Analysis of Wind Power Potential and Electric Energy in the Algerian Sahara Regions

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1 International Journal o Applied Engineering Research ISSN Volume 1, Number 7 (17) pp Analysis o Wind Power Potential and Electric Energy in the Algerian Sahara Regions M. DAHBI 1,, A. BENATIALLAH, M.SELLAM, B. DEENAI 1 1 Department o Material Science, Faculty o Exact Sciences, Uniersity o, Algeria, ENERGARID, Laboratory, Uniersity o, Algeria LEESI, Laboratory, Uniersity o, Algeria, *M. DAHBI, P.B.417, independence Street, Algeria, Abstract The wind energy is one o the most signiicant and rapidly deeloping renewable energy sources in the world and it proides a clean energy resource, which is a promising alternatie in the short term in Algeria. The main purpose o this paper is to compared and discuss the wind power potential in three sites located in sahara o Algeria (south west o Algeria) and to perorm an inestigation on the wind power potential o desert o Algeria. In this comparatie, wind speed requency distributions data obtained rom the web site SODA.com are used to calculate the aerage wind speed and the aailable wind power. The Weibull density unction has been used to estimate the monthly power wind density and to determine the characteristics o monthly parameters o Weibull or these three sites. The annual energy produced by the BWC XL.1 1KW wind machine is obtained and compared. The analysis shows that in the south west o Algeria, at 1 m height, the aailable wind power was ound to ary between W/m and 1.4 W/m. The highest potential wind power was ound at, with 1h per day and the mean wind speed is aboe 6 m/s. Besides, it is ound that the annual wind energy generated by that machine lie between 51KWh and 164.Wh. Howeer, the wind resource appears to be suitable or power production on the sahara and it could proide a iable substitute to diesel oil or irrigation pumps and rural electricity generation. Keywords: Wind Power; Electric Energy; Wind Turbine; Operating Hours; Wiebull s Parameters. INTRODUCTION The south o Algeria, characterized by the desert nature, presents a ery low population density. Less than thirty per cent o the population lies in this part o the country. In addition, in large areas o the southern Algeria there is no existence o main grid line and the extension o the conentional utility grid to the remotely located community is uneconomical. Fuelling o engines in remote areas is diicult and costly [1].. The distribution o wind speeds is important or the desing o wind arms, power generators and agricultural applications such as the irrigation. It is not easy tas to choose a site or a wind turbine because many actors hae to be taen into account. Compared to the other renewable energy resources, such as tidal or solar energy, wind energy has a more ariable and diuses energy lux. In order to maximize the beneit o this resource it is ery important to be able to describe the ariation o wind elocity at any gien site under consideration or the deelopment o wind energy conersion system.[-]. The ariation o wind elocity using the Weibull two parameter density unction.there are seeral methods to calculate the two Weibull parameters, c, and [4-5].I the mean and ariance o the wind speed are nown can be determined c and directly, in this paper an acceptable approximation is used [6].. In Algeria, wor on wind energy resource assessment dates bac to 1976 when a wind atlas was deeloped by using wind speed data rom 7 locations [7]. This Algerian Wind Atlas containing the wind results statistics o 7 meteorological stations or the period spanned between Dahbi and all [8] calculated the monthly Weibull parameters or s site at 1m and ound that the wind speed was well represented by the Weibull distribution unction, the data wind speed measured at the 1th meters and collected during 876hours by a wind obseration station web site weather underground (The global weather data could be obtained rom internet ). Algeria has a ast uninhabited land area where the south (desert) represents the part with considerable wind regime. This Paper present the monthly wind speed and wind power density to assess the wind power potential or three Algerian Sahara regions named, and located South Western o Algeria. The Weibull density unction has been used to estimate the two monthly Weibull parameters, c, and at these three sites. The monthly electric power output o BWC XL.1 1KW wind turbine and the monthly operating hours are calculated and simulated. Simulation is perormed using Matlab sotware enironment. 1

2 International Journal o Applied Engineering Research ISSN Volume 1, Number 7 (17) pp SIMULATION OF WIND POWER AND WIND TURBINE CHARACTERISTICS Weibull density unction : The wind speed probability density unction can be calculated as [9]:. c c. exp c 1 Where () is the probability o obsering wind speed, c is the Weibull scale parameter and is the dimensionless Weibull shape parameter. Basically, the scale parameter, c indicates how windy a wind location under consideration is, whereas the shape parameter,, indicates how peaed the wind distribution is (i.e. i the wind speeds tend to be ery close to a certain alue, the distribution will hae a high alue and be ery peaed)[9-1]. Once the mean speed is nown, the ollowing approximation can be used to calculate the Weibull parameters, and c [11] : (1) 1.9. () c 1 1 Where the aerage wind speed is n 1 i n i i1 And the gamma unction o (x) (standard ormula) calculated.[1]: x e u u x 1 du The main limitation o the Weibull density unction is that it does not accurately represent the probabilities o obsering zero or ery low wind speeds [1]. The Aerage Power in the Wind : The aerage power in the wind can be expressed as [1]: () (4) (5) 1 p A ( ) d (6) The aerage wind power, expressed in W / m calculated using the ollowing equation:, can be 1 p 1 1 Where p is the aerage power in the wind [W/m^]; is the gamma unction ; is the Weibull shape parameter; is the aerage wind speed[m/s], is the air density (Kg/m). Power Output Characteristics o Wind Turbine : As dierent generators hae dierent power output perormance cures, so the model used to describe the perormance is also dierent.in literature [14-15], the ollowing equation is used to simulate the power output o wind turbine: C PR * ( C R) R C Pw ( ) P ( ) 8 R R ( C & ) (7) Where P R is the rated electrical power [W]; c is the cut-in wind speed[m/s]; R is the rated wind speed[m/s] ; is the cut-o wind speed o the wind turbine[m/s]; is the Weibull shape parameter. The operating hours o the wind turbine : The cumulatie distribution unction can be used or estimating the time or which wind is within a certain elocity interal. The monthly operating hours in a year can be calculated lie ollow [16]: p. c c c c exp exp tm Where c is the cut-in speed, is the cut-o speed, m (9) t is the monthly hours number ( day chosen or each month), is the Weibull shape actor and c is the Weibull scale actor. CASE STUDY FOR WIND POWER POTENTIAL ANALYSIS Three Algerian Sahara sites named, and located South Western o Algeria was selected in this wor. It was based around an oasis o the Sahara Desert. A meteorological data collected during 65day by a wind obseration station web site www. SoDa.com (Serices or Proessionals in Solar Energy and Radiation)[17]. (The global whether data could be obtained rom internet) is used or analysis in this paper. Which geographical coordinates are presented in the table 1 [7]. 11

3 International Journal o Applied Engineering Research ISSN Volume 1, Number 7 (17) pp Table.1: Geographical Coordinates o Selected Sites Sites Longitude Latitude Altitude 15 W 1 8 N 86m 17 E 7 49 N 6m 8 8 W 7 4 N 4m ly Weibull Parameters and Wind Power Density : Once the monthly mean wind speed is nown, the monthly Weibull parameters and c can be obtained. In Fig., are shown histograms o the monthly mean wind speed at selected sites. The monthly Weibull parameters and c are itted in the ig. and ig.4 respectiely, Yearly Weibull Density Function : The calculation results meet the Weibull distribution. From the recorded wind data, the yearly Weibull parameters, c and mean wind speed o three Algerian Sahara sites are presented in the table. Table : Weibull Parameters o Selected Sites. Sites K C(m/s) Vmean(m/s) m/s m/s m/s 4.7 Wind Speed (m/s) Fig.: ly mean wind speed or selected sites Using Equ.1.The Weibull distribution is shown in ig.1 or the three selected sites Weibull distribution(%) =1.85 c=4.1m/s =. c=5.m/s =.4 c=6.66m/s Weibull parameter K Fig.: ly.weibull parameter or selected sites Wind Speed (m/s) Fig. 1 : The Yearly Weibull distribution o Selected sites It is clear rom the igure that the site o has the highest alue o and c compared with the site o and. The analysis o Weibull parameters shows that the shape parameter aries between 1.85 and.4 while the scale parameter c aries between 4.1m/s and 6.66m/s. It can be seen that the highest alues o and c are ound in, located in the southwest part o the country. Whereas the lowest alues o the two parameters were ound in. It can be seen, that the Weibull approximation o these sites encouraging prospect or wind energy applications. Weibull parameter c (m/s) Fig.4: ly.weibull parameter c or selected sites It is clear rom the ig. and ig.4,that the shape parameter aries between 1.79 and.9 while the scale parameter c aries between 6.77m/s and.9m/s at. It can be seen that the highest alues o and c are ound in June. 1

4 International Journal o Applied Engineering Research ISSN Volume 1, Number 7 (17) pp Whereas the lowest alues o the two parameters were ound in December. It is clear rom these igures that the shape parameter aries between 1.7 and. while the scale parameter c aries between 8.5m /s and 4.99m /s at. It can be seen that the highest alues o and c are ound in June. Whereas the lowest alues o the two parameters were ound in September. The analysis o Weibull parameters shows that the shape parameter aries between 1.65 and.7 while the scale parameter c aries between.1 m/s and 5.57 m/s at. It can be seen that the highest alues o and c are ound in April. Whereas the lowest alues o the two parameters were ound in December. The results show that the parameters are distinctie or dierent months in a year at the selected sites, which means the monthly wind speed distribution diers oer a whole year. It is clear that the mean wind speed increases during spring months and decrease during all months. ly Wind Power Density : With the aboe equation and the monthly Weibull parameters, the monthly wind power density can also be calculated. The results are gien in ig.5. Wind potentail (W/m ) Fig.5: ly wind potential at selected sites. In Figure 5, are shown histograms o the wind potential at selected sites. The results indicate that a potential o 1.4 W/m, at 1 m a.g.l., is aailable or the site o representing the maximum alue, while the lowest alue is ound at site with a potential o 8.7 W/m, but the site o rans in the second position with a wind power density o W/m. It is clear rom the results that the aerage wind power density is distinctie or dierent months at selected sites. In February to June, the wind power is high, but low in the all months. This is due to the ariation o the wind speed and Weibull parameters between summer months and winter months at each selected sites. It can be seen that the highest alues o wind power potential is ound in compared to the other sites. The analysis o the results indicates that there is potential or wind energy utilization in southwest o Algeria. The wind resource is good enough in southwest o Algeria, especially and, to supply people with basic energy needs. MONTHLY WIND POWER PRODUCED BY BWC XL.1 TURBINE To analysis the eect o the wind turbine characteristics on the wind power generation, a wind turbine o BWC XL.1 1KW generator with a synchronous permanent magnets machine is chosen in this study based on the calculated monthly mean wind speed (is high to.5 and low to 1m/s). The cut-in speed is.5m/s, the cut-o speed is 1m/s and the rated electrical power o the turbine is 1W(at rated wind speed 11m/s).Using the Eq.7 and Eq.8,the aerage monthly power generated by the wind turbine and the operating hours o the wind turbine in a year can be calculated or the three Algerian Sahara sites. The analysis o the results indicates that the operating hours changes in dierent selected sites. The highest 1h/day occurs while the lowest is 16h/day at s site. The operating hours o the site o is 19h /day.the trend is not in accordance with the trend o monthly wind power density, because the operating hours is determined not only the wind data distribution but also by the perormance o the wind turbine. For selected sites, the monthly energy generated by the BWC XL.1 wind machine generated is calculated and the results are gien in ig6. The results shows that or each month the energy generated is dierent, arying rom 66.97KWh to 1.8KWh at site. The wind turbine can generate electrical power in the site o amounting to 164.Wh per year. The monthly energy generated by the BWC XL.1 wind machine aries between 8.74 KWh and KWh at. The lowest energy output is generated in the s site, it is aries the 7.5 KWh to 89. KWh. The total annual wind energy output is 51KWh per year and KWh per year at and respectiely The ly Wind Energy Output by BWC XL.1 (KWh) CONCLUSION Fig.6: ly wind energy output o Bergy XL.1 turbine The proposed simulation model is ound applicable or assessing the potential o wind power generation at a location. From the case study, it is ound that it is imperatie to account or the monthly dierence o wind speed using Weibull estimation as the wind energy potential can ary signiicantly. According to result s o simulation, it is shown 1

5 International Journal o Applied Engineering Research ISSN Volume 1, Number 7 (17) pp that the parameters o Weibull inluence directly the wind power aailable lie oer the duration o production o electrical energy. In the site, the total annual wind energy is 164.Wh with one duration o aailability o 1h per day. In the site o, the wind energy aailable is KWh with one duration o aailability o 19h per day. In the case o, it is 51KWh with one duration o aailability o 16h per day. The analysis o the results o comparison o total annual wind energy generated by the BWC XL.1 wind machine or the selected sites indicates that the maximum energy obtained rom this type o wind machine is or, region in the southern Algeria with high wind speed compared with and Béchar. The analysis shows that there are good prospects or wind energy utilization in the selected Algerian Sahara site. The southwest area located in the west o longitude and between 5 N and N latitudes is the windiest part o southern Algeria with an aerage win speed exceeding 6 m/s or and 5 m/s or at a height o 1 m. In the case o selected Algerian Sahara sites, it is ortunate that the windy season coincides with the high temperature seasons (45-55 ) which causes an increased demand or electricity could be coered by exploitation o wind energy. Thereore, accurate wind predictability and its correlation with electricity load demand may allow or a high penetration o wind energy and could mae it an economically attractie supplement to diesel-uelled power station. It is recommended to undertae urther studies to explore other locations in the Sahara o Algeria and to deelop this renewable energy resource. REFERENCES [1] S.Dia; M. Belhamel; M.Haddad.; A.Louche (7), Assesment o Wind Energy Ressource in Southern Algeria, Re.Energ. Ren. Vol. 1 (),, pp. 1- [] K.Ulgen, A.Hepbasli (); Determination o Weibull parameters or Wind Energy analysis o Ismir, Turey. Int J Energy Res. Vol.6 n.6,, pp [] S. Mathew; K. P. Pandey., and A.Kumar (), Analysis o Wind Regimes or Energy Estimation, Renewable Energy, ol.5 n.,,pp [4] I.Y.F. Lun; JC. Lam (), A Study o Weibull Parametre using Long term Wind Obserations. Renew Energy, ol. n.,, pp [5] JV. Seguro, TW.Lambert (,), Modern Estimation o the Parameters o the Weibull wind speed Distribution or Wind Power Energy Analysis.J Wind Energy Ind Aerodyn, ol.85 n. 1, pp [6] M. Dahbi; A.Benatiallah ; T. Benslimane (8,), Analyse du Potentiel Eolien dans Le Site de : Caractérisation des Paramètres de Weibull, The First International Worshop on Renewable Energies and their Applications (1WIERA),Laghouat, Algeria, May 1-1, pp [7] R. Hammouche,( 1991) Wind Atlas o Algeria, Meteorological National Oice, Uniersity Publications Oice. Algiers, Algeria,. [8] M. Dahbi, A. Benatiallah, M. Sellam, (1 ) The Analysis o Wind Power Potential in Sahara Site o Algeria-an Estimation Using the Weibull Density Function, Energy Procedia, ol 6,, pp [9] L Gary Johnson (1) Wind Energy Systems, Manhatan KS. Noember, pp. -8. [1] C. G Justus, Wind and Wind System Perormance, Franlin Institute Press; Philaelphia;1978. [11] S. Essalaimeh, A. Al-Salaymeh, Y. Abdullat (1), Electrical production or domestic and industrial applications using hybrid PV-wind system,, Energy Conersion and Management, ol.65,, pp [1] D. Weisser (), A Wind Energyr Analysis o Grenada: An Estimation Using the Weibull Density Function, Renew Energy,,ol. 8,, pp [1] S.Persaud ; D.Flynn, B..Fox (1999), Potential or Wind Generation on the Guyana Coastlands, Renew Energy, ol.18 n.,, pp [14] L Lin.; Y. Hongxing,B.John (), Inestigation on Wind Power Potentiale on Hong Kong Island-an Analysis o Wind Power and Wind Turbine Characteristics, Renew Energy, ol.7,, pp.1-1. [15] FMA.Ghali, MM. Abd el Aziz.; Syam FA(1997), Simulation and analysis o Hybrid system Using Probabilistic techniques. In; Power Conersion Conerence; Nagaoa,, pp [16] ES.Gaanidou.; AG. Bairtzis(1999), Design o a Stand Alone System with Renewable Energy Sources Using trade o methods. IEEE, Trans. Energy Conersion,ol. 7 n.1,, pp [17] www. SoDa.com, Serices or Proessionals in Solar Energy and Radiation. 14