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Analysis of Wind Data and Assessing Wind Energy Potentiality for Selected Locations in Egypt A

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Analysis of Wind Data and Assessing Wind Energy Potentiality for Selected Locations in Egypt A International Journal of Scientific & Engineering Research, Volume 6, Issue 3, March-2015 604 ISSN 2229-5518 Analysis of wind data and assessing wind energy potentiality for selected locations in Egypt A. Y. Hatata, M. G. Mousa, Rana M. Elmahdy Abstract— The wind energy resource is available in large regions at Egypt. This paper investigates the wind energy potential at different locations at Egypt. The wind data for these regions was collected at 10m height for period of ten years. These data are used to find out the wind energy potential with help of 2-parameter Weibull distribution. The wind speed distribution is modeled by using Weibull distribution. Weibull parameters, shape and scale parameters are calculated using two different methods which are method of moments (MOM) and maximum likelihood method (MLM). The annual energy and the annual capacity factor of three different manufacturers wind turbines are calculated for the selected regions in Egypt. The highest annual mean wind speeds at 10 m height were 9 and 8.2 m/s at Gebel El Zeit and Ras Ghareb respectively. The maximum wind power density was found to be 445 W/m2 and 344 W/m2 at Gebel El Zeit and Ras Ghareb respectively. From this study, it is concluded that, Gebel El Zeit and Ras Ghareb are the most suitable for large-scale wind energy generation. Index Terms— Wind Speed, Wind Power density, Weibull Distribution, Shape and Scale Factors. —————————— —————————— 1 INTRODUCTION Egypt occupies a geographical zone between 22 and 32oN share reaches 20% of the total generated energy by 2020 as latitude and 25 and 36oE longitude. Although the area of the 12% wind, 6% Hydro and 2% solar [2]. country of Egypt is about 1milion km2, only 3.5% of it can be said to be permanently settled, while the remainder being Modeling and prediction of wind speed are essential pre- desert. Electricity production in Egypt depends heavily on requisites in the sitting and sizing of wind power applications. imported oil and natural gas for its energy requirements. Fos- In recent years, many efforts have been made to develop sil fuels are one of the non-renewable energy sources that models through which the wind distribution can be found in nature in limited quantities. Egypt faces a serious estimated. The extent to which wind can be exploited as a challenge of energy crisis. Instead fossil fuels are preferred source of energy depends on the probability density of occur- that are not only expensive but also lesser in this country. rence of different speeds at the site. To optimize the design of These fossils may become extinct within 2-3 decades if used a wind energy conversion device, data on speed range continuously for this purpose [1], especially with the rapidly over which the device must operate to maximize energy growing demand for electricity in Egypt. It was estimated that extraction is required, which requires the knowledge of the demand is increasing at a rate of 1,500 to 2,000 MW a year, as a frequency distribution of the wind speed. Among the proba- result of rapid urbanizationIJSER and economic growth. At the bility density functions that have been proposed for wind same time Fossil fuels involves many pollutants and particu- speed frequency distributions of most locations [4]. There are a lates such as nitrogen oxides, sulfur dioxide, volatile organic lot of researchers estimated the potential of wind energy in compounds and heavy metals that are the main cause of air different locations based on the Weibull and the Rayleigh pollution. models [5, 6]. Many studies have reached to the Weibull dis- In order to have a sustainable development, the govern- tribution is the most popular methods that gives a good result ment has to take measures to utilize the renewable energy with experimentation data for wind energy estimation [5, 7]. in order to satisfy part of the energy demand in Egypt. This distribution is characterized by parameters the shape pa- It has richness in sources of renewable energy from the wind rameter K and scale parameter c, There are several methods ( and the sun, where the highest rates of wind speed and the Graphical method (GM); Method of moments; Standard devia- highest average solar radiation is available. The average level tion method; Maximum likelihood method; Power density of solar radiation of between 2,000 to 3,200kWh per square method; Modified maximum likelihood method; Equivalent meter a year and wind speed can be reached to 10 m/s in energy method to calculate these parameters as reported by [6, some area. So the efforts of the state are heading towards the 8]. exploitation of solar and wind energy. According to Egyptian Various wind resource assessment studies have been Renewable Energy Strategy of 2013, the renewable energy conducted around the world to determine the potentialities of local sites for wind power/electricity [9-19]. The case of ———————————————— Egypt is not left out and the researches are available. • Prof. M. G. Mousa is currently working as Professor in Mechanical power Some attempts have been made to analyze the potential in Dept., Faculty of engineering, Mansoura Univ., Egypt. Egypt [20-24] and some experimental work [25,26] has • Dr. A. Y. Hatata is currently working as Lecturer in Electric Engineering Dept. Faculty of engineering, Mansoura Univ., Egypt, E-mail: been conducted. Each one of these reports considered differ- [email protected]. ent sites and presented analyses to justify their results. • Eng. Rana M. Elmahdy is currently pursuing master’s degree program in In this paper, the Waybill distribution method is used to Technology and Environmental Management Engineering. Faculty of eng., determine the average mean speed and the shape and scale Mansoura Univ., Egypt. parameters can be estimated by using the Maximum Likeli- IJSER © 2015 http://www.ijser.org International Journal of Scientific & Engineering Research, Volume 6, Issue 3, March-2015 605 ISSN 2229-5518 hood Method (MLM) and Method of moments (MOM) as 2.2 Maximum Likelihood Method (MLM) there are the most efficient methods and calculated of ex- pected output power at different locations in Egypt to set up The MLM was the most widely used method for estimating power plants using wind energy. The methodology of wind the parameters of the weilbull distribution. The weilbull shape energy potential presented in this paper takes into considera- parameter k is estimated using MLM method as expressed in tion wind speed and transmission to grid. It predicts the wind Eq. 8. turbine energy generated to summarize the energy generation. ( ) ( ) = 푁 푘 푁 −1 (8) Theses algorithms are implemented into Matlab program. The ∑푖=1 푙푛 푣푖 푣푖 ∑푖=1 푙푛 푣푖 푘푁 methodology is applied to a case study for evaluating wind Once 푘the value� ∑푖=1 of푣 푖the −Wiebull푁 shape� parameter k is obtained, energy potential in Egypt. the Wiebull scale parameter c is estimated using the Eq. 9. 1 = (9) 푘푁 푘 2 WIND SPEED ANALYSIS MODEL ∑푖=1 푣푖 푁 It is important to drive the probability distribution of the 푐 � � site’s wind speed to evaluate the wind energy at this site. The 3 TRANSMISSION GRID AND LOSSES Weibull density function is used to describe the wind speed Transmission of power from wind farms to utility lines is frequency. It was the common wind speed distributions when generally very costly. New transmission lines can cost over $1 both a mean and standard deviation of wind speed are known. million per mile, and high capacity lines in urban areas can cost The cumulative probability density function of the Weibull dis- over $1 billion per mile [29]. Thus, locating wind turbines close tribution is given by [17, 27]: to existing high voltage transmission lines can dramatically im- prove project economics. An equally important issue arises ( ) = 1 (1) 푣 푘 when transmission lines are near full capacity and unable to Where f(v) is the Weibull cumulative distribution function 푓 푣 − 푒푒푒 �− �푐� � accept additional power generation. Maps identifying high and represents the probability for the wind speed to be lower voltage transmission lines can be obtained from local public than a certain value, v is the wind speed (m/s), k is the shape utility commissions. In Egypt, high voltage transmission line parameter and c is the scale parameter (m/s) determined from maps are published by the Egyptian electricity holding compa- the wind speed data. The scale parameter c indicates how ny. windy a wind location is while the shape parameter k, indicates Power loss over distance is a common challenge in any how peaked the wind distribution is. transmission infrastructure. In AC transmission, 4 to 6% line The mean value of the wind speed, vm, and standard loss per 1000km, though achieving that level of power loss deviation σ, for the Weibull distribution is defined in terms of would be expensive. As transmission distances increase from the Weibull parameters, k and c as: 500km to 1000km to 2000km and higher, this loss will add up = 1 + (2) more and more. Losing 2% of transmitted power, while certain- 1 ly a loss, is acceptable for most utilities. 푣푚 푐푐 � 푘� IJSER = 1 + 1 + (3) 2 1 2 2 4 WIND POWER DENSITY Where휎 Γ ( �) is푐 the�푐 �gamma푘� −function�푐 � of푘� (.).� � The most probable and maximum energy carrying wind The average specific power available depends on the air den- speeds can be evaluated from Eq. 4 and 5: sity and the cube of the wind speed. It can be estimated by us- ing Eq. 10: = 1 (4) = 2 푘 W/m (10) 푘−1 1 3 2 푚푝 Where Pw is the power density given in W/m , ρ is air 푣 푐 � 푘 � 푒푤 2 휌푣 = 1 (5) density and usually taken as 1.225 kg/m3 which depends on 푘+2 푘 퐸푚푎푥 altitude, air pressure and temperature and v is the wind speed Where푣 vmp is the푐 � most푘 � probable wind speed and vEmax is the (m/s).
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