Wind Atlas Analysis Research Articles

Improving the wind map using interpolation approach: Case study of a southeastern region of Algeria

Various software programs like Wind Atlas Analysis and Application Program (WAsP) and WindSim use only a single data source, limiting the information generated to a small area, while it is more interesting to look for the contribution that can be added to the local speed generated at a certain distance. To improve accuracy of the prediction, refining wind maps with data from neighboring masts and using new interpolation methods is proposed in this paper. Thus, to make corrections to the local speed generated at a certain distance, we propose to refine the wind maps produced by numerical simulations of WAsP software, taking into account the data from neighboring masts and optimizing the results by new interpolation methods. This technique is applied to a region of southeastern Algeria, where the wind data were collected from three meteorological stations, namely of Biskra, Guemar, Sidi Mahdi, and three neighboring stations of Tunisia namely Gafsa, Kebili and Nefta. The results shown that depending on the characteristics and the surrounding environment of the measuring mast, the simulated wind speed can vary between 5% and 25%.

Assessing offshore wind plants for energy and green hydrogen production: A case study in the Mostaganem coastal region, Algeria

This study assesses the feasibility and strategic implications of establishing a 500 MW offshore wind farm utilizing fixed wind turbine technology along Algeria’s western coastal economic zone, with a focus on the Mostaganem region. The study recommends integrating 33 Vestas V-235 wind turbines, each boasting a 15 MW capacity to harness offshore wind resources for electricity and green hydrogen production. Utilizing the Wind Atlas Analysis and Application Program (WAsP), offshore wind potential is assessed based on meteorological data from a land-based station, overcoming the lack of in situ sea level measurements. Results show that the proposed wind farm could yield 1361.63 GWh/year of electricity at a cost of 0.89 $/kWh. Additionally, it would produce 28,571 tons of hydrogen at a cost of 2.12 $/kg. This initiative is anticipated to significantly reduce CO2 emissions, by approximately 595,450 tons/year, highlighting the effectiveness of offshore wind resources in promoting sustainable energy production and advancing green hydrogen as a viable energy carrier in this region.

Assessment Wind Energy in the Central Region of Thailand

This study evaluates the wind energy potential in the central region of Thailand by using data from seven wind measurement stations (Ayutthaya, Bangna, Chainat, Kamphaeng Saen, Lopburi, Nakhon Sawan, and Pathum Thani) and two wind turbines, namely AN Bonus 1300/62 and Vestas Wind System A/S. The analysis was conducted using the Wind Atlas Analysis and Application Program (WAsP) to examine the collected wind speed data over three years from the seven stations. The objective was to identify the top three areas with the highest annual energy production (AEP). Additionally, the study included an economic analysis using various metrics, such as the present value of costs (PVC), benefit-cost ratio (BCR), payback period (PBP), and levelized cost of electricity (LCOE). The results indicate that the AN Bonus 1300/62 model provides higher values in areas with high wind speeds and relatively high electricity demand, whereas the Vestas V52 model is suitable for areas with low wind speeds and lower investment requirements. Based on these findings, the authors recommend prioritizing wind energy development in the provinces of Ayutthaya, Nakhon Sawan, and Lopburi using the AN Bonus 1300/62 model, as these areas have high wind speeds and relatively high electricity demand. Overall, this research provides valuable insights for policymakers and investors, enabling them to make informed decisions regarding renewable energy investments in Thailand.

Repowering feasibility of Indian wind energy sector: A case study

Repowering wind farms entails upgrading or replacing old turbines with more efficient, capable, and profitable ones. This technique has the potential to boost energy production, improve grid integration, and lower operational costs. Repowering also makes use of the most recent breakthroughs in wind energy technology, ensuring that wind farms stay economically viable and contribute to the growth of renewable energy. The majority of the wind farms that are located in India were constructed in early 2000, and their capacity ratings range from 200 kW to 800 kW. The lifespans of these wind farms have finally come to an end. Repowering wind farms is a viable alternative in these regions due to the significant wind capacity that exists there. In order to find the wind potential in the site wind resource assessment is needed. This paper proposes a repowering scheme for the existing wind farm located in Kayathar, Tamil Nadu. The reduction in power loss due to the wake effect in the existing wind farm is analyzed using WAsP software and repowering scheme is proposed to increase the Annual Energy Production (AEP), Capacity Utilisation Factor (CUF). The Wind Atlas Analysis and Application Program (WAsP) is utilized in order to carry out the site’s wind resource evaluation. After the wind resource assessment, individual turbine wake loss is identified, and the viability of repowering the wind farm by raising the hub height of high wake-affected turbines was investigated. Another repowering study is also carried out by installing high-capacity turbines in place of the existing turbines.

Mesoscale modelling for wind resource evaluation purposes. A test case in complex terrain

The aim of this work was the preliminary wind resource assessment of a complex terrain site, located in Bulgaria, using a virtual wind data series, taken from mesoscale modelling Weather Research and Forecasting system (WRF). The meso-micro scale coupling was carried out applying the virtual wind data series to the point where once a local wind measurement was conducted. This way, the comparison between the two data sets, virtual and local measurement, could be done. Using the mesoscale virtual information the characterization of the wind was done for the place of study. The microscale model Wind Atlas Analysis and Application Program (WASP) was used to make the wind resource mapping and the calculation of the estimated wind resource and annual production of energy, taking into account the defined configuration for the wind farm and the turbine model chosen. The obtained differences, in terms of the magnitude of the estimated resource and its own dominant orientation indicates that the application of mesoscale models in very complex topography terrains should be done with extreme care.

Modelling the wind potential energy for metallurgical sector in Albania

The metallurgical industry, in the context of the global energy crisis and the new European green deal, needs urgent investments on energy and resource efficiency. The metallurgical sector, which includes the production of different metals is an energy-intensive industry that requires large amounts of energy for various processes such as smelting, refining, and casting. One of the largest consumptions of energy in Albania comes from the metallurgical sector during the production of iron, steel, chromium and aluminum which corresponds respectively to three private companies called “Kurum International Ltd”, “AlbChorme Ltd” and “Everest Ltd”. During the last three years, these companies have temporary interrupted the production process due to the higher electricity price that come from imports. Based on it, our research work presents the energy efficiency analysis in the Albanian metallurgical sector by focusing on the implementation of wind energy in the above mentioned private metallurgical companies, because adding new generation capacity from Renewable Energy Sources in a context of industrial energy communities, will contribute to improve the security of supply for this industry. The Wind Balkan Atlas, New European Wind Atlas, and Wind Atlas Analysis and Application Program (WAsP) has been used to select the appropriate areas and to develop the wind potential distribution maps, as well as to select the most suitable type of wind turbine based on capacity factors. Two areas were selected close to the metallurgical sectors in the regions of “Vajkal” in Bulqizë and “Selitë e Malit” in Tirana. It has been installed the power of 9 MW for each wind farm, with a capacity factor of 40% and 36.6% respectively, and with a total annual energy production of about 60 GWh/year, these wind farms will cover about 26% of the total annual consumption of companies. Clean Energy Management Software (RETScreen Expert) was used for the detailed economic analysis and environmental impact of proposed wind farms. The economic sensitivity analysis of the proposed wind farms showed that even for the highest installation cost value of 1350 €/kW, for discount rates 5, 7, and 11%, the LCoE values are within the statistically established range for wind farms in Europe.

Site suitability analysis of wind energy resources in different regions of Algeria’s southwestern highland

This paper presents a site suitability analysis for a 20 MW wind farm project in western Algeria’s highlands. The aim is to improve the quality of the electricity grid’s service and increase Algeria’s renewable energy utilization. The wind potential of three regions, Mecheria, El Kheiter, and Naâma, was evaluated using the Weibull function and the wind atlas analysis and application program (WAsP) with a ten-year database (2011-2021) at 10 m hub height. The assessment encompassed a comprehensive analysis of various wind resource parameters, including mean wind speed, prevailing direction, and power densities. In comparison to other sites, the Mecheria region has the best wind potential, with a mean annual wind speed of 6.31 m/s, a power density of 283 W/m2, and Weibull parameters A = 7.1 m/s and k = 2.02. These promising results prompted us to design a wind farm in this region using Power Wind 90/2000 kW turbine technology facing the predominant wind directions of the site, producing 103.91 GWh of total annual gross energy produced (gross AEP) and 103.75 GWh of total annual net energy produced (net AEP). Finally, it appears that the wind resources in the selected region are well-suited for electricity generation, offering a promising opportunity to reduce the country's dependence on fossil fuels.

An optimum design and economic feasibility analysis of wind farms in Kuwait using different wind generation technologies

Kuwait plans to produce 15 % of its electricity from renewable resources by 2030. This paper aims at designing a 300-MW wind farm in six different sites in Kuwait. The study uses the measured wind data at Kuwait International Airport to predict the wind profile (speed and power density) at the selected sites. To validate the work, two different types of wind generation technologies are used in the design. The first type is Full-Converter Wind Turbine Generators (FCWTGs), and the second type is Doubly Fed Induction Generators (DFIGs). The designed wind farms are simulated using the Wind Atlas Analysis and Application Program (WAsP®) to estimate the Annual Energy Production (AEP) for each type of wind farms in each selected site. The location of every wind turbine in each wind farm (both types) for every selected site is accurately determined while considering needed spacing between rows and columns of turbines. The wake effect for downstream wind turbines is considered and estimated in the design. A comparison between the different wind farms in the six sites using the DIFGs and the FCWTGs generators is carried out. The economic feasibility of the designed wind farms is studied using the estimated Annual Energy Production (AEP) in each one of the designed wind farms.

Wind resource assessment of northern part of Thailand

With the unpleasant occurrences of climate change and global warming, there is an inevitable need to generate energy from renewable sources. Energy generation from burning coal, extracting fuel, ignition of CO 2 , exploiting tar sands, or any other environmentally unfriendly resources are hazardous to our planet. Therefore, the world needs to switch towards renewable sources. Wind energy has developed across the globe due to being the most eco-friendly, comparatively efficient, and affordable. Thailand has a higher potential for wind energy because of the median height of 287 m above sea level with a soaring altitude of 2565 m above sea level. In addition to this, Thailand has a higher energy wind potential are of 550 km 2 . Regarding this, Thailand has realized wind energy is a strong potential renewable energy resource that needs to be developed. To fulfill energy demands, the prospect of particular provinces concerning wind power and the capacity of electrical energy acquired from wind energy has been studied. Consequently, with the data derived from the specific regions, consisting of 13 different stations at 10 m height and 10 min interval, the wind energy potential has been evaluated for each region in the WASP (Wind Atlas Analysis and Application Program). In addition, 7 stations data was processable among 13 stations. In this program, the wind data acquired from the study area consists of Chiang Rai, Lamphun, Mae Hong Son, Mae Sa Riang, Pha Yao, Theon, and Thung Chang with the latitude and longitude through meteorological stations and entered as an input to the WASP. WAsP simulation software was used to analyze the data generated, which is considered to be among the best simulation applications worldwide. As a result, the potential areas for electricity generation are identified. This study supports the generation of renewable energy in particular northern regions of Thailand and accordingly the purpose is to provide guidelines and contributions to the researchers and related organizations to further dig into which can substitute the conventional methods and economically provide energy.

Using Observed and Modelled Heat Fluxes for Improved Extrapolation of Wind Distributions

Modelling the horizontal and vertical variation of wind speed is crucial for wind energy applications. A model frequently used for this purpose is part of the Wind Atlas Analysis and Application program (WAsP). Here, we modify the model in WAsP to account for local atmospheric stability parameters. Atmospheric stability effects are treated by using the impact of a temperature scale on the geostrophic drag law and the diabatic logarithmic wind profile. Using this approach, wind-direction dependent mean and standard deviation of a surface-layer temperature scale and a mean boundary-layer height scale can be obtained from either numerical weather prediction model output or observations to improve vertical extrapolations of Weibull wind speed distribution parameters. The modified atmospheric stability model is validated at six flat sites in northwestern Europe. The surface-layer temperature scale is available from sonic anemometer measurements at three of the sites. At all sites the temperature scale is also estimated from reanalysis data and from mesoscale model output. The modified model improves the aggregated estimations of power density distributions when extrapolating to nearby locations from 5.2 to 3%, when using the temperature scale derived from either observations or mesoscale/reanalysis output compared to the current model.

Study on Atmospheric Stability and Wake Attenuation Constant of Large Offshore Wind Farm in Yellow Sea

Power generation estimation is one of the key steps in wind farm micro-sitting, and its accuracy is related to the wake decay constant in the wake model. Considering the influence of wind resource distribution in different regions, this study carried out interval optimization for the wake decay constant of offshore wind farms in the Yellow Sea region of China. Given the very small length of the sea surface roughness, atmospheric stability is a critical factor influencing the wake extent and recovery speed of offshore wind farms. WAsP 10 (Wind Atlas Analysis and Application software) simulates the wake of various scenarios, and the selection range of wake attenuation constant is investigated by combining the cases of two offshore wind farms in the Yellow Sea region. The study found that the higher the atmospheric stability, the larger the wake and the lower the wake attenuation coefficient. The Yellow Sea wind farm’s wake error system is between 0.03 and 0.04, and the forecast error can be controlled to within 3%. When simulating the wind farm at Yellow Sea offshore for improving power generation and economic evaluation, it is critical to select the correct value range of wake decay constant.

WIND ENERGY POTENTIAL AND WIND CHARACTERISTICS FOR THE DISTRICTS OF THE CENTRAL DEVELOPMENT REGION OF THE REPUBLIC OF MOLDOVA

The poor energy security worldwide and especially at the national level, requires all entities to look for effective solutions to rectify the current situation by turning to renewable energy sources and energy efficiency. The purpose of this paper is to study the wind energy potential and wind characteristics for second-level administrative-territorial entities (districts) from the Central Development Region, Republic of Moldova, which includes 13 districts: Anenii Noi, Călărași, Criuleni, Dubăsari, Hâncești, Ialoveni, Nisporeni, Orhei, Rezina, Străseni, Șoldănesti, Telenesti and Ungheni. The Wind Atlas Method accompanied by the special Wind Atlas Analysis and Application Program, data on wind speed and direction measured by the Technical University and the orographic map of the Republic of Moldova was used for the research. For each individual district there were: calculated and presented the maps of the average annual wind speed and wind power density at the height of 100 m above ground level; classified the district territory according to the power density value and also calculated the theoretical wind power possible to install. Following the calculations made for the thirteen analyzed districts, it was found that the average annual wind speed at the height of 100 m is between 6.70 and 7.40 m/s, and the wind power density -between 287 and 398 W/m2. The highest average annual speed equal to 7.40 m/s and windpower density equal to 398 W/m2 was identified in Nisporeni district and the lowest inIaloveni, Rezina, Șoldănești and Dubăsari districts.

Comparative evaluation of optimal Weibull parameters for wind power predictions using numerical and metaheuristic optimization methods for different Indian terrains.

The accurate selection of the wind speed distributions is crucial for a better utilisation of wind energy. The Weibull distribution is most commonly used distribution and hence its parameters need to be optimized. In this study five numerical methods, namely, maximum likelihood method (MLM), graphical method (GM), empirical method of Justus (EMJ), modified maximum likelihood method (MMLM) and wind atlas analysis and application program (WAsP) and three metaheuristic optimization algorithms, namely, social spider optimization (SSO), particle swarm optimization (PSO) and genetic algorithm (GA) are applied for estimating Weibull distribution parameters at three different locations (onshore-Kayathar, nearshore-Jafrabad and offshore-Gulf of Khambhat (GOK) in India and also comparison of numerical and optimization methods are employed to tune the optimal parameters. The accuracy of the methods was evaluated using three different statistical analysis techniques. As per the results, GOK has the maximum wind power density of 450.2W/m2 compared to Jafrabad and Kayathar. It was observed that among the five methods used for Weibull parameters estimation, WAsP method presented a better curve fit with the histogram of the wind speed. The results shows that SSO and PSO presents a comparably better performance than GA in the term of accuracy on the basis of closeness to converged solution.

A comparative analysis of wind characteristics for distinct terrains of India

The accurate wind potential assessment is the critical and inevitable process before wind farm planning. This paper aims to evaluate and compare the wind potential between the evolutionary algorithms and numerical methods using the wind data measurement data on flat, complex, coastal offshore, and offshore sites from the mast and remote sensing method. The maximum likelihood method, modified maximum likelihood method, and WAsP (wind atlas analysis and application program) are employed to estimate the optimum Weibull parameters. Furthermore, the Jaya algorithm is compared with particle swarm optimization and genetic algorithms to evaluate Weibull function for different topological terrains of India. The four-performance metrics, root mean square error, normalized root mean square error, normalized error, and root mean square difference are estimated to analyze the accuracy of various methods. Considering numerical methods, the WAsP method was found better than other numerical techniques. While the Jaya algorithm and particle swarm optimization were found to be efficient as compared to the genetic algorithm. The mean power density is maximum in the coastal area followed by offshore, complex terrain, and flat terrain with 687 W/m2, 485 W/m2, 301 W/m2, and 243 W/m2, respectively at 100 m height.

Wind Resource Assessment by Analyzation and Simulation in WAsP for Electricity Generation in Chiang Mai, Thailand

The purpose of this study is to assess and analyse the potential wind energy in Chiang Mai, the northern province of Thailand. The calculation in this paper is based on ten-minutes interval data at 10m height recorded for three years data from 2017 to 2019 at Thai meteorological station, Thailand. Weibull model is applied to evaluate the wind distribution by utilizing wind atlas analysis and application program (WAsP). Meanwhile, the average wind speed and the average power density was recorded at 1.48 m/s and 15 W/m2. The prominent wind direction is from the south west to north east. The two potential sites showed the maximum annual energy production 1401.419 MWh and 1913.410 MWh by using Bonus 300kW Mk III wind turbine with LCOE $382.64 / MWh and $274.63 / MWh respectively. This paper suggests the suitable sites for the electricity generation in Chiang Mai. Hence, it will not only reduce the stress on conventional methods but also create awareness regarding the potential of wind energy.

Wind Energy Data Analysis and Resource Mapping of Dangla, Gojjam, Ethiopia

Energy is one of the most important factors in socio-economic development. The rapid increase in energy demand and air pollution has increased the number of ways to generate energy in the power sector. Currently, wind energy capacity in Ethiopia is estimated at 10,000 MW. Of these, however, only eight percent of its capacity has been used in recent years. One of the reasons for the low use of wind energy is the lack of accurate wind atlases in the country. Therefore, the purpose of this study is to develop an accurate wind atlas and review the wind resources using Wind Atlas Analysis and Application Program in Dangla so that the best sites used for the installation of wind farms can be easily identified. Wind climatology data, vector maps, and wind turbine data were used to model the Wind Atlas Analysis and Application Program. The wind data collected from National Meteorology Survey Agency over three years were used for the analysis. Besides, vector data for the survey area was prepared using Global Mapper V20.1. In this study, the Wind Atlas Analysis and Application Program tool was used to estimate wind resources. The wind resource map was developed at an altitude of 80 m above ground level, and a horizontal axis type wind generator called (i.e., GridStreamer Vestas V100 1.8 MW) was selected from the Wind Atlas Analysis and Application Program catalog to mimic the wind farm. The results obtained from the analysis of actual wind data showed that the minimum wind speed was 0.12083 m/s while the maximum wind speed was 9.96389 m/s. At a height of 10 m a.g.l., the mean wind speed and wind power density were 1.8 m/s and 9 w/m2, respectively. The most common wind direction was also discovered to be 210 degrees. The maximum wind speed and capacity factor were available around hills, according to the wind resource map, and the net annual energy output of the Dangla wind farm at a turbine height of 80 m a.g.l. was found to be 282.726 GWh (or, 32.27 MW). The farm’s capacity factor was also discovered to be 9.54 percent, indicating that the site is rated as low potential.

Satellite-based estimation of roughness lengths and displacement heights for wind resource modelling

Abstract. Wind turbines in northern Europe are frequently placed in forests, which sets new wind resource modelling requirements. Accurate mapping of the land surface can be challenging at forested sites due to sudden transitions between patches with very different aerodynamic properties, e.g. tall trees, clearings, and lakes. Tree growth and deforestation can lead to temporal changes of the forest. Global or pan-European land cover data sets fail to resolve these forest properties, aerial lidar campaigns are costly and infrequent, and manual digitization is labour-intensive and subjective. Here, we investigate the potential of using satellite observations to characterize the land surface in connection with wind energy flow modelling using the Wind Atlas Analysis and Application Program (WAsP). Collocated maps of the land cover, tree height, and leaf area index (LAI) are generated based on observations from the Sentinel-1 and Sentinel-2 missions combined with the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2). Three different forest canopy models are applied to convert these maps to roughness lengths and displacement heights. We introduce new functionalities for WAsP, which can process detailed land cover maps containing both roughness lengths and displacement heights. Validation is carried out through cross-prediction analyses at eight well-instrumented sites in various landscapes where measurements at one mast are used to predict wind resources at another nearby mast. The use of novel satellite-based input maps in combination with a canopy model leads to lower cross-prediction errors of the wind power density (rms = 10.9 %–11.2 %) than using standard global or pan-European land cover data sets for land surface parameterization (rms = 14.2 %–19.7 %). Differences in the cross-predictions resulting from the three different canopy models are minor. The satellite-based maps show cross-prediction errors close to those obtained from aerial lidar scans and manually digitized maps. The results demonstrate the value of using detailed satellite-based land cover maps for micro-scale flow modelling.

Determination of feasible sites for wind farm using WAsP in Uttaradit, Thailand

Electricity production from the wind plays the potential role to reduce conventional way of electricity generation to reduce the negative impacts on the environment. In this study the data is collected from Uttaradit, the northern province of Thailand. The calculation in this study is based on ten-minutes interval data at 10 m observed during the year 2017-2019 by Thai meteorological department. Weibull distribution is applied to extract the monthly and yearly wind in the selected area by using wind atlas analysis and application program (WAsP). Moreover, in WAsP a stimulation was created to observe the comparison of potential of wind energy between three windiest sites located in the study area. The results generated show that the mean wind speed is 2.35m/s and the gradient wind direction from north and south are quite distinct. The annual energy production calculation of three sites in Uttaradit by WAsP estimates about 2125.815MWh, 3379.621MWh and 3369.235MWh respectively by using Bonus 300kW Mk III wind turbine. This paper suggests and supports the suitable sites and wind turbine for the electricity generation in Uttaradit. Hence, it will not only reduce the stress on conventional methods but also create awareness regarding the potential of wind energy.

Assessment of wind energy potential of Hat Yai (Songkhla), Thailand

Due to environmental problems associated with fossil fuels and rising need for energy, wind power renewable energy will play a vital role in transformation of future energy structure in Thailand. Exploitation of wind energy for sustainable development, wind resource assessment plays an important role in wind power utilization. This case study presents wind resource assessment using the wind atlas analysis and application program (WAsP), in order to assess the potential of wind energy in Hat Yai, Thailand. Ten-minutes interval wind data observed by the Thai Meteorological Department recorded during the period 2017-2019, have been used to harness adequate wind power density and wind energy potential. The annual mean wind speed is 3.5 m/s at 10 m height above the ground. The prevailing direction southwest, south and northeast of the wind rose are very pronounced. The WAsP analysis estimates about 2,731.28 MWh of the total net annual energy production for the specific sites using the Enercon E-18 (80 kW) wind turbine of 1.92 MW capacity. The findings of this study indicate the possibility of the small-scale wind farm project for electricity generation in future.

Wind energy resource assessment for Mukdahan, Thailand

ABSTRACT The generation of electricity from wind energy can reduce the fossil sources imported and carbon dioxide emissions. The wind is free, clean, and green energy. This study aims to present a wind energy assessment for Mukdahan site of Thailand. The wind speed at heights of 60, 90, and 120 m above ground level was measured from January 1st, 2012 to December 31st, 2017. The annual mean wind speeds were 3.59, 4.02, and 4.51 m/s at 60, 90, and 120 m AGL, respectively. The majority of wind directions were contributed by the monsoon for this region. The Wind Atlas Analysis and Application Program (WAsP) was used to predict the Annual Energy Production and Capacity Factor for five selected wind turbines in a capacity range of 0.85 − 3.30 MW. Moreover, the high-resolution wind resource map also indicated the high potential for wind around the site. The low cut-in speed and high hub-height wind turbines such as VestasV110-2.0 MW and V126-3.3 MW can produce higher energy output, capacity factor and better cost of energy, especially when the wind turbine site is located on the ridges and peaks of hills around the site. The best cost of energy was 0.030 USD/kWh, which was observed for the V110 wind turbine and the second best was 0.041 USD/kWh for the V126 wind turbine, especially when considering placement on the peak of a hill. The important data from this study can be developed for wind farm project installation and suitable wind turbine design for the whole local region.