ) Vrince (m s ) Stndrd devition (m s ) Stndrd error Skewness Kurtosis

6 206 K. Rosen et l. Fig. 3. Division of the US Air Force dt for Aseb, showing number of dt points in ech sesonl 3-h bin. portnt in the cse of the Aseb dt, where the distribution is simply (12s) times the stndrd observed frequency drops bruptly between 0 nd Weibull distribution. 1 m s, nd then follows the expected Weibull For ech seson, this three-prmeter Weibull distribution closely. model ws fit to the wind speed frequency To the stndrd Weibull prmeters k nd A is distributions for the 13 subsets contining suffidded vrible s denoting the frequency of cient dt. A best fit ws obtined by minimizing clms. The eqution of the three-prmeter the sum of the squred differences between points Weibull probbility density function is: on the observed frequency distribution nd the Weibull distribution. After clculting the three s,tv50 prmeters of k, A nd s for ech subset, sctter f(v) 5H k k 2(v /A) k (1 2 s)(kv /A ) exp, for v. 0 plot ws then creted using the Airport vlues s the bscisss, nd the Seport vlues s the (1) ordintes (see Fig. 5). As cn be seen in Fig. 5(), the sctter plot of k-vlues found t the Aseb Airport nd Seport where v is the wind speed, s is the observed 2 did not indicte cler liner correltion (R 5 frequency of clms, A is the mgnitude prmeter, ); therefore, we used the verge sesonl k k is the shpe prmeter, nd f(v)dv is the frction vlue t the Airport to estimte the three missing of time the velocity dt is in bin centered t v, 2 vlues. For both A nd s, cceptble liner with bin size dv. Note tht for v.0, the model correltions were determined between the two 2 2 sttions (R nd R , respectively). The missing vlues were then clculted s y5mx1b, where y nd x re the prmeters t the Airport nd Seport, respectively, nd m nd b re the slopes nd y-intercepts found in the regression nlyses respectively. Men wind speeds could then be estimted s (Mulugett nd Drke, 1996): m 5 AG(1/k 1 1)(1 2 s) (2) Sesonl wind speed frequency distributions t the Airport were clculted s the verge of the five observed nd three estimted frequency distributions for ech 3-h bin for ech seson. Sesonl wind speed frequency distributions t Fig. 4. Sctter plot showing the correltion between men wind speeds t the Aseb Airport nd Seport. 2 Mny different methods were used to estimte the Weibull prmeter of k for the empty bins, including verging, liner correltions nd non-liner correltions. All methods provided nerly identicl men nnul wind speeds (60.5 m s ). We chose to present the verging k-vlue method becuse, of the methods tested, it resulted in the most conservtive wind speed estimtes.

7 Wind energy potentil of costl Eritre: n nlysis of sprse wind dt 207 Fig. 5. Sctter plots showing correltions between Airport nd Seport k, A nd s vlues. distribution, nd f s(v) nd f w(v) re the summer nd winter wind speed frequency distributions, respectively. Three-prmeter Weibull distribu- tions were then fit to the resulting nnul wind speed distributions to derive Weibull prmeters for the ggregted dt t ech site. Wind power density is the mount of wind power vilble in plne perpendiculr to the direction of the wind. In this study we clculte the men nnul wind power density for ech 3-h dt bin s: the Seport were simply clculted s the verge of the eight observed frequency distributions. For this study, we defined the summer seson s the five months from My to September nd the winter seson s the seven months from October to April; therefore, nnul distributions for ech sttion were clculted s: 5 7 f(v) 5] f s(v) 1] f w(v) (3) where f(v) is the nnul wind speed frequency

8 208 K. Rosen et l. 1 hve chosen to present the mjority of vlues t 3 O ] rv f(v) (4) 10 m without mking ny ssumptions bout the 2 wind speeds t higher hub heights. Men wind where r is the verge observed ir density, v is speed vlues bsed on USAF surfce records re the wind speed, nd f(v) is the wind speed estimted to be ccurte within 5% of given frequency distribution. Men nnul wind power vlues. density is clculted s the rithmetic verge of Tble 4 shows men wind speeds clculted the 3-h bin wind power densities. from observed wind speed vlues. Vlues in itlics t :00, 0:00 nd 3:00 t the Airport were 5. RED SEA DATA AND ANALYSIS estimted s described in Section 4. Tble 5 shows the prmeters obtined using The Comprehensive Ocen-Atmosphere Dt three-prmeter Weibull fits to the observed 3-h Set (COADS) is globl collection of mrine wind speed distributions. Agin, vlues for :00, observtions recorded between 1854 nd :00 nd 3:00 re estimted s described in tht is widely used for studies of ocen winds, Section 4, where men wind speeds re bsed on temperture, nd het budget. Due to insufficient Eq. (2). The mjority of men 3-h wind speed sptil resolution (18), observtions recorded be- vlues presented in Tble 5 re within 2% of the fore 1940 were discrded. The portion of dt set observed men wind speeds. The gretest differretined for this study contined over ence between clculted vlues nd observed observtions. vlues ws 3.3% t 0:00 t the Seport. To ccount for uneven temporl smpling in Fig. 6 depicts the men diurnl wind speed the dt set, the dt were divided into sesonl vritions t the Aseb Airport nd Seport. Esti- 6-h bins, resulting in eight dt subsets. Men mted vlues t :00, 0:00 nd 3:00 re circled wind speeds were clculted for ech position in Fig. 6(b). The higher middy wind speeds contining dt in ll eight dt subsets. The shown in both grphs suggest potentil for inrithmetic verge of wind speeds in ech 0.18 bin cresed power supplies during the pek demnd ws then clculted for ech subset. Averge period. Obvious similrities between Figs. 6() sesonl wind speeds were derived s the verge nd 6(b) support the ssumption tht wind speeds of the four 6-h subsets for ech seson for ech t the two sttions re closely relted bin. Men nnul wind speeds were clcu- Fig. 7 shows the three-prmeter Weibull fits to lted for ech 0.18 bin s the sum of 5/12 the the wind speed distributions t the Aseb Airport summer verge nd 7/ 12 the winter verge. nd Seport. In Fig. 7(), the Observed distribution t the Airport is ctully the rithmetic 6. RESULTS verge of the five observed distributions nd three estimted distributions (see Section 4). The Unless otherwise noted, results presented here Observed distribution in Fig. 7(b) is the rithrepresent wind speed vlues t 10 m height. It is metic verge of the eight observed 3-h disexpected tht wind speeds t typicl turbine hub tributions t the Seport. heights of 30 m or more would be higher thn The mount of electricity tht cn be generted those presented here. In some cses, however, t Aseb depends on severl fctors, including the winds hve been known to decrese with height, hub height, rotor size, nd spcing of the wind prticulrly in mountinous res. Therefore, we turbines, nd lso the estimted efficiencies of the Tble 4. Results of the nlysis of US Air Force dt for Aseb, showing men sesonl nd nnul 10-m wind speeds (in m s ) for 3-h periods t the Aseb sttions Eritren time Airport Seport Summer Winter Annul Summer Winter Annul 6: : : : : : : : Averge Figures in itlics represent vlues estimted by liner correltion between sttion wind speeds.

9 Wind energy potentil of costl Eritre: n nlysis of sprse wind dt 209 Tble 5. Three-prmeter Weibull prmeters nd men 10-m wind speeds derived from them for sesonl 3-h periods t the Aseb sttions Eritren time Airport Seport k A s Wind speed k A s Wind speed (%) (m s ) (%) (m s ) Summer 6: : : : : : : : Summer verges Winter 6: : : : : : : : Winter verges Annul verges Figures in itlics represent vlues estimted using correltions between sttion prmeters k, A nd s. turbine, rry nd power system. The clcultions within the town. This suggests tht the Seport presented in Tble 6 use the following ssump- estimte is not representtive of the high wind tions: (i) The rotor dimeter (D) is 20 m; (ii) the power potentil in the surrounding region. turbine spcing is 10D 35D; (iii) the rry nd There were severl confounding fctors in the system efficiency is 75%. US Air Force dt set for Aseb, including the A typicl nnul verge wind power density loction chnge in 1986, the lck of nighttime 22 for utility scle energy production is 450 W m observtions t the Airport nd the high pert turbine hub height (Cvllo et l., 1993). The centge of clms recorded t both sttions. To wind power densities shown in Tble 6 re high ccount for these fctors, severl different methbecuse of the very high wind speeds during the ods of nlysis were used s described in Section winter months t Aseb. It should be noted, 4. It is interesting t this point to note the however, tht the wind power supply between differences between these results. A summry of My nd September is expected to be consider- the results obtined using four different methods bly lower. of nlysis is presented in Tble 7. Fig. 8 shows pproximte (61 m s ) men As noted previously, inconsistent smpling nnul wind speeds in the Red Se long the methods fvored the higher dytime wind speeds, southern Eritren costline. According to these resulting in the rtificilly high vlues described results, men nnul wind speeds long the lower s Unbinned. Stndrd Weibull fits to the 3-h 200 km of the southern Eritren costline re in distributions lso produced higher vlues becuse excess of 6 m s. This suggests tht sites with they filed to recognize the high percentge of high wind power potentil my be found long clms recorded t Aseb. The liner correltion nd much of the lower Eritren costline. three-prmeter Weibull fit methods used in this nlysis resulted in much more conservtive nd 7. DISCUSSION probbly more ccurte men nnul wind speed vlues. The results of this study indicte tht the men Wind development t Aseb depends minly on nnul wind speed difference between the Airport economic fctors. Becuse of the uncertinties in nd the Seport is bout 2.5 m s. We ttribute wind speeds, cost estimtes t this stge re this to the different levels of wind exposure t the highly unrelible; however, the cost of windtwo sttions: the Airport is locted outside the city generted electricity t Aseb will lmost certinly nd hs excellent wind exposure, wheres the be lower thn the current diesel-generted elec- Seport sttion is locted in developed re tricity. The Cliforni Energy Commission (CEC)

10 0 K. Rosen et l. Fig. 6. Grphs showing men diurnl wind speed vritions t the Aseb Airport nd Seport. estimtes tht the cost of wind power t good sites is the reltively smll cpcity of the Aseb power is bout US$13 per MJ (4.6 /kw h) (Cliforni system. Given tht the combined cpcity of the Energy Commission, 1997). All else being equl, power system is only 17 MW, the Aseb utility this cost is lredy less thn the cost of diesel fuel without expnsion could ccommodte only bout t Aseb, which is bout US$18 per MJ (6.5 3 MW of wind (Grubb nd Meyer, 1993). This is / kw h). Bsed on the unusully high men minute frction of the totl vilble wind nnul wind speed t Aseb, it is sfe to ssume power t Aseb (see Tble 6). tht the cost of wind power would be even lower The mple lnd nd wind power resources t thn the CEC estimte. Aseb hve the potentil to offer more power thn There re severl problems ssocited with the entire country could bsorb in the foreseeble wind development t Aseb. The min fctor future. It therefore seems worthwhile to consider constrining wind power development ner Aseb options for mximizing utiliztion of this re-

11 Wind energy potentil of costl Eritre: n nlysis of sprse wind dt 1 Fig. 7. Grphs showing three-prmeter Weibull fits to the observed nnul wind speed distributions t the Aseb Airport nd Seport. Tble 6. Projected wind speed, cpcity fctors, power, nd energy output t Aseb, t 10 nd 30 m hub height Airport Seport 10 m 30 m 10 m 30 m Averge nnul wind speed (m s ) Wind power density (W m ) Cpcity fctor (%) Wind power vilble per turbine (kw) Electricl power generted per turbine (kw) Annul energy output per turbine (TJ) Annul energy output per km (TJ km ) Height extrpoltions to 30 m bsed on the 1/7 power lw. Cpcity fctors bsed on the Flowind AWT-27 power curve.

12 2 K. Rosen et l. Fig. 8. Mp showing men nnul wind speeds in the southern Red Se off the Eritren costline. mission lines my be prohibitively expensive nd power losses uncceptbly high. It my be pos- sible, however, to find high-qulity costl wind power sites tht re closer to the power supply system in the centrl highlnds. The nlysis of Red Se winds indictes tht high wind speeds my extend s fr s north ltitude, bout 300 km from the centrl grid t Mitsiw e. If current wind prospecting efforts in this region re successful, trnsmission between these two loc- tions my be fesible. Reserch continues to be source. A pln tht would both further exploit the wind resource nd level the sesonl lods is coopertive effort with Ethiopi, in which winter wind power from Aseb is trded for summer hydropower from the Blue Nile region. However, this option my not be fesible due to recent politicl conflicts with Ethiopi. Another option for distributing excess supply my be to connect the power system t Aseb to the ntionl grid in the centrl highlnds. Although this option is preferble in mny respects, construction of trns- Tble 7. Results of different dt nlysis methods for the Aseb Airport nd Seport, showing Weibull prmeters k nd A, men nnul wind speeds (MAWS) nd men nnul wind power densities (WPD), ll t 10 m height Method Airport Seport k A MAWS WPD k A MAWS WPD (m s ) 22 (W m ) (m s ) 22 (W m ) Undjusted b Liner correltion c Three-prmeter Weibull d Stndrd Weibull Undjusted, unbinned rithmetic men of ll dt. b Dt divided into subsets s shown in Fig. 6. Liner correltion between subset mens used to estimte mens for empty bins. c Dt divided into subsets s shown in Fig. 6. Correltions between three-prmeter Weibull prmeters, k, A nd s, used to estimte prmeters for empty bins. d Dt divided into subsets s shown in Fig. 6. Correltions between stndrd Weibull prmeters, k nd A, used to estimte prmeters for empty bins.

13 Wind energy potentil of costl Eritre: n nlysis of sprse wind dt 3 conducted in the Eritren highlnds, but further REFERENCES investigtion into power trnsmission from the Cliforni Energy Commission (CEC) (1997) 1996 Energy southern Eritren cost to the highlnd re is lso Technology Sttus Report, CEC Report P , wrrnted. Scrmento, CA, pp Cvllo A. J., Hock S. M. nd Smith D. R. (1993) Wind Further funding for this project hs been pro- energy: Technology nd economics. In Renewble Energy: cured from the Globl Environment Fcility Sources for Fuels nd Electricity, Johnsson Thoms B., (GEF), joint progrm between the United Kelly Henry, Reddy Amuly K. N. nd Willims Robert H. (Eds.), Islnd Press, Wshington, DC. Ntions Development Progrm (UNDP), United Centrl Intelligence Agency (CIA) (1997) World Fctbook. Ntions Environment Progrm (UNEP) nd the Ntionl Technicl Informtion Service, United Sttes Deprtment of Commerce, Springfield, VA. World Bnk. Results of full scle wind prospect- Elliott D. nd Renne S. (1987) Wind energy resource ssessing effort undertken under this grnt re ex- ment of Egypt. In Proc. 6th ASME Wind Energy Symp. pected in presented t the 10th Annul Energy-Sources Technology Conf. nd Exhibition, Dlls, TX, Februry SED- Vol CONCLUSIONS Grubb M. J. nd Meyer N. I. (1993) Wind energy: Resources, systems, nd regionl strtegies. In Renewble Energy: According to these results, the Eritren cost- Sources for Fuels nd Electricity, Johnsson T. B., Kelly H., Reddy A. K. N. nd Willims R. (Eds.), pp , line hs n outstnding wind resource, prticulrly Islnd Press, Wshington, DC. in the Aseb re. Of the two sites monitored t Mulugett Y. nd Drke F. (1996) Assessment of solr nd Aseb, the Aseb Airport site ppers to be the wind energy resources in Ethiopi. II: Wind energy. Solr Energy 57, more promising. Existing dt sources indicte Pllbzzer R. nd Gbow A. (1991) Wind resources of men nnul wind speeds of 9.5 m s t the Somli. Solr Energy 46, Aseb Airport t 10 m height. Such winds cn Rdwn A. (1987) Wind energy in Sudi Arbi. In Alterntive Energy Sources VII. produce more power thn the Aseb power system Rosen K. (1998) An nlysis of the potentil for utility-scle cn bsorb, but limited development my provide wind power genertion in Eritre. Mster s Thesis, Sn Jose Aseb with less expensive power source thn the Stte University. VnBuskirk R., Grbesi K. nd Rosen K. (1997) Wind current diesel supply. The nlysis of Red Se resource ssessment of Eritre, Afric: Preliminry results surfce winds presented in this study suggest tht nd sttus. In Proc. 2nd Europen Conf. on Wind Engineering, Genov, Itly, Solri G. (Ed.), June similr wind resource potentil extends s fr s United Sttes Nvl Ocenogrphy Commnd Detchment 200 km north of Aseb long the Eritren cost- (1993) US Nvy Regionl Climtic Study of the Red Se line. nd Adjcent Wters. Ntionl Ocenic nd Atmospheric Administrtion, Asheville, NC. United Sttes Air Force Environmentl Technicl Appliction Acknowledgements This work ws supported by Sn Jose Center (USAFETAC) (1986) Climtic Dtbse Users Stte University, Sn Jose, Cliforni. The uthors would lso Hndbook No. 4, DATSAV2 Surfce. USAFETAC/ UH-86/ like to thnk the Eritren Deprtment of Energy for its 004. coopertion nd ssistnce.