Wind Energy Potential in Jordan: Analysis of the First Large-Scale Wind Farm and Techno-Economic Assessment of Potential Farms

2020 ◽  
Vol 143 (1) ◽  
Author(s):  
Suhil Kiwan ◽  
Elyasa Al-Gharibeh ◽  
Emad Abu-Lihia
Keyword(s):  
Wind Energy ◽  
Large Scale ◽  
Wind Farm ◽  
Economic Assessment ◽  
Capacity Factor ◽  
First Year ◽  
Energy Potential ◽  
Levelized Cost Of Electricity ◽  
Total Capacity ◽  
The Cost

Abstract We research the investment potential of wind energy in Jordan. The capacity factor of the first large-scale wind farm in the country, Tafila Wind Farm, was found to be 33.1%, based on actual energy production during its first year of operation. The best performing turbine in the farm achieved a capacity factor of 39.1%. Other eight sites, which are expected to have such capacity factors were subjected to techno-economic investigation utilizing 52 different turbine models of nameplate capacities range from 1.0 to 5.0 MW. A capacity factor higher than 25.0% can be achieved at all the studied sites. The average levelized cost of electricity of the 52 turbines at the eight sites is 0.0708 $/kWh, and the cost ranges from 0.0452 to 0.1108 $/kWh. A proposed 80 MW farm at every location results in a total capacity of 640 MW and an annual estimated energy generation of 1545.0–2076.0 GWh, around 7.0–9.0% of the country's projected electricity demand in 2020.

Assessment of bioenergy development potential in agricultural enterprises

2020 ◽  
pp. 165-171
Author(s):  
Iryna Hryhoruk
Keyword(s):  
Renewable Energy ◽  
Large Scale ◽  
Agricultural Waste ◽  
General Structure ◽  
Geographical Location ◽  
Economic Assessment ◽  
Energy Resources ◽  
Industrial Complex ◽  
Renewable Energy Resources ◽  
Energy Potential

Exhaustion of traditional energy resources, their uneven geographical location, and catastrophic changes in the environment necessitate the transition to renewable energy resources. Moreover, Ukraine's economy is critically dependent on energy exports, and in some cases, the dependence is not only economic but also political, which in itself poses a threat to national security. One of the ways to solve this problem is the large-scale introduction and use of renewable energy resources, bioenergy in particular. The article summarizes and offers methods for assessing the energy potential of agriculture. In our country, a significant amount of biomass is produced every year, which remains unused. A significant part is disposed of due to incineration, which significantly harms the environment and does not allow earning additional funds. It is investigated that the bioenergy potential of agriculture depends on the geographical distribution and varies in each region of Ukraine. Studies have shown that as of 2019 the smallest share in the total amount of conventional fuel that can be obtained from agricultural waste and products suitable for energy production accounts for Zakarpattya region - 172.5 thousand tons. (0.5% of the total) and Chernivtsi region - 291.3 thousand tons. (0.9%). Poltava region has the greatest potential - 2652.2 thousand tons. (7.8%) and Vinnytsia - 2623.7 thousand tons. (7.7%). It should be noted that the use of the energy potential of biomass in Ukraine can be called unsatisfactory. The share of biomass in the provision of primary energy consumption is very small. For bioenergy to occupy its niche in the general structure of the agro-industrial complex, it is necessary to develop mechanisms for its stimulation. In addition, an effective strategy for the development of the bioenergy sector of agriculture is needed. The article considers the general energy potential of agriculture, its indicative structure. The analysis is also made in terms of areas. In addition, an economic assessment of the possible use of existing potential is identified.

scholarly journals Harnessing Wind Energy Potential in ASEAN: Modelling and Policy Implications

2021 ◽  
Vol 13 (8) ◽  
pp. 4279
Author(s):  
Youngho Chang ◽  
Phoumin Han
Keyword(s):  
Wind Energy ◽  
Carbon Emissions ◽  
Policy Implications ◽  
Wind Generation ◽  
Energy Potential ◽  
Trade Model ◽  
Electricity Trade ◽  
Generation Capacity ◽  
The Cost ◽  
Business As Usual

This study examines whether and how harnessing more wind energy can decrease the cost of meeting the demand for electricity and amount of carbon emissions in the Association for Southeast Asian Nations (ASEAN) region, using the ASEAN integrated electricity trade model. Three scenarios are considered: a counterfactual business-as-usual (BAU) scenario, which assumes no wind energy is used; an actual BAU scenario that uses the wind-generation capacity in 2018; and a REmap scenario, which employs the wind-generation capacity from the Renewable Energy Outlook for ASEAN. Simulation results suggest that dispatching more wind energy decreases the cost of meeting the demand for electricity and amount of carbon emissions. However, these emissions increase during the late years of the study period, as the no- or low-emitting energy-generation technologies are crowded out.

Techno-Economic Assessment of Utilizing Wind Energy for Hydrogen Production Through Electrolysis

2017 ◽  
Author(s):  
Reza Ziazi ◽  
Kasra Mohammadi ◽  
Navid Goudarzi
Keyword(s):  
Hydrogen Production ◽  
Wind Energy ◽  
Wind Turbines ◽  
Alternative Energy ◽  
Large Scale ◽  
Fossil Fuels ◽  
Combustion Engine ◽  
Economic Assessment ◽  
Large Cities ◽  
North East

Hydrogen as a clean alternative energy carrier for the future is required to be produced through environmentally friendly approaches. Use of renewables such as wind energy for hydrogen production is an appealing way to securely sustain the worldwide trade energy systems. In this approach, wind turbines provide the electricity required for the electrolysis process to split the water into hydrogen and oxygen. The generated hydrogen can then be stored and utilized later for electricity generation via either a fuel cell or an internal combustion engine that turn a generator. In this study, techno-economic evaluation of hydrogen production by electrolysis using wind power investigated in a windy location, named Binaloud, located in north-east of Iran. Development of different large scale wind turbines with different rated capacity is evaluated in all selected locations. Moreover, different capacities of electrolytic for large scale hydrogen production is evaluated. Hydrogen production through wind energy can reduce the usage of unsustainable, financially unstable, and polluting fossil fuels that are becoming a major issue in large cities of Iran.

scholarly journals Optimizing operation of a large-scale pumped storage hydropower system coordinated with wind farm by means of genetic algorithms

2019 ◽  
Keyword(s):  
Genetic Algorithms ◽  
Renewable Energy ◽  
Wind Energy ◽  
Large Scale ◽  
Wind Farm ◽  
Closed Loop ◽  
Open Loop ◽  
Energy Output ◽  
Reservoir System ◽  
Pumped Storage

<p>Due to the intermittent and fluctuating nature of wind and other renewable energy sources, their integration into electricity systems requires large-scale and flexible storage systems to ensure uninterrupted power supply and to reduce the percentage of produced energy that is discarded or curtailed. Storage of large quantities of electricity in the form of dynamic energy of water masses by means of coupled reservoirs has been globally recognized as a mature, competitive and reliable technology; it is particularly useful in countries with mountainous terrain, such as Greece. Its application may increase the total energy output (and profit) of coupled wind-hydroelectric systems, without affecting the availability of water resources. Optimization of such renewable energy systems is a very complex, multi-dimensional, non-linear, multi modal, nonconvex and dynamic problem, as the reservoirs, besides hydroelectric power generation, serve many other objectives such as water supply, irrigation and flood mitigation. Moreover, their function should observe constraints such as environmental flow. In this paper we developed a combined simulation and optimization model to maximize the total benefits by integrating wind energy production into a pumped-storage multi-reservoir system, operating either in closed-loop or in open-loop mode. In this process, we have used genetic algorithms as the optimization tool. Our results show that when the operation of the reservoir system is coordinated with the wind farm, the hydroelectricity generation decreases drastically, but the total economical revenue of the system increases by 7.02% when operating in closed-loop and by 7.16% when operating in open-loop mode. We conclude that the hydro-wind coordination can achieve high wind energy penetration to the electricity grid, resulting in increase of the total benefits of the system. Moreover, the open-loop pumped-storage multi-reservoir system seems to have better performance, ability and flexibility to absorb the wind energy decreasing to a lesser extent the hydroelectricity generation, than the closed-loop.</p>

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.

Decision Support System for Wind Farm Installation Using Bipolar Analysis

2015 ◽  
pp. 1-21 ◽  
Author(s):  
Yasmina Bouzarour-Amokrane ◽  
Ayeley P. Tchangani ◽  
François Pérès
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Wind Energy ◽  
Support System ◽  
Large Scale ◽  
Wind Farm ◽  
Negative Impact ◽  
Life Quality ◽  
Energy Projects ◽  
And Performance

The necessity to control and reduce the negative impact of human activities on environment and life quality along with technology progress in renewable energy in general and wind energy in particular render it possible today to consider wind energy projects on a large scale. Developing wind energy on a large scale however raises other problems such as choosing an adequate site to settle a wind farm where many other issues such technical feasibility and performance levels, visual pollution, economic and social concerns, etc. must be addressed. Such decisions usually involve many parameters and necessitate the collaboration of many stakeholders. In this context, this chapter proposes an approach based on the concept of bipolar analysis through Benefit Opportunity Cost and Risk (BOCR) analysis, which permits one to address correctly a Group Decision-Making Problem (GDMP) to build a decision support system in order to assist the wind farm installation process.

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.

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 Influence of the ENSO and Monsoonal Season on Long-Term Wind Energy Potential in Malaysia

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 2965 ◽  
Author(s):  
Aliashim Albani ◽  
Mohd Ibrahim ◽  
Kim Yong
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
El Nino ◽  
Southwest Monsoon ◽  
Capacity Factor ◽  
Wind Data ◽  
Northeast Monsoon ◽  
Energy Potential ◽  
Wind Energy Potential

This paper assesses the long-term wind energy potential at three selected sites, namely Mersing and Kijal on the east coast of peninsular Malaysia and Kudat in Sabah. The influence of the El Niño-Southern Oscillation on reanalysis and meteorological wind data was assessed using the dimensionless median absolute deviation and wavelet coherency analysis. It was found that the wind strength increases during La Niña events and decreases during El Niño events. Linear sectoral regression was used to predict the long-term wind speed based on the 35 years of extended Climate Forecast System Reanalysis data and 10 years of meteorological wind data. The long-term monthly energy production was computed based on the 1.5 MW Goldwind wind turbine power curve. The measured wind data were extrapolated to the selected wind turbine default hub height (70 m.a.s.l) by using the site-specific power law indexed. The results showed that the capacity factor is higher during the Northeast monsoon (21.32%) compared to the Southwest monsoon season (3.71%) in Mersing. Moreover, the capacity factor in Kijal is also higher during the Northeast monsoon (10.66%) than during the Southwest monsoon (5.19%). However, in Kudat the capacity factor during the Southwest monsoon (36.42%) is higher compared to the Northeast monsoon (24.61%). This is due to the tail-effect of tropical storms that occur during this season in the South China Sea and Pacific Ocean.

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