Evaluation Of Wind Energy Potential Research Articles

Wind energy potential evaluation. case of study: Constantine, an Algerian Province

Wind energy potential evaluation. case of study: Constantine, an Algerian Province

Climatic Trend of Wind Energy Resource in the Antarctic

Wind energy resource is an important support for the sustainable development of Antarctica. The evaluation of wind energy potential determines the feasibility and economy of wind power generation in Antarctica, among which mastering the variation rule of wind energy resource is the key to realizing the effective utilization of polar wind energy. Based on the 6-h ERA-5 reanalysis data of ECMWF from January 1981 to December 2020, this paper systematically analyzed the long-term variation trend of Antarctic wind energy resource by using the climate statistical analysis method and the least square fitting, with the comprehensive consideration of a series of key indicators such as Wind Power Density, Effective Wind Speed Occurrence, Energy Level Occurrence, and Stability. The results show that it indicates a positive trend for wind power density (0.5~2 W × m−2 × a−1), effective wind speed occurrence (2~3%/a), energy level occurrence (0.1~0.2%/a), and coefficient of variation (−0.005/a) in the South Pole—Kunlun station and the central region of Queen Maud land. The westerly belt exhibits a decreasing index (−0.5%/a) in terms of stability trend, indicating a positive potential. Kemp Land, the Ross Island—Balleny Islands waters show shortages in all indicators. The wind power density in the Antarctic region is stronger in spring and summer than in autumn and winter, with the weakest in autumn. Based on the above indicators, the variation trend in the East Antarctic coast, Wilhelm II Land—Wilkes Land, the South Pole—Kunlun station, and the westerlies is generally superior.

Comparison of Wind Speed Probability Distribution Models for Accurate Evaluation of Wind Energy Potential: A Case Study from Kerala, India

Comparison of Wind Speed Probability Distribution Models for Accurate Evaluation of Wind Energy Potential: A Case Study from Kerala, India

Evaluation of Wind Energy Potential in Omu Aran, Nigeria Using Weibull and Rayleigh Models

The depletion of resources and emission of hazardous gases have been identified with conventional sources of energy. The negative influence of conventional sources of energy on the environment necessitates the call for the use of renewable and sustainable energy sources, such as wind. Wind power is one of the available renewable energy sources in Nigeria with huge potential that can be tapped in order to contribute to its energy mix. Wind energy utilization in Nigeria is poor because the available data in all six geopolitical political regions for system design have not been fully analysed and implemented. Wind energy projects are liable to failure if proper analysis is not done. Therefore, before any location could be considered suitable or unsuitable for wind power generation, the power density must be determined using the standard approach. This study, therefore evaluated the wind energy potential of Omu Aran, Nigeria using Weibull and Rayleigh models. Five years data collected from the metrological station of the Landmark University on Lat. 8.14 oN; Long. 5.10 oE were processed and analysed in Matlab computer software using a code developed for two statistical modelling methods (Weibull and Rayleigh). The actual mean yearly wind speed of 3.964 m/s for Kwara falls in the low wind speed. Although, the power density for hours of the day, months, and seasonal variation ranged from 24 to 141 W/m2. More than 50% of the power density for daily hours was less than 100 W/m2 which indicated that Omu Aran, Nigeria belongs to class 1. The coefficient of efficiency (COE) for Weibull probability distribution ranged from 39.95 to 94.9 while the coefficient of determination (COD) R2 ranged from 0.66 to 0.98. This range of performance values for the Weibull model, when compared to the Rayleigh model, were within the acceptable limits for prediction accuracy, hence the Weibull probability distribution function can be used for the preliminary design of wind power plants for Kwara State, Nigeria. Therefore, it would help the relevant stakeholders in wind power project investment to make the appropriate decision.

Comprehensive analysis of offshore wind farm and evaluation of wind energy potential: a case study of the University of Southampton

The aim of this paper is to provide 40% of electricity consumption of Highfield Campus at the University of Southampton. The wind data is observed during the year of 2019 at three different heights, 10 m, 25 m and 45 m and obtained wind velocities are found as 6.34 m/s, 7.1 m/s and 7.48 m/s, respectively. According to the collected data, the best location for the wind turbine is proposed to be on the coast of the Isle of Wight. The system is designed with an installed capacity of 3.45 MW wind turbine. Based on the hub height and rotor diameter results run in MATLAB environment, two different solutions of turbine were given. Providing energy requirement of the campus with wind energy, there will be a decrease of approximately 20,000 tCO2 emissions per year. The diameter of the rotor and the hub height are calculated approximately 126 m and 158 m, respectively.

Comprehensive Analysis of Offshore Wind Farm and Evaluation of Wind Energy Potential: a case study of University of Southampton

Comprehensive Analysis of Offshore Wind Farm and Evaluation of Wind Energy Potential: a case study of University of Southampton

Evaluation of Wind Energy Potential in View of the Wind Speed Parameters – A Case Study for the Southern Jordan

Evaluation of Wind Energy Potential in View of the Wind Speed Parameters – A Case Study for the Southern Jordan

Evaluation of wind energy potential at four provinces in Morocco using two-parameter Weibull distribution function

In the last years, the use of wind turbines for power generation has increase due to the advance's technology used and the stable cost. In this paper, due to the low investment in the desert regions of Fezouata, Ouijjane, El Ouatia, and Taroudannt in Morocco, we have considered wind resources as an ideal option. Using meteorological statistics, Weibull's distribution function was able to estimate the wind power and potential of four various wind turbines for each site with various nominal powers, ranging from 250 kW to 2000 kW, for use in wind farms. 24 years of wind speed data to fit the Weibull distribution. For the four provinces examined, the annual mean value of wind speed and frequency distributions were collected. The desert province of El Ouatia shows that it is economically feasible to install a wind farm for the production of green energy.

A Comparative Study of Wind Characteristics Between South-Western and South-Eastern Thailand Using Different Wind Turbine Models

Globally, wind energy has proven to be one of the most sustainable sources of energy. Wind energy assessment plays a critical role on determining installation of wind turbines worldwide. This work presents the technical evaluation of wind energy potential using three available wind turbine models for prospective onshore wind farm in the southern Thailand at Krabi and Songkhla sites. Ten-minute interval wind data over a period of 3 to 4 years obtained from Weather Observing Station is utilized to observe the diurnal and monthly wind speed, as well as frequency distribution. WAsP program is applied for energy yield calculations and wind resource maps. Our results reveal that Krabi and Songkhla has the highest mean wind speed of 4.39 m/s in December and 3.91 m/s in February, respectively. The prevailing wind direction in Krabi and Songkhla are north-east and south-east, respectively. WAsP analyses show that the total net AEP for Krabi is 7163.782 MWh, 7762 MWh and 12731 MWh using 275 kW, 300 kW and 500 kW wind turbine models, respectively. Similarly, the total net AEP for Songkhla is 7116.63 MWh, 7775.245 MWh and 12390 MWh using 275 kW, 300 kW and 500 kW wind turbine models, respectively. The total capacity factor for Songkhla and Krabi is 29.1% and 28.3%, respectively. Our results indicate that Enercon E-40/5.40 500 kW wind turbine model produces the highest total gross AEP and total net AEP for Krabi and Songkhla sites. Besides, the Vergnet GEV MP-C 275 kW turbine model shows slightly higher capacity factor in case of both sites. The findings of this study reflect that small to medium size wind turbines can be utilized to generate electricity at the sites.

Evaluation of wind energy potential for different regions in Lebanon based on NASA wind speed database

The grid-connected system can be an attractive solution to reduce electricity consumption, dependence on utility power, and increase electricity generation from renewable energy resources like wind energy for residential electricity users. Based on 33-year wind data (1983-2020), this study investigates the potential of wind energy at different locations ((Akkar, Baalbek, Beirut, Zahlé, Baabda, Nabatieh, Tripoli, and Sidon) in Lebanon using the Weibull distribution function. Monthly NASA wind speed data during the period (1983-2020) were used to estimate the wind energy potential. The result showed that the averaged wind speeds at the selected regions are varied from 3.695m/s to 4.457m/s at the height of 10m. Furthermore, the annual wind power density was estimated at various heights (10m, 30m, and 50m). The results demonstrated that small-scale wind turbines are recommended to be used for generating electricity from wind in the selected regions. Finally, the performance of WRE.060 / 6 kW (vertical axis wind turbine) and Proven WT 6000 (horizontal axis wind turbine) was done based on the monthly NASA wind speed database.

Contribution of Cartography to the Optimization of the Evaluation of Wind Energy Potential in the Republic of Cameroon: Case of Bitchoua Highlands

This study deals with a model combining cartography with mathematical simulation for the optimal evaluation of wind potential in the context of the absence of networks of in-situ observation stations. It is based on both geographic Information Systems (GIS), climate data from NASA Surface Meteorology and Solar Energy (SSE) from 1985 to 2018, and field survey data from 2018.The NASA-SSE data, made it possible to obtain information on the direction of the winds, to determine parameters of distribution of wind speed frequencies (by the Weibull method).Then, we proceeded to the processing and numerical simulation of the data to provide predictions of the electrical energy that could be generated. By mobilizing GIS, the study proposes a decisional mapping allowing the planning and realization of wind energy projects in the studied area. It appears from the work carried out in the field that with an average wind speed of 2.56m / s (at 50 m from the ground) the winds of Bitchoua have an average power density estimated at 1612.64 W. Under current operating conditions defined by the Betz limit, it would be possible to recover from the local wind, thanks to a 50 m diameter wind turbine, an electrical power of approximately 956.87 W / s, for a maximum average of 974.17 W / s. The spatial representation of this potential presents the Center and North-East of Bitchoua as the most suitable sectors for the installation of wind turbines in the locality. Indeed, with an average wind speed of 2.8m / s, the area has an average wind power density evaluated at 13.45 W, for an available power of 4221.53 W. Under current conditions of exploitability, the recoverable potential in this part would be about 1251.79 W / s, for 1275.07W / s on average maximum (well above the local average).

Evaluation of Wind Energy Potential in Rayong Province, Thailand by WAsP Program

Over the past decades, Wind energy is one of the alternative energy or renewable sources, which has been harvested to produce electricity. Our research aims to study the wind potential of the areas in the Rayong provinces of Thailand. Data from meteorological stations were collected every 10 minutes for of 3 years (2017-2019), with a measuring tower at 10-meter height above ground level (AGL). The annual average wind speeds were investigated in Rayong (2.02 m/s) with Weibull Probability Distribution Function (PDF). The annual average power density in Rayong regions was 13 W/m2. In all locations, wind direction was detected mainly from Southwest (SSW) and the yearly maximum wind power capacity is 94.376 MWh. The capacity factor of 21.5 % was noticed. With relatively low wind speed was noticed in Rayong provinces of Thailand, a small wind turbine installed at 30 meters would be recommended as a cost-effective way to convert wind power to electricity.

Towards a sustainable 2022 FIFA World Cup in Qatar: Evaluation of wind energy potential for three football stadiums

This study analyzes the feasibility of satisfying the demand of three Football Stadiums for the 2022 FIFA World Cup in Qatar, using the wind’s kinetic energy. For all three selected locations (Lusail, Al Rayyan, and Al Wakrah), the wind potentiality is calculated through an environmental parameters study, from which the wind power density is obtained. Furthermore, a commercial wind turbine with proper characteristics is selected, and the same case study for each location is presented, to quantify the capacity that wind energy offers for satisfying the maximum energy demand of each associated stadium. In addition, the environmental benefits and the time required by each wind farm to satisfy the energy demand are computed. The results reveal that the conditions enable the use of wind energy for this purpose, based on a 5.06 m/s, 4.63 m/s, and 5.18 m/s velocity mean for Lusail, Al Rayyan, and Al Wakrah, respectively; from which values of 187.49 W/m2, 150.96 W/m2, and 187.29 W/m2 of wind power density are obtained. Also, the proposed wind farms could produce 69,952.56 MWh/year, 59,550.19 MWh/year, and 75,333.70 MWh/year, respectively. Moreover, the wind farms should produce energy for a period of 5.64 h, 4.41 h, and 5.23 h, to satisfy the maximum demand by a football match in its associated location. Additionally, to avoid the implementation of a storage system, the electricity obtained from the wind is connected to the power grid, decreasing the quota of fossil fuel power plants. In consequence, Qatar will eliminate the emissions of approximately 23.376 tons of CO2 in total per trio of matches held in these stadiums. Finally, a post 2022 FIFA World Cup scenario is analyzed, obtaining a positive outcome from both environmental and economic perspectives, in which an average of 14,675 tons of CO2 and 6.03 Million US$ can be saved annually.

Evaluation of wind energy potential: a case study

ABSTRACT In this study, the wind energy potential of the Kırklareli University Kayalı Campus at a height of 100 meters has been evaluated by using statistical distribution methods. The parameters of the distributions were calculated by Moment and Maximum Likelihood (MLE) methods. As a result of the goodness of fit tests, the Rayleigh MLE method was estimated the most suitable model among the statistical distributions examined. According to the annual mean results estimated by applying the Rayleigh MLE method; the scale parameter, the wind speed, the standard deviation, and the power density were found as 7.15 m/s, 6.34 m/s, 3.31 m/s and 322 , respectively. The annual dominant wind direction was determined as the Northeast, (NE) with 1407 hours of blowing. It is suggested that the most suitable turbine for the location is the GE103 model, estimated to generate 7.270 GWh of electrical energy annually.

Geospatial Evaluation of Wind Energy Potential in the South-East and South-South Sections of Nigeria

Investment into a renewable energy project spurs the need to investigate sites with potential for a renewable energy source. Such a crucial investigation is the main motivation for this study, which uses a geospatial technology to evaluate wind energy potential within the south-east and south-south regions of Nigeria. A multi-criteria decision analysis (MCDA) model was implemented using Landsat TM images at bands 2, 3 & 4, and integrated with NASA global wind speed data, airport location map and forest reserve map of the area. The criteria for generation of wind energy potential map were: wind speed ≥ 3m/s, 2000m buffer from built-up areas, 2,500m buffer from airports and outside the forest reserve. The results indicate the presence of a reasonable amount of potential for wind energy which lies mostly in the southernmost part of the study area. The total potential area is about 104,700 hectares in land size, which is merely 1.2% of the total study area, although River state encloses most of the potential locations. When compared to global vortex wind data, by visual inspection, these potential areas show a great deal of sensitivity to wind speed, highlighting its critical importance in the present modelling. Wind farms can be located in this area, although it is a rather small scale investment in a renewable energy resource considering that the consumable amount of energy in the study area is in a steady increase. Stake holders and experts in energy economy will find that the need to protect this potential energy location from indiscriminate urban development and other anthropogenic activities is compelling.

Assessment of wind energy potential across varying topographical features of Tamil Nadu, India

Wind energy is one of the abundant, cheap and fast-growing renewable energy sources whose intensive extraction potential is still in immature stage in India. This study aims at the determination and evaluation of wind energy potential of three cities located at different elevations in the state of Tamil Nadu, India. The historical records of wind speed, direction, temperature and pressure were collected for three South Indian cities, namely Chennai, Erode and Coimbatore over a period of 38 years (1980-2017). The mean wind power density was observed to be highest at Chennai (129 W/m2) and lowest at Erode (76 W/m2) and the corresponding mean energy content was highest for Chennai (1129 kWh/m2/year) and lowest at Erode (666 kWh/m2/year). Considering the events of high energy-carrying winds at Chennai, Erode and Coimbatore, maximum wind power density were estimated to be 185 W/m2, 190 W/m2 and 234 W/m2, respectively. The annual average net energy yield and annual average net capacity factor were selected as the representative parameters for expressing strategic wind energy potential at geographically distinct locations having significant variation in wind speed distribution. Based on the analysis, Chennai is found to be the most suitable site for wind energy production followed by Coimbatore and Erode.

THE SPATIO-TEMPORAL VARIATIONS OF WIND SPEED DURING HARMATTAN SEASON IN NORTHEASTERN NIGERIA

Wind speed is the principal climatic element that drives the Marmaton season in West African sub region. It drives the season by conveying huge amount of dust across the Northeastern Nigeria. The presence of dust in the atmosphere brought by the Northeast trade winds during the Harmattan season plays a vital role in absorbing and scattering solar radiation. The study examines the spatial and temporal variations of wind speed in Northeastern Nigeria during the Harmattan season with the sole aim of ascertaining its variability, patterns and trends from1984 to 2014. Descriptive and statistics such as mean, standard deviation, coefficient of variation, and time series analysis with ArcGIS 10.3 was used in examine the temporal and spatial variations of wind speed from 1984–2014 in six synoptic stations of Northeastern Nigeria. The findings show that wind speed varied both temporally and spatially in the last three decades. The pattern of variations in the six synoptic stations shows rising trends within the study years. It was also found that latitude playing a crucial role in determining the speed of the wind in the study area and as the speed of the wind increases with increasing latitude.
 Keywords: Wind speed, Harmattan, Season, Northeast, Variation and ITD.
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Weibull Probability Distribution of Wind Speed for Gaza Strip for 10 Years

The need of clean and renewable energy, as well as the power shortage in Gaza strip with few wind energy studies conducted in Palestine, provide the importance of this paper. Probability density function is commonly used to represent wind speed frequency distributions for the evaluation of wind energy potential in a specific area. This study shows the analysis of the climatology of the wind profile over the State of Palestine; the selections of the suitable probability density function decrease the wind power estimation error percentage. A selection of probability density function is used to model average daily wind speed data recorded at for 10 years in Gaza strip. Weibull probability distribution function has been estimated for Gaza based on average wind speed for 10 years. This assessment is done by analyzing wind data using Weibull probability function to find out the characteristics of wind energy conversion. The wind speed data measured from January 1996 to December 2005 in Gaza is used as a sample of actual data to this study. The main aim is to use the Weibull representative wind data for Gaza strip to show how statistical model for Gaza Strip over ten years. Weibull parameters determine by author depend on the pervious study using seven numerical methods, Weibull shape factor parameter is 1.7848, scale factor parameter is 4.3642 ms-1, average wind speed for Gaza strip based on 10 years actual data is 2.95 ms-1 per a day so the behavior of wind velocity based on probability density function show that we can produce energy in Gaza strip.

Evaluation of wind energy potential and trends in Morocco

In recent years, the use of wind energy has become increasingly attractive for the successful and economic development. Wind energy is one of the fastest-growing renewable energy technologies of electricity generation. Wind energy has proved its potential in combating environmental degradation while ensuring a renewable, efficient and clean energy source. Good wind sites can even be competitive with traditional energy sources. In this paper, we used statistical methods namely Weibull probability density function for evaluating the wind energy potential as a power source in Morocco's regions, in particular Taza and Dakhla cities. Various methods were explored as wind variability, power density, standard deviation, Moroccan and WAsP methods for calculating the Weibull parameters using mean wind speed data measured at one-hour intervals. The wind data have been extracted at the height of 50 m and over a three-year period 2015–2017. Furthermore, the variations of monthly and annual wind speed are studied and the power and energy densities are evaluated. The monthly values of the Weibull shape parameter are on average 5.01 m/s at Taza and 9.04 m/s at Dakhla. The results obtained showed that the highest values of wind potential occur during March, July, September and December in Dakhla and during the December to March in Taza.

Evaluation of wind energy potential and estimation of wind turbine characteristics for two different sites

In this study, a novel approach is discussed to study wind speed characteristics and wind turbine (WT) characteristics. This paper focuses on the study of estimation of wind resource potential and WT characteristics at higher hub height. A detailed wind resource assessment analysis and selection of WT are discussed for estimating capacity factor and harnessing maximum wind power at MANIT and Mamatkheda. The selection procedures of the efficient WT of (class II) for the site, according to IEC 61400, are thoroughly investigated. It is observed from the investigation that generalised gamma distribution produces accurate results to estimate annual energy production (AEP). This study also reveals that MANIT has a very low wind potential at a height of 80 m; therefore, it is not a suitable location for a class IV WT, whereas Mamatkheda has a high wind potential which results in a significant increase in AEP.