Wind Energy Density Research Articles

Assessment of combined wind and wave energy in the tropical cyclone affected region:An application in China seas

Marine renewable energy resources are important for clean energy development. Research on the combined assessment of wind and wave resources, especially in tropical cyclone (TC) affected area is still rare. This study is to assess the potential combined wind and wave energy in the coastal waters of China, where TCs frequently occurred. The study utilizes the blended wind field with a parametric TC model based on the ECMWF reanalysis wind data from 1979 to 2013 for assessing potential wind energy, and the waves generated by the same wind data using the FVCOM-SWAVE model for assessing wave energy. The combined wind and wave energy density and annual power generation are analyzed. The potential energy from wind and waves at 15 nearshore locations along China east coasts are estimated. The results show that the frequency and intensity of TCs have a considerable impact on the distribution of density and stability of wind and wave energy, especially in the southeastern coastal areas of China. Suggestions of site selection of co-located wind and wave farm in the coastal waters of China are given. The research outcome provides a useful guidance for the selection of potential sites and design of wind and wave energy converters along the China coasts.

Statistical-analytical study on world development trend in offshore wind energy production capacity focusing on Great Britain with the aim of MCDA based offshore wind farm siting

Present study is a statistical-analytical analysis about the offshore wind energy plants development. As a multi objective or multi step study, in the first step the last 20 year development trend of top 10 pioneering countries in offshore wind energy production capacity studied to classify the countries based on their activity level in development path. Based on results the Great Britain (GB) can be nominated as the most active country from the offshore wind energy production capacity development point of view. But in order to access a real rank of countries based on offshore wind energy per capita, a more reliable index defined with dividing the offshore wind energy production capacity by population of countries. Based on introduced index the condition of GB with per capita of 123.5 Watt/person is not good enough compared to countries like Denmark, Belgium, Sweden and Netherlands with lower production capacity but higher per capita of 293.6, 194.4, 184.7 and 145.9 Watt/person respectively. Considering the island type and geographical position of GB and also having the highest development rate of offshore wind energy production capacity between top 10 countries in last 20 years, as the second step an analytical study conducted to find the best geographical coordinates for new offshore wind energy plant installation and enhancing production capacity. Blending multi criteria decision analysis (MCDA) with GIS software that is called special multi criteria decision analysis (SMCDA) is the method that is applied for offshore wind farm siting. Wind energy density, wind speed, water depth and distance from shore are the four main selected criteria for offshore wind farm siting. Next to for main criteria, the locations of installed or under construction offshore wind farms and also efficiency of offshore wind farms in various months and seasons are the other criteria for selecting suitable siting. In addition to above mentioned criteria, the suitability analysis for offshore wind farm siting applied in four different altitudes and also in six various areas around the GB. Based on results the northern (area#1), north western (some parts of area#6), north eastern (some parts of area#2) and some parts of western waters (area#5) are the best areas for installing offshore wind farms based on suitability map results in all four altitudes.

Technical Assessment of Wind Energy Potentials in Bangladesh

Wind power has experienced very rapid growth over the past two decades as major technological advances have been made to reduce the cost of producing electricity through wind. It is also renowned for its low maintenance and negligible effect on environmental pollution. The main purpose of this study is to evaluate and compare the wind energy potential in seven major districts of Bangladesh including Barisal, Chittagong, Dhaka, Khulna, Rajshahi, Rangpur, and Sylhet. Data had been recorded on daily basis for the consecutive five years from 2015 until 2019 and analyzed using the Weibull distribution function for various essential parameters such as wind speed, wind power density and Weibull parameters. Results show that the monthly average wind speed varies between 0.5 m/s to 2.10 m/s for all the divisions except Chittagong which is in the range between 3 m/s and 4.5 m/s. Similarly, the maximum wind power density and wind energy density were also found in the Chittagong division with annual densities that range between 51.86967 W/ to 84.01142 W/and 454.3783 KWh/ to 753.94 KWh/, respectively. The shape and scale parameters (k and c) are varying between 0.774373 – 1.086069 and 0.684588 – 1.735511 m/s, respectively for all the divisions except Chittagong where it ranges between 1.463098 – 1.625881 and 3.131256 – 4.28601 m/s, respectively. Meanwhile, the prevailing wind directions vary from one division to another but mainly between the south and east. This, this study strongly recommends the Chittagong division for the utilization of the potentiality of wind energy typically for small-scale applications.

Wind resource assessment considering the influence of humidity

The current study presents a wind resource assessment (WRA) approach by combining existing approaches, including wind probability density estimation based on hourly wind speed frequency, wind power density (WPD) and wind energy density (WED), wind turbine (WT) power output and power curve modeling, and annual energy production (AEP). Wind probability density investigation employed various probability density functions (PDF), including parametric probability density functions such as Weibull, Normal, and Gamma, and non-parametric distribution, including Kernel Density Estimator (KDE). The present study also models the influence of humidity on air density for estimating WPD, WT power output, and AEP. The current study validated the proposed approach by conducting case studies for selected sites of remote Indonesian archipelago islands. AEP estimation proposed by this study can assist the site-turbine fitting design, especially for relatively moist locations.

Wind and Solar Resources Assessment Techniques for Wind-Solar Map Development in Jeddah, Saudi Arabia

Recent decades show a massive demand increment toward clean sources of energy as the world is experiencing industrial and technological revolutions. Among the various clean energy resources, wind and solar can be utilized effectively. This study aims to study wind and solar energy potentials in Jeddah, Saudi Arabia while identifying seasonal variations of wind and solar energies in the city. The essentiality of the study relies on the added benefits to the country where this research can help in finding other alternatives of energy other than fossil fuel. The Weibull distribution function and the Angstrom techniques were respectively used for the wind and solar resources assessments. The meteorological data involved are for ten years (2010-2019) including wind speed and direction, direct and diffused solar radiations. The results show that the prevailing wind direction at 10 m and 80 m altitudes were north and north-northwest, respectively. Meanwhile, the mean wind speed at 80 m altitude is found to be 4.36 m/s and 3.72 m/s at 10 m altitudes. The highest wind power and wind energy densities were at 80 m altitude with the value of 192.19 W/m2 and 247.29 kWh/m2, respectively. In terms of solar resources, the site has an average potentiality of global solar radiation of 23.13 MJm2. The highest average possible sunshine duration occurred mostly in February, June, and November with respective values between 12.00 and 12.034 hours for most of the years. Lastly, the highest Angstrom’s ratio occurred during June 2016 scoring 0.7942 while the lowest on the other hand was in December 2015, scoring 0.4253.

Production and Development of Wind Energy in Wasit and Al-Mothennah Governorates

Renewable or alternative energy is a criterion for international progress in investing its natural resources, especially wind speed. Since the uses of wind are witnessing a wide spread, it has become necessary to work on calculating the rate of wind energy density because it is a criterion that determines the extent to which wind turbines are used or installed. The researcher depends on a comparison between two areas with different classification; where Al-Mothennah governorate enjoys a large quantity of winds, while Wasit governorate is experiencing lower rates than its counterpart in Al-Semawah station.

Wind Energy Assessment as a Source of Power Generation in Bangladesh

Wind energy has been considered one of the most popular forms of renewable energy. It has been widely considered for the generation of electricity for its low maintenance cost and negligible effect on environmental pollution. The purpose of this research is to evaluate and compare the wind energy potential in seven different districts of Bangladesh including Barisal, Chittagong, Dhaka, Khulna, Rajshahi, Rangpur, and Sylhet. Data had been recorded on daily basis for the consecutive five years from 2015 until 2019 and analysed using Weibull distribution function various essential parameters such as wind speed, wind energy density and wind power density. Results show that the monthly average wind speed varies between 0.5 m/s to 2.10 m/s for all the divisions except Chittagong where it is in the range between 3 m/s and 4.5 m/s. Similarly, the maximum wind power density and wind energy density were also found in the Chittagong division with annual densities that range between 51.86967 W/ to 84.01142 W/ and 454.3783 KWh/ to 753.94 KWh/ , respectively. The shape and scale parameters (k and c) are varying between 0.774373 – 1.086069 and 0.684588 – 1.735511 m/s, respectively for all the divisions except Chittagong where it ranges between 1.463098 – 1.625881 and 3.131256 – 4.28601 m/s, respectively. Meanwhile, the prevailing wind directions vary from one division to another but mainly between south and east. This, this study strongly recommends the Chittagong division for the utilization of the potentiality of wind energy.

Characteristics of Wind Resources and Post-Project Evaluation of Wind Farms in Coastal Areas of Zhejiang

As the onshore wind farm technology matures, offshore wind energy has attracted increasing attention. Zhejiang has coastal areas with massive potential for wind resources because of its geographical location. Therefore, understanding the wind resources in these areas can lay a foundation for future development and utilization. On this basis, this study used the measured wind field data of a wind farm along the coast of Zhejiang from March 2014 to February 2015 and from March 2016 to February 2018 to investigate and compare the characteristics of wind energy resources, including average wind speed, Weibull shape and scale factors, wind direction variation, and wind energy density. Then, the capacity coefficient of a wind turbine predicted using the wind farm data was compared with the actual capacity coefficients of two wind turbines in the wind farm in 2019. Results revealed the following observations: The overall variations in the evaluation indicators followed clear patterns over the 3 years. For example, the main wind direction in the same season was the same, and the variations in the monthly average wind speed, the monthly wind power density, and the theoretical capacity factors were highly similar. The time-series data indicated that the difference in the indicators between summer and autumn was significantly larger than that between other seasons, with the maximum difference in monthly average wind speed of 1.46 times and the maximum difference in monthly wind power density of 1.5 times. The comparison results of the capacity coefficient showed that the theoretical and actual capacity coefficients were extremely close when the monthly average wind speed was less than 6 m/s, with the average difference being less than 9%. When the monthly average wind speed was greater than 6 m/s, the proximity between the theoretical and actual capacity coefficients was reduced, with an average difference of more than 9% and a maximum value of 28%. In general, the overall characteristics of wind resources in coastal areas of Zhejiang exhibited similar trends but fluctuated considerably in some months. Wind energy forecasts had significant discrepancies from the actual operation indicators of the wind farm when the wind speed was high.

Analysis on the characteristics of wind speed and wind energy resources from 1961 to 2020 and the impact of urban underlying surface change on them in Shenyang

The long-term variation trend of wind speed, monthly variation characteristics and grade frequency of wind energy density and the impact of underlying surface on wind speed in the process of urbanization are analyzed by using the observational wind speed data from 1971 to 2020 in Shenyang and WRF models simulation. The results show that the wind speed has shown a linear decreasing trend year by year at the rate of 0.018 m s−1 every year since 1961 in Shenyang and The decreasing trend of wind speed has slowed down significantly since 2010. The wind speed and wind energy density show obvious monthly variation characteristics with three peaks in Shenyang. The peak value appears in April, with the monthly average wind speed of 3.76 m s−1 and the monthly average wind energy density of 58.3 W m−2. The southwest wind is the dominant wind direction in Shenyang all year round, and the occurrence frequencies of southwest wind and south–south​ west wind are 12% and 10% respectively, which account for about one quarter of the annual wind direction frequency. Due to the different types of underlying surfaces in numerical simulation, the intensity of 10 m wind speed in most areas of Liaoning Province is slightly weakened, and the average wind speed is reduced by 0.15 m s−1 in Shenyang. So the development of urbanization is one of the reasons for the decrease of wind speed and wind energy resources in recent years.

Integrated monitoring and assessments of marine energy for a small uninhabited island

Marine renewable energy (wind energy, wave energy, and tidal current energy) has important application potential for the construction and development of uninhabited islands, however, it is necessary to assess the richness and stability of resources before energy development. In this study, a marine renewable energy integrated monitoring system was deployed on a small island, Dongluo Island, in the northwestern South China Sea. Based on the observation data over one year, the energy density and availability are systematically assessed. The results show that the renewable energy resources in the sea area around the island have a certain utilization potential, in which the average wind energy density is 81 W/m2 and the available frequency is 44.6%, the average wave energy density is 1.74 kW/m and the available frequency is 29.2%, and the average tidal current energy density is 32.4 W/m2 and the available frequency is 18.4%. All three types of energy propagation directions are relatively uniform. In addition, because the seasonal variations of the intensity and stability of the three types of energy are different, the three energy resources show obvious complementary advantages. Although the available frequency of single energy is relatively low, the available frequency will be significantly improved by comprehensively superimposing the three resources. Therefore, for the energy development of the island, it is necessary to integrate and optimize the allocation of different types of marine energy resources.

Analysis and Assessment of Wind Energy Potential of Socotra Archipelago in Yemen

The increasing use of fossil fuels has a significant impact on the environment and ecosystem, which increases the rate of pollution. Given the high potential of renewable energy sources in Yemen and the absence of similar studies in the region, this study aims to examine the potential of wind energy in Socotra Island. This was done by analyzing and evaluating wind properties, determining available energy density, calculating wind energy extracted at different altitudes, and then computing the capacity factor for a number of wind turbines and determining the best. The average wind speed in Socotra Island was obtained from the Civil Aviation and Meteorology Authority data, only for the five-year data currently available. The results showed high wind speeds from June to September (9.85–14.88 m/s) while the wind speed decreased for the rest of the year. The average wind speed in the five years was 7.95 m/s. The average annual wind speed, wind energy density, and annual energy density were calculated at different altitudes (10, 30, and 50 m). According to the International Wind Energy Rating criteria, the region of Socotra Island falls under Category 7 and is classified as ‘Superb’ for most of the year. This study provides useful information for developing wind energy and an efficient wind approach.

THE POTENTIAL OF OFFSHORE WIND ENERGY IN THE EAST COAST OF PENINSULAR MALAYSIA, TERENGGANU

A detailed understanding of wind characteristics is very important for offshore wind energy development. A 26 years of wind speed data (1993-2018) were retrieved using Radar Altimeter Database System (RADS) to assess the potentiality of offshore wind energy in Terengganu waters. Seasonal assessment and wind energy density derivation was carried out to choose the potential location for wind energy development. This study highlights the multi-criteria site suitability analysis using Analytical Hierarchy Process (AHP) and is supported by the geographical information system (GIS) by developing a suitability map. The site suitability analysis considered a few criteria, such as seasonal assessment, physical, environmental, and wind resources. Theoretically, the Terengganu area possessed strong wind during the Northeast monsoon with an average of 3.46m/s and experienced up to 6 m/s during this monsoon. For offshore areas, which is more than 50km from the coastline, Terengganu waters experienced a maximum of wind speed more than 5m/s and the average wind power density varied from 40W/m2 to 60W/m2. While Tenggol Island possessed a maximum wind speed between 3m/s to 5m/s and produce up to 40W/m2 of average wind energy density. From the suitability analysis, a few areas are identified as the potential location with an optimum resource of wind energy. Even though, Malaysia is located at low wind area, this research will help organisation or governments to plan suitable technology and policy for harvesting wind energy.

The Application of Small-Scale and Large-Scale Wind Turbines in Kerman, Iran; A Case Study

Wind data collected of the three synoptic sites for the period of Jul 2006 to Jun 2008 at the height of 40 m has been used to study the wind characteristics, monthly and annual wind energy potential for three agricultural districts in Kerman ( 30°15/N, 56°58/E ), Iran. Two statistical methods (Meteorological and Weibull) have been applied to determine the wind characteristics. Wind energy density, mean wind speeds and wind speed directions have been investigated. A technical assessment has been done and the electricity generation from five different wind turbines having capacity of (26 kW, 100 kW, 300 kW, 600 kW and 660 kW) has been calculated. The results show that all the locations studied are not suitable for electric wind application in a large-scale.

Performance Comparison of New Generation Parameter Estimation Methods for Weibull Distribution to Compute Wind Energy Density

To install a wind energy conversion system to a region, the wind speed characteristics of that region must be identified. The two-parameter Weibull distribution is highly efficient in modeling wind speed characteristics. In this study, the wind speed data of 32 cities in three different regions of Turkey have been comparatively analysed to estimate Weibull distribution function parameters by the use of three well-known methods (Graphical Method (GM), Maximum Likelihood Method (MLM), Justus Moment Method (JMM)) and three new parameter estimation methods (Energy Pattern Factor Method (EPFM), Wind Energy Intensification Method (WEIM), Power Density Method (PD)) which have been proposed in recent years. Three years of hourly wind speed data of the specified regions have been used. The performance metrics of these analyses have been compared using Wind Energy Error (WEE), Root Mean Square Error (RMSE), and Coefficient of Determination (R2). The results have shown that while the PD method has high model performance, the JMM is closely competitive with the MLM. Besides, the wind energy densities that were estimated by using actual data have been compared with the resulting Weibull distribution. It has been clear that the method that has the closest estimation to the actual values is the PD method.

Rüzgar Hızı Değerlendirmesinde İki Parametreli Weibull Dağılımı İçin Üç Parametre Tahmin Metodunun Karşılaştırmalı Performans Analizi

The two-parameter Weibull distribution is widely used in the estimation of wind speed. In this paper, some recently proposed parameter estimation methods for the two parameter Weibull distribution have been compared using the wind data from two cities in Turkey. The compared methods in this paper are Wind Energy Intensification Method (WEIM), Energy Pattern Factor Method (EPFM), and Power Density Method (PD). These methods have been compared by checking the fit have provided in the probability-density graph. The comparison has also been made by comparing of efficiencies these methods in predicting wind energy density. Lastly, a comparison has been investigated by using the following performance criteria; Wind Energy Error (WEE), Root Mean Square Error (RMSE), Coefficient of Determination (R2), and the results of error analysis have been compared. According to simulation results, while the EPFM and PD methods have shown a very close fit on the graph; when it comes to calculating wind energy densities, the PD method has shown a significant advantage over other methods. Finally, after the examination of error criteria, it was clear that EPFM has shown accurate performance which is the desired result. The main conclusion is that the accurate method for these selected regions is the EPFM.

Technical Assessment of Wind Energy Potentiality in Malaysia Using Weibull Distribution Function

In this paper, an assessment of the wind characteristics and wind power potentials in three different stations (Chuping, Kuantan and Melaka) in Malaysia has been analyzed at 80 m height. The assessment technique was based on the two-parameter Weibull distribution function over three recent consecutive years (2018-2020) while aiming to establish the potentiality of the wind as a source of power generation in these sites. The results demonstrate that the monthly highest mean wind speeds were 4.42 m/s, 2.96 m/s and 2.17 m/s at Melaka, Kuantan and Chuping, respectively. The highest most probable wind speed was 4.70 m/s and the wind speed carrying maximum energy was 1.74 m/ both speeds occurred at Maleka in 2019. The yearly highest Weibull shape parameter was 1.69 and the scale parameter was 2.96 m/s. Among the three stations, Melaka has shown the highest wind power potentials with an average value of 26.10 W/m2 followed by Kuantan with 12.71 W/m2 and Chuping with 6.80 W/m2 wind power density. The corresponding wind energy densities were 595.58 kWh/m2/year, 111.37 kWh/m2/year and 228.65 kWh/m2/year for Chuping, Kuantan and Melaka station, respectively. The prevailing wind directions are northeast at both Kuantan and Melaka station, west and southwest direction at Chuping station. It is therefore concluded that the potentiality of the wind power of the sites covered in the present study is only feasible for small-scale power generations.

Statistical analysis of wind resource and energy potential assessment of Sanghar site, Sindh Pakistan

PurposeThe purpose of this paper is to assess the wind resource and energy potential of the Sanghar site for minimizing the dependence on fossil fuels and improving the environment.Design/methodology/approachThe Sanghar site wind shear coefficient and turbulence intensity factor are investigated for a period of a year. The two-parameter k and c Weibull distribution function is used to analyze the wind speed of the Sanghar site. The standard deviation, coefficient of variation, wind power density and energy density; and capacity factor was assessed for a period of a year. The economic assessment of energy/kWh is investigated for the selection of appropriate wind turbines.FindingsThe mean wind shear of the Sanghar site was found to be 0.2509. The mean wind speed was found to be 4.766, 5.534 and 6.121 at 20, 40 and 60 m above the ground level. The mean value of the k parameter was observed to be 2.433, 2.777 and 2.862 at 20, 40 and 60 m for a period of a year. The Weibull c m/s parameter was found to be 5.377, 6.245 and 6.906 m/s at 20, 40 and 60 m. The major portion of values of standard deviation was found to be in between 0.1 to 2.00 at 20, 40 and 60 m. The mean wind power density values were observed to be 88.33, 93.5 and 110.16 W/m2 at 20, 40 and 60 m; respectively, for a period of a year. The mean coefficient of variation was found to be 0.1478, 0.1205 and 0.1033 at 20, 40 and 60 m; respectively. The mean energy density was found to be 476.75, 683.08 and 866.33 kWh/m2 at 20, 40 and 60 m; respectively. The mean capacity factor for different wind turbines was ranged between 18 to 24.83 for a period of a year. The economic assessment showed that wind turbine B has the minimum cost (US$) 0.0484/kWh.Practical implicationsThe assessment provides the solution to sustainable energy generation which reduces the consumption of fuel and the effect of fluctuating price of fuel in the world market on local consumers.Social implicationsWind energy may have social implications including environmentally friendly, consistent supply of energy during the peak summer season, less unit per cost, etc.Originality/valueThe Sanghar site is new and assessed for the first time in this research work. The Sanghar site is suitable for installing utility wind turbines for energy generation at the lowest cost.

Assessing climate change impacts on wind characteristics in Greece through high resolution regional climate modelling

This work introduces an assessment of the projected climatic changes in wind characteristics in Greece through the WRF model 5 × 5 km2, forced by the EC-EARTH Global Climate Model (GCM). Firstly, the model is validated against historic observations at 10 m, before being applied to the Representative Concentration Pathways (RCPs) 4.5 and 8.5 that represent an average expected future and a worst-case scenario. Projected changes in the mean annual wind speed at 100 m, between the historic (1980–2004) and future (2020–2044) scenarios are found to vary locally between −5% and +20%, whereas for the Wind Energy Density (WED) this variation lies between −15% and +60%. Overall, robust and significant increases regarding the mean wind speeds were found mainly over the north and central-western Aegean region, the Island of Crete, as well over Greek mainland and the Ionian Sea. Both scenarios predicted higher statistically significant increases in the Weibull shape parameter values (of about 0.2) in the north–central Aegean, while the summer seasonal analysis, yielded significant decreases over the western Ionian Sea and south and south-western parts of Crete, which might be indicative of more gusty events. Finally, extreme wind speeds analysis indicated increases, which might affect wind turbines structural integrity.

Statistical analysis of wind resource and energy potential assessment of Quaidabad site, Sindh Pakistan

Purpose Pakistan is an energy starving country that needs continuous supply of energy to keep up its economic speed. The aim of this paper is to assess the wind resource and energy potential of Quaidabad site for minimizing the dependence on fuels and improving the environment. Design/methodology/approach The Quaidabad site wind shear coefficient and turbulence intensity factor are investigated. The two-parameter k and c Weibull distribution function is used to analyze the wind speed of site. The standard deviation of the site is also assessed for a period of a year. The wind power density and energy density are assessed for a period of a year. The economic assessment of energy/kWh is investigated for selection of appropriate wind turbine. Findings The mean wind shear coefficient was observed to be 0.2719, 0.2191 and 0.1698 at 20, 40 and 60 m, respectively, for a period of a year. The mean wind speed is found to be 2.961, 3.563, 3.907 and 4.099 m/s at 20, 40, 60 and 80 m, respectively. The mean values of k parameters were observed to be 1.563, 2.092, 2.434 and 2.576 at 20, 40, 60 and 80 m, respectively, for a period of a year. The mean values of c m/s parameter were found to be 3.341, 4.020, 4.408 and 4.625 m/s at 20, 40, 60 and 80 m, respectively, for a period of a year. The major portion of values of standard deviation was found to be in between 0.1 and 2.00 at 20, 40, 60 and 80 m. The wind power density (W/m2) sum total values were observed to be 351, 597, 792 and 923 W/m2 at 20, 40, 60 and 80 m, respectively, for a period of a year. The mean coefficient of variation was found to be 0.161, 0.130, 0.115 and 0.105 at 20, 40, 60 and 80 m, respectively. The sum total energy density was observed to be 1,157, 2,156, 2,970 and 3,778 kWh/m2 at 20, 40, 60 and 80 m, respectively. The economic assessment is showing that wind turbine E has the minimum cost US$0.049/kWh. Originality/value The Quaidabad site is suitable for installing the utility wind turbines for energy generation at the lowest cost.

Influence of wind energy utilization potential in urban suburbs: a case study of Hohhot

Given the increasing trend of using wind energy in cities, the utilization of distributed wind energy in cities has been widely concerned by researchers. The related research on the micro-site selection of wind turbines, a sub-project of the Task27 project of the International energy agency, was continued in this paper. The wind speed data of an observation station near Hohhot, Inner Mongolia, with a range of 10–19 m were collected. The evaluation included wind direction, Weibull parameter characteristics, and turbulence intensity. The potential energy output in 10 different heights was estimated using commercial horizontal and vertical axis wind turbines of the same power. Results showed that the following: the three-parameter Weibull distribution model can well describe the statistical properties of the wind speed in this site. The wind speed distribution model constructed from extrapolation parameters reflects the wind speed statistical properties out of detection positions to a certain extent. The wind energy density of the vertical axis wind turbine is slightly lower than that of the horizontal axis wind turbine. Furthermore, more power can be generated from March to May.