scholarly journals Wind Farm Site Selection Using WAsP Tool for Application in the Tropical Region

2021 ◽  
Vol 13 (24) ◽  
pp. 13718
Author(s):  
Ismail Kamdar ◽  
Shahid Ali ◽  
Juntakan Taweekun ◽  
Hafiz Muhammad Ali
Keyword(s):  
Wind Energy ◽  
Wind Farm ◽  
Small Scale ◽  
Tropical Region ◽  
Suitability Analysis ◽  
Study Region ◽  
Tropical Regions ◽  
Wind Speeds ◽  
South Eastern ◽  
Cost Of Energy

Wind energy is one of the most promising renewable energy technologies worldwide; however, assessing potential sites for wind energy exploitation is a challenging task. This study presents a site suitability analysis to develop a small–scale wind farm in south–eastern Thailand. To this aim, the most recent available data from 2017 to 2019, recorded near the surface, at nine weather stations of the Thai Meteorological Department (TMD) were acquired. The analysis was conducted using standard wind–industry software WAsP. It was found that the mountain peaks and ridges are highly suitable for small–scale wind farm development. Nevertheless, the wind data analysis indicates that regions fall in low–to–moderate wind classes. The selected sites in south–eastern Thailand have mean wind speeds ranging from 5.1 m/s to 9.4 m/s. Moreover, annual energy production (AEP) of 102 MWh to 311 MWh could be generated using an Enercon E–18 wind turbine with a rated power of 80-kW at the hub height of 28.5 m. The Levelized Cost of Energy (LCOE) reveals that the development cost of a small–scale wind farm is lowest in the Songkhla and Yala provinces of Thailand, therefore these two locations from the investigated study region are financially most suitable. The findings could encourage researchers to further investigate low–speed wind energy mechanisms in tropical regions, and the demonstrated approach could be reused for other regions.

scholarly journals Inter-annual variability of wind climates and wind turbine annual energy production

2018 ◽  
Author(s):  
Sara C. Pryor ◽  
Tristan J. Shepherd ◽  
Rebecca J. Barthelmie
Keyword(s):  
Standard Deviation ◽  
Wind Energy ◽  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Speeds ◽  
Annual Variability ◽  
Eastern Usa

Abstract. Inter-annual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in pre-construction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derives in part from variability in wind climates. However, the magnitude of IAV in wind speeds at/close to wind turbine hub-heights is poorly constrained and maybe overestimated by the 6 % standard deviation of annual mean wind speeds that is widely applied within the wind energy industry. Thus there is a need for improved understanding of the long-term wind resource and the inter-annual variability therein in order to generate more robust predictions of the financial value of a wind energy project. Long-term simulations of wind speeds near typical wind turbine hub-heights over the eastern USA indicate median gross capacity factors (computed using 10-minute wind speeds close to wind turbine hub-heights and the power curve of the most common wind turbine deployed in the region) that are in good agreement with values derived from operational wind farms. The IAV of annual mean wind speeds at/near to typical wind turbine hub-heights in these simulations is lower than is implied by assuming a standard deviation of 6 %. Indeed, rather than in 9 in 10 years exhibiting AEP within 0.9 and 1.1 times the long-term mean AEP, results presented herein indicate that over 90 % of the area in the eastern USA that currently has operating wind turbines simulated AEP lies within 0.94 and 1.06 of the long-term average. Further, IAV of estimated AEP is not substantially larger than IAV in mean wind speeds. These results indicate it may be appropriate to reduce the IAV applied to pre-construction AEP estimates to account for variability in wind climates, which would decrease the cost of capital for wind farm developments.

Assessment of wind energy potential and characteristics in Qatar for clean electricity generation

2021 ◽  
pp. 0309524X2110438
Author(s):  
Carlos Méndez ◽  
Yusuf Bicer
Keyword(s):  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Rose ◽  
Energy Potential ◽  
Wind Power Density ◽  
Wind Speeds ◽  
Wind Energy Potential

The present study analyzes the wind energy potential of Qatar, by generating a wind atlas and a Wind Power Density map for the entire country based on ERA-5 data with over 41 years of measurements. Moreover, the wind speeds’ frequency and direction are analyzed using wind recurrence, Weibull, and wind rose plots. Furthermore, the best location to install a wind farm is selected. The results indicate that, at 100 m height, the mean wind speed fluctuates between 5.6054 and 6.5257 m/s. Similarly, the Wind Power Density results reflect values between 149.46 and 335.06 W/m2. Furthermore, a wind farm located in the selected location can generate about 59.7437, 90.4414, and 113.5075 GWh/y electricity by employing Gamesa G97/2000, GE Energy 2.75-120, and Senvion 3.4M140 wind turbines, respectively. Also, these wind farms can save approximately 22,110.80, 17,617.63, and 11,637.84 tons of CO2 emissions annually.

The equatorial wind structure in Jupiter’s stratosphere from direct wind and temperature measurements with ALMA and IRTF/TEXES

2021 ◽  
Author(s):  
Bilal Benmahi ◽  
Thibault Cavalié ◽  
Thomas K. Greathouse ◽  
Vincent Hue ◽  
Rohini Giles ◽  
...  
Keyword(s):  
Tropical Region ◽  
Temperature Structure ◽  
Horizontal Structure ◽  
Tropical Regions ◽  
Upper Troposphere ◽  
Thermal Wind ◽  
Wind Speeds ◽  
Wind Structure ◽  
First Time ◽  
Middle Stratosphere

<p>Since 30 years, an equatorial oscillation of the temperature structure with a quasi-period of 4 years has been discovered in the atmosphere of Jupiter (Orton et al. 1991, Leovy et al. 1991). This phenomenon results in a complex vertical and horizontal structure of prograde and retrograde jets. However, the wind structure of the stratosphere in the equatorial zone of Jupiter has not been measured directly. It has only been inferred in the tropical region from the thermal wind balance using temperatures measured in the jovian stratosphere and the cloud-top wind speeds measured as a initial condition (e.g. Flasar et al. 2004). But temperatures are not constrained between the upper troposphere and the middle stratosphere from observations, limiting thus the accuracy of the thermal wind balance.</p> <p>In this study, we derive self-consistently for the first time the structure of the tropical winds by utilizing wind and temperature observations all performed in the stratosphere. The wind speeds were obtained by Cavalié et al. (2021) at 1 mbar in Jupiter's stratosphere in both the equatorial and tropical regions in March 2017 with ALMA. The stratospheric thermal field was measured a few days before from the equator to the mid-latitudes with Gemini/TEXES (Giles et al. 2020). For the derivation of the wind, we use both the thermal wind equation (Pedlosky 1979) and the equatorial thermal wind equation (Marcus et al. 2019). In this paper, we will present and discuss our results.</p>

scholarly journals Effects of a wind farm installation on the understory bat community of a highly biodiverse tropical region in Mexico

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3424
Author(s):  
Miguel Briones-Salas ◽  
Mario C. Lavariega ◽  
Claudia E. Moreno
Keyword(s):  
Wind Energy ◽  
Wind Farm ◽  
Site Preparation ◽  
Tropical Region ◽  
Ecological Communities ◽  
Fragmented Habitat ◽  
Second Stage ◽  
Preparation Stage ◽  
Isthmus Of Tehuantepec ◽  
Two Stages

Wind energy has rapidly become an important alternative among renewable energies, and it is generally considered clean. However, little is known about its impact at the level of ecological communities, especially in biodiversity hotspots. The Isthmus of Tehuantepec is a highly biodiverse region in Mesoamerica, and has the highest potential for generating wind energy in Mexico. To assess the effects of installing a wind farm on the understory bat community in a landscape of fragmented habitat, we assessed its diversity and composition over four stages of installation (site preparation, construction, and two stages of operation). We captured 919 bats belonging to 22 species. Species richness, functional diversity and phylogenetic diversity decreased during construction and the first stage of operation. However, these components of biodiversity increased during the second stage of operation, and species composition began to resemble that of the site preparation stage. No species considered as sensitive to disturbance was recorded at any stage. This is the first study to reveal the diversity of a Neotropical bat community after wind turbines begin to operate.

Technoeconomic Study of Wind Energy Potential and Prospects in Oman

2010 ◽  
Author(s):  
Arif S. Malik ◽  
Haitham N. Al-Jabri ◽  
Fahad N. Al-Farsi ◽  
Thani S. Al-Ma’mary ◽  
Mohammed K. Al-Khadhuri
Keyword(s):  
Wind Energy ◽  
Gas Turbines ◽  
Wind Farm ◽  
Economic Cost ◽  
Energy Potential ◽  
Levelized Cost ◽  
Long Run ◽  
Cost Of Energy ◽  
Wind Energy Potential ◽  
Grid Application

This paper reports the study that carried out to find the wind energy potential and prospects in Oman. The results presented here are for three different sites. The first site discussed is for remote non-grid application of wind energy, the second for grid application and the third for wind pump application. The economic comparison for non-grid power applications is made between diesel engine generating sets alone and wind-diesel hybrid system at the selected location. The economic cost of grid system extension is also estimated for comparison purposes. The results show that for non-grid application for the selected site the levelized cost of wind-diesel system is 0.105 $/kWh comparing to 0.148 $/kWh for diesel system alone. For grid power application the study found that installing a 20 MW wind farm in Quiroon Hariti has a levelized cost of energy comparable to long-run marginal cost of open cycle gas turbines. For wind pump application the study found that the total annualized cost of installing wind pumps for irrigating a selected farm in Thumrait without and with one day water storage is $1,368 and $2,067 respectively. The total annualized cost of using a diesel pump for irrigating the same farm is $3,523.

scholarly journals Interannual variability of wind climates and wind turbine annual energy production

2018 ◽  
Vol 3 (2) ◽  
pp. 651-665 ◽  
Author(s):  
Sara C. Pryor ◽  
Tristan J. Shepherd ◽  
Rebecca J. Barthelmie
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Interannual Variability ◽  
Energy Production ◽  
Wind Farm ◽  
Wind Farms ◽  
Power Curve ◽  
Wind Speeds ◽  
Eastern Usa

Abstract. The interannual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in preconstruction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derive in part from variability in wind climates. However, the magnitude of IAV in wind speeds at or close to wind turbine hub heights is poorly defined and may be overestimated by assuming annual mean wind speeds are Gaussian distributed with a standard deviation (σ) of 6 %, as is widely applied within the wind energy industry. There is a need for improved understanding of the long-term wind resource and the IAV therein in order to generate more robust predictions of the financial value of a wind energy project. Long-term simulations of wind speeds near typical wind turbine hub heights over the eastern USA indicate median gross capacity factors (computed using 10 min wind speeds close to wind turbine hub heights and the power curve of the most common wind turbine deployed in the region) that are in good agreement with values derived from operational wind farms. The IAV of annual mean wind speeds at or near typical wind turbine hub heights in these simulations and AEP computed using the power curve of the most commonly deployed wind turbine is lower than is implied by assuming σ=6 %. Indeed, rather than 9 out of 10 years exhibiting AEP within 0.9 and 1.1 times the long-term mean AEP as implied by assuming a Gaussian distribution with σ of 6 %, the results presented herein indicate that in over 90 % of the area in the eastern USA that currently has operating wind turbines, simulated AEP lies within 0.94 and 1.06 of the long-term average. Further, the IAV of estimated AEP is not substantially larger than IAV in mean wind speeds. These results indicate it may be appropriate to reduce the IAV applied to preconstruction AEP estimates to account for variability in wind climates, which would decrease the cost of capital for wind farm developments.

scholarly journals An Analysis of Wind Power Generation on the Electric Transmission System of Southern Vietnam

2021 ◽  
Vol 16 ◽  
pp. 204-212
Author(s):  
Minh-Hoa Nguyen ◽  
Van-Tan Tran ◽  
Tan-Hung Pham ◽  
Thanh-Luu Cao
Keyword(s):  
Power Generation ◽  
Power Systems ◽  
Power System ◽  
Wind Energy ◽  
Wind Turbines ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Speeds ◽  
Southern Vietnam ◽  
Three Phase

Renewable energy is an emerging candidate in power generation for the compensation of the exhausted fossil fuel, in which wind energy plays an important role. However, how wind farms impact existing power systems has still been a subject on which many researchers are studying. This study has analyzed and evaluated the four wind farms consisting of Ca-Mau (300 MW), Bac-Lieu (99 MW), Soc-Trang (100 MW) and Tra-Vinh (33 MW) located in Southern Vietnam via using the commercial package, WAsP software. Ca-Mau wind farm has the highest planned rated capacity with 51.7% among the wind farms. Each wind farm is built from three different types of wind turbines (1 MW, 2 MW and 3 MW). The estimation has shown that all of the wind farms could produce 2,265 GWh annually, and the 3-MW wind turbines are the most efficient and give the smallest losses for producing wind energy. The wind farms, with respect to environmentally friendly aspects, could avoid 978,544 tCO2 emitted to the environment annually. Additionally, the ETAP program has also been applied to simulate the effects of the proposed wind farms on the national power system including the disturbances from wind speeds, three-phase bus faults, tripping off wind farms and three-phase line faults on the power system. The results show that the wind farms are only slightly impacted.

Improving short-term wind power forecasts during ramp events by including nacelle wind speed observations

2021 ◽  
Author(s):  
Moritz Lochmann ◽  
Heike Kalesse-Los ◽  
Michael Schäfer ◽  
Ingrid Heinrich ◽  
Ronny Leinweber
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Wind Farm ◽  
Mean Deviation ◽  
Short Term ◽  
Wind Speeds ◽  
Sonic Anemometers ◽  
Ramp Events

<p>Wind energy is and will be one of the key technologies for a transition to green electricity. However, the smooth integration of the generated wind energy into the electrical grid depends on reliable power forecasts. Rapid changes in power generation, so-called ramps, are not always reflected properly in NWP data and pose a challenge for power predictions and, therefore, grid operation. While contributions to the topic of ramp forecasting increased in the recent years, this work approaches the mitigation of deviations from the forecast more directly.</p> <p>The power forecast tool used here is based on an artificial neural network, trained and evaluated on multiple years of data. It is applied in comparison to power generation data for a 44 MW wind farm in Brandenburg. For short-term wind power forecasts, NWP wind speeds in this power forecast tool are replaced with recent Doppler Lidar wind profiles and nacelle wind speed observations from ultra-sonic anemometers, aiming to provide an easy-to-implement way to reduce negative impacts of ramps. Compared to NWP input data, this persistence approach with observational data aims to improve the forecast quality especially during the time of wind ramps.</p> <p>Different ramp definitions and forecast horizons are explored. In general, the number of ramps detected increases dramatically when using wind speed observations instead of the (too smooth) NWP model data. In addition, the mean deviation between power forecast and actual power generation around ramp events decreases, indicating a reduced need for balancing efforts.</p>

Does wind speed effects performance and cost of energy? A case study of wind farm

2020 ◽  
Vol 14 (5) ◽  
pp. 953-974
Author(s):  
Zahid Hussain Hulio ◽  
Wei Jiang
Keyword(s):  
Renewable Energy ◽  
Wind Speed ◽  
Wind Farm ◽  
Power Coefficient ◽  
Local Wind ◽  
Content Type ◽  
Wind Speeds ◽  
Cost Of Energy ◽  
Wind Characteristics ◽  
The Cost

Purpose The rapid rising of renewable energy sources particularly wind energy cannot be ignored. The numerical increase in wind energy farms throughout the world is the best example. The purpose of this paper is to assess the basic question of whether wind characteristics affect the performance and cost of energy. The importance of this question cannot be ruled out while comparing renewable energy to a conventional form of energy more specifically especially for the developing country where the cost of energy is very high. Design/methodology/approach The research design of this paper is consists of an assessment of local wind characteristics of the wind farm site using Weibull k and c parameters. The performance model is used to assess the performance of the wind turbine (WT) corresponding to local wind characteristics. The wind correlation with WT in terms of changing wind speed has been assessed to quantify the effects of wind speed on the WT behavior and failure of WT components. Similarly, the power curve of WT is assessed and compared with the International Electrotechnical Commission standards 61400-12-2. The WT power coefficient and tip speed ratio corresponding to wind speed is also investigated. The energy volume and cost of energy lost model is used to determine the cost and volume loss of energy/kWh of the wind farm. Findings The findings of practical wind farms showed that the wind conditions of the site are showing a strong tendency that can be determined from the results of Weibull k and c parameters. The k and c parameters are observed to be 3.44 and 9.16 m/s, respectively, for a period of a year. The standard deviation is observed to be 2.56 for a period of a year. WT shows the efficient behavior can be obtained from the power coefficient and tip speed of WT at different wind speeds. Also, wind farm observation showed that to be some increasing wind speed cause of based WT component failures. The results of energy volume and cost/kWh assessment showed that the major portion of energy volume and cost of energy is lost owing to network, voltage dip and frequency surge, electrical and mechanical components failures. Originality/value Generally, it can be concluded that the WTs are now able to cope with variable wind speeds. However, the results of this paper are showing that WT performance and availability decreased due to increased wind speeds. It can also be a reason to decreased volume and increase the cost of energy/kWh.

scholarly journals Higher Wind: Highlighted Expansion Opportunities to Repower Wind Energy

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7716
Author(s):  
Francisco Haces-Fernandez
Keyword(s):  
Wind Energy ◽  
Wind Farm ◽  
Wind Farms ◽  
Energy Generation ◽  
The United States ◽  
Wind Speeds ◽  
Wind Energy Generation ◽  
Novel Method ◽  
Renewable Energy Generation ◽  
Near Future

Decarbonizing the world economy, before the most damaging effects of climate change become irreversible, requires substantially increasing renewable energy generation in the near future. However, this may be challenging in mature wind energy markets, where many advantageous wind locations are already engaged by older wind farms, potentially generating suboptimal wind harvesting. This research developed a novel method to systematically analyze diverse factors to determine the level of maturity of wind markets and evaluate the adequacy of wind farm repowering at regional and individual levels. The approach was applied to wind markets in the United States (U.S.), in which several states were identified as having diverse levels of maturity. Results obtained from case studies in Texas indicated a consequential number of wind farms that have reached their twenty-year end-of-life term and earlier obsolescence levels. The proposed approach aided in determining wind farms that may benefit from total or partial repowering. The method indicated that total repowering of selected installations would significantly increase overall wind energy generation, considering that these older installations have access to some of the best wind speeds, infrastructure and areas to grow. The proposed method can be applied to different world wind markets.

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