scholarly journals Key aspects and feasibility assessment of a proposed wind farm in Jordan

2019 ◽  
Vol 15 (1) ◽  
pp. 97-105 ◽  
Author(s):  
Mohammad Al-Addous ◽  
Motasem Saidan ◽  
Mathhar Bdour ◽  
Zakariya Dalala ◽  
Aiman Albatayneh ◽  
...  
Keyword(s):  
Wind Energy ◽  
Transmission Lines ◽  
Wind Farm ◽  
Cost Effective ◽  
Selling Price ◽  
Technological Advancement ◽  
Energy Potential ◽  
Environmental Consequences ◽  
Feasibility Assessment ◽  
The Interest Rate

Abstract To tackle climate change and secure energy supplies, many countries invest heavily on wind energy as it is a clean source and is becoming more cost effective with the technological advancement and increased capacity per unit installed. The investigation of the availability of wind resources is an essential step of any feasibility study of a wind farm project and is vital for securing financial resources. With this intent, the main aspects for designing a wind farm at Ajloun (north of Jordan) is investigated and wind energy potential is determined based on available wind data. Based on the site characteristic, the required infrastructure is highlighted, including the turbine array layout and the pattern of connections with the external transmission lines. The investigation of the feasibility of the project includes an appraisal of social and environmental consequences of constructing the wind farm project. The results show that the selected location for the wind farm is encouraging and has a promising profit potential. The findings estimate the annual electricity generation of the wind farm at 379659.51 MWh, with a breakeven selling point of around $30.03/MWh, at a highly competitive price. However, with an estimated selling price of $36.65/MWh on average, it will settle the interest rate demanded by the banks that have an internal rate of return of 7%. No major issues with geotechnical and environmental issues were identified with respect to the project.

scholarly journals Wind Energy Implementation to Mitigate Wildfire Risk and Preemptive Blackouts

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2421
Author(s):  
Francisco Haces-Fernandez
Keyword(s):  
At Risk ◽  
Wind Energy ◽  
Transmission Lines ◽  
Wind Farm ◽  
Wind Farms ◽  
Offshore Wind ◽  
Energy Potential ◽  
High Power Output ◽  
Wind Energy Potential ◽  
Fire Threat

Damages caused by wildfires in California due to transmission line failures have increased significantly in recent years. Curtailment of electric service in areas under fire threat has been implemented to avoid these wildfires. Results from this research indicated that 24% of California’s cities are at risk of wildfire, while 52% are at risk of blackout. These blackouts have resulted in significant financial losses and risk to life and health. Undergrounding current transmission lines has been proposed as a long-term solution. However, undergrounding lines would take decades to complete and increase average monthly electric bills from $80 to $260. This research investigated shortening the length of the electricity supply chain, supplying affected communities with onshore and offshore wind energy. Results showed good wind energy potential in locations near affected cities. Distance analyses revealed that more than two hundred cities (population 5.5 million) can be served by existing wind farms located at less than 50 km. Future offshore wind turbines could generate high power output (capacity factor >50% for significant periods). An analysis of diverse locations along California’s coast indicated that just one offshore wind farm could serve more than a hundred cities with cumulative population larger than one million.

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.

Estimating the potential of wind energy resources using Weibull parameters: A case study of the coastline region of Dar es Salaam, Tanzania

2021 ◽  
Vol 11 (1) ◽  
pp. 1093-1104
Author(s):  
Enock Michael ◽  
Dominicus Danardono Dwi Prija Tjahjana ◽  
Aditya Rio Prabowo
Keyword(s):  
Parameter Estimation ◽  
Wind Energy ◽  
Wind Turbine ◽  
Cost Effective ◽  
Dar Es Salaam ◽  
Capacity Factor ◽  
Energy Potential ◽  
Weibull Parameters ◽  
Distribution Parameter Estimation ◽  
Annual Capacity

Abstract This study aimed to compare the graphical method (GM) and standard deviation method (SDM), based on analyses and efficient Weibull parameters by estimating future wind energy potential in the coastline region of Dar es Salaam, Tanzania. Hence, the conclusion from the numerical method comparisons will also determine suitable wind turbines that are cost-effective for the study location. The wind speed data for this study were collected by the Tanzania Meteorological Authority Dar es Salaam station over the period of 2017 to 2019. The two numerical methods introduced in this study were both found to be appropriate for Weibull distribution parameter estimation in the study area. However, the SDM gave a higher value of the Weibull parameter estimation than the GM. Furthermore, the five selected commercial wind turbine models that were simulated in terms of performance were based on a capacity factor using the SDM and were both over 25% the recommended capacity factor value. The Polaris P50-500 commercial wind turbine is recommend as a suitable wind turbine to be installed in the study area due to its maximum annual capacity factor value over 3 years.

scholarly journals A Framework for the Selection of Optimum Offshore Wind Farm Locations for Deployment

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1855 ◽  
Author(s):  
Varvara Mytilinou ◽  
Estivaliz Lozano-Minguez ◽  
Athanasios Kolios
Keyword(s):  
Decision Making ◽  
Wind Energy ◽  
Wind Farm ◽  
Cost Effective ◽  
Optimization Techniques ◽  
Offshore Wind ◽  
Moray Firth ◽  
The Uk ◽  
The Given ◽  
Nondominated Sorting

This research develops a framework to assist wind energy developers to select the optimum deployment site of a wind farm by considering the Round 3 available zones in the UK. The framework includes optimization techniques, decision-making methods and experts’ input in order to support investment decisions. Further, techno-economic evaluation, life cycle costing (LCC) and physical aspects for each location are considered along with experts’ opinions to provide deeper insight into the decision-making process. A process on the criteria selection is also presented and seven conflicting criteria are being considered for implementation in the technique for the order of preference by similarity to the ideal solution (TOPSIS) method in order to suggest the optimum location that was produced by the nondominated sorting genetic algorithm (NSGAII). For the given inputs, Seagreen Alpha, near the Isle of May, was found to be the most probable solution, followed by Moray Firth Eastern Development Area 1, near Wick, which demonstrates by example the effectiveness of the newly introduced framework that is also transferable and generic. The outcomes are expected to help stakeholders and decision makers to make better informed and cost-effective decisions under uncertainty when investing in offshore wind energy in the UK.

Wind resource assessment and wind farm modeling in Mossobo-Harena area, North Ethiopia

2020 ◽  
pp. 0309524X2092540
Author(s):  
Addisu Dagne Zegeye
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Power Density ◽  
Energy Production ◽  
Wind Farm ◽  
Ground Level ◽  
Energy Potential ◽  
Mean Power ◽  
Wind Energy Potential

Although Ethiopia does not have significant fossil fuel resource, it is endowed with a huge amount of renewable energy resources such as hydro, wind, geothermal, and solar power. However, only a small portion of these resources has been utilized so far and less than 30% of the nation’s population has access to electricity. The wind energy potential of the country is estimated to be up to 10 GW. Yet less than 5% of this potential is developed so far. One of the reasons for this low utilization of wind energy in Ethiopia is the absence of a reliable and accurate wind atlas and resource maps. Development of reliable and accurate wind atlas and resource maps helps to identify candidate sites for wind energy applications and facilitates the planning and implementation of wind energy projects. The main purpose of this research is to assess the wind energy potential and model wind farm in the Mossobo-Harena site of North Ethiopia. In this research, wind data collected for 2 years from Mossobo-Harena site meteorological station were analyzed using different statistical software to evaluate the wind energy potential of the area. Average wind speed and power density, distribution of the wind, prevailing direction, turbulence intensity, and wind shear profile of the site were determined. Wind Atlas Analysis and Application Program was used to generate the generalized wind climate of the area and develop resource maps. Wind farm layout and preliminary turbine micro-sitting were done by taking various factors into consideration. The IEC wind turbine class of the site was determined and an appropriate wind turbine for the study area wind climate was selected and the net annual energy production and capacity factor of the wind farm were determined. The measured data analysis conducted indicates that the mean wind speed at 10 and 40 m above the ground level is 5.12 and 6.41 m/s, respectively, at measuring site. The measuring site’s mean power density was determined to be 138.55 and 276.52 W/m2 at 10 and 40 m above the ground level, respectively. The prevailing wind direction in the site is from east to south east where about 60% of the wind was recorded. The resource grid maps developed by Wind Atlas Analysis and Application Program on a 10 km × 10 km area at 50 m above the ground level indicate that the selected study area has a mean wind speed of 5.58 m/s and a mean power density of 146 W/m2. The average turbulence intensity of the site was found to be 0.136 at 40 m which indicates that the site has a moderate turbulence level. According to the resource assessment done, the area is classified as a wind Class IIIB site. A 2-MW rated power ENERCON E-82 E2 wind turbine which is an IEC Class IIB turbine with 82 m rotor diameter and 98 m hub height was selected for estimation of annual energy production on the proposed wind farm. 88 ENERCON E-82 E2 wind turbines were properly sited in the wind farm with recommended spacing between the turbines so as to reduce the wake loss. The rated power of the wind farm is 180.4 MW and the net annual energy production and capacity factor of the proposed wind farm were determined to be 434.315 GWh and 27.48% after considering various losses in the wind farm.

scholarly journals Offshore wind energy potential for Bahrain via multi-criteria evaluation

2020 ◽  
pp. 0309524X2092539
Author(s):  
Mohamed Elgabiri ◽  
Diane Palmer ◽  
Hanan Al Buflasa ◽  
Murray Thomson
Keyword(s):  
Wind Energy ◽  
Geographical Information Systems ◽  
Wind Farm ◽  
Electricity Consumption ◽  
Pairwise Comparison ◽  
Wind Farms ◽  
Offshore Wind ◽  
Geographical Information ◽  
Energy Yield ◽  
Energy Potential

Current global commitments to reduce the emissions of greenhouse gases encourage national targets for renewable generation. Due to its small land mass, offshore wind could help Bahrain to fulfil its obligations. However, no scoping study has been carried out yet. The methodology presented here addresses this research need. It employs analytical hierarchy process and pairwise comparison methods in a geographical information systems environment. Publicly available land use, infrastructure and transport data are used to exclude areas unsuitable for development due to physical and safety constraints. Meteorological and oceanic opportunities are ranked and then competing uses are analyzed to deliver optimal sites for wind farms. The potential annual wind energy yield is calculated by dividing the sum of optimal areas by a suitable turbine footprint to deliver maximum turbine number. In total, 10 favourable wind farm areas were identified in Bahrain’s territorial waters, representing about 4% of the total maritime area, and capable of supplying 2.68 TWh/year of wind energy or almost 10% of the Kingdom’s annual electricity consumption. Detailed maps of potential sites for offshore wind construction are provided in the article, giving an initial plan for installation in these locations.

Effects of global warming on wind energy potential

2015 ◽  
Vol 12 (4) ◽  
pp. 369-374 ◽  
Author(s):  
Afsin Gungor
Keyword(s):  
Global Warming ◽  
Wind Energy ◽  
Wind Power ◽  
Wind Farm ◽  
Wind Data ◽  
Energy Potential ◽  
Time Intervals ◽  
Wind Energy Generation ◽  
Wind Energy Potential ◽  
Yearly Data

A recent study conducted to determine the potential of wind power in Nigde which used 35 year wind data, has shown that global warming may also affect the potential of wind power negatively. The wind data were collected on 10 min time intervals at 10 m mast height. The missing data were 3.9%. When the results are closely examined it is observed that the potential of wind power has decreased dramatically throughout the years. The 35 yearly data has shown a decrease of wind power density from 48.14 W/m2 to 13.25 W/m2. These results are of extreme importance because of various reasons given below. The first problem we may see is that it is possible to observe an area which was once regarded as a highly suitable region for wind energy generation is now not as sustainable as it was assumed to be. Thus it may stand as a hidden but great risk for certain wind farm investments. Therefore, the calculation of wind power potential is a really serious matter to deal with. Moreover, if the loss of the wind power potential is observed consistently and continually as a result of global warming, the only reasonable solution to this problem may be the relocation of the whole power-plant.

scholarly journals Wind Energy Potential in Kuching Areas of Sarawak for Small-Scale Power Application

2015 ◽  
Vol 15 ◽  
pp. 1-10 ◽  
Author(s):  
S.M. Lawan ◽  
W.A.W.Z. Abidin ◽  
W.Y. Chai ◽  
Azhaili Baharun ◽  
Thelaha Masri
Keyword(s):  
Wind Energy ◽  
Lower Layer ◽  
National Development ◽  
Cost Effective ◽  
Energy System ◽  
Small Scale ◽  
Energy Potential ◽  
Wind Energy Potential ◽  
Power Application ◽  
Wind Energy Systems

Energy is a catalyst for national development; most of the countries depend on hydrocarbon fuels for power generation. The traditional sources of energy are exorbitant and finite. In addition, they emit excessive carbon dioxide and other gases into the lower layer of the atmosphere which influence the increase occurrence of global warming in the world. Recently, renewable energy’s are gaining more attraction and attention in many parts of the globe, due to non-polluting characteristics. Among the renewable, wind power has emerged as safest and cleanest resource that will satisfy the need of energy in a cost effective way. Wind energy system can suit the energy need for grid and stand alone mode. This paper investigates the potential of wind energy in Kuching for small-scale application. The study employed three years wind speed data spanning from 2010-2012 observed at the Kuching meteorological station. Details of the analysis and potential of using wind energy systems are presented. Additionally, the output performances of two wind turbines are examined on the basis of the computed Weibull distribution.

scholarly journals Evaluation of wind energy potential of the state of Tamil Nadu, India based on trend analysis

2021 ◽  
Vol 49 (1) ◽  
pp. 244-251
Author(s):  
Narayanan Natarajan ◽  
S. Rehman ◽  
Nandhini Shiva ◽  
M. Vasudevan
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Trend Analysis ◽  
Tamil Nadu ◽  
Wind Farm ◽  
Linear Trend ◽  
Energy Output ◽  
Energy Yield ◽  
Energy Potential ◽  
Increasing Trend

An accurate estimate of wind resource assessment is essential for the identification of potential site for wind farm development. The hourly average wind speed measured at 50 m above ground level over a period of 39 years (1980-2018) from 25 locations in Tamil Nadu, India have been used in this study. The annual and seasonal wind speed trends are analyzed using linear and Mann-Kendall statistical methods. The annual energy yield, and net capacity factor are obtained for the chosen wind turbine with 2 Mega Watt rated power. As per the linear trend analysis, Chennai and Kanchipuram possess a significantly decreasing trend, while Nagercoil, Thoothukudi, and Tirunelveli show an increasing trend. Mann-Kendall trend analysis shows that cities located in the southern peninsula and in the vicinity of the coastal regions have significant potential for wind energy development. Moreover, a majority of the cities show an increasing trend in the autumn season due to the influence of the retreating monsoons which is accompanied with heavy winds. The mean wind follows an oscillating pattern throughout the year at all the locations. Based on the net annual energy output, Nagercoil, Thoothukudi and Nagapattinam are found to be the most suitable locations for wind power deployment in Tamil Nadu, followed by Cuddalore, Kumbakonam, Thanjavur and Tirunelveli.

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