The technical and economical feasibility study of offshore wind farms in Turkey

Yıldırım, Alper

doi:10.1007/s10098-022-02392-0

Cited by 12 publications

(4 citation statements)

References 57 publications

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“…Using the site specific constants and wind turbine parameters, COE evaluation starts by calculating the scale factor at reference height c 0 30–33 :

{c}_{0}=\frac{{V}_{{\rm{m}}}}{{\rm{\Gamma }}\left(1+\frac{1}{{k}_{0}}\right)},

were Γ is the Gamma function.…”

Section: Coe Modelmentioning

confidence: 99%

“…Wind turbine parameters include maximum power coefficient C p max (0.48), 28 total loss of energy η (0.17), 29 cut-in wind speed V cut-in (3 m/s), cut-off wind speed V cut-off (22.5 m/s), rated wind speed V r (9.9 m/s), rated power P r (4000 kW) and the fix charge rate FCR (0.1158). 11 Using the site specific constants and wind turbine parameters, COE evaluation starts by calculating the scale factor at reference height c 0 [30][31][32][33] :…”

Section: Coe Modelmentioning

confidence: 99%

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A techno‐economic assessment and optimization of Dumat Al‐Jandal wind farm in Kingdom of Saudi Arabia

Marouani,

Fouad,

Mrad

2023

Energy Science & Engineering

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One major criterion in the selection of wind farm location is the cost of energy (COE). COE is the cost of producing 1 kWh electric energy on an annual basis. Mathematical model of COE includes site‐specific constants (such as reference height, mean wind speed, shape factors, wind shear coefficient, average temperature, and turbine altitude) and wind turbine parameters (such as maximum power coefficient, total loss of energy, cut‐in/cut‐off wind speed, rated wind speed, rated power, and the fix charge rate). In this work, we evaluate the COE of an onshore wind farm located at Dumat Al‐Jandal (Saudi Arabia) according to the hub height and rotor size. The 99 Vestas turbines can be mounted at a hub height ranging from 105 to 166 m with available rotor diameters of 105, 112, 117, 126, 136, 150, 155, or 163 m. Particle swarm optimization with a normal distribution is used to optimize the COE. Results show that COE is varying around the average value of $0.029335/kWh by ±$0.00021/kWh. The minimum COE was achieved with a rotor diameter of 150 m at hub height of 105 m. COE increases with the increase of hub height. At 105 m‐hub height, COE is almost the same, with a variation of 0.03% (It ranges between $0.029125/kWh and $0.029133/kWh). COE is more sensitive to rotor size than hub height. This investigation revealed that the COE estimation is in a range of 39%–48% greater than that announced COE by the developing project consortium.

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“…Using the site specific constants and wind turbine parameters, COE evaluation starts by calculating the scale factor at reference height c 0 30–33 :

{c}_{0}=\frac{{V}_{{\rm{m}}}}{{\rm{\Gamma }}\left(1+\frac{1}{{k}_{0}}\right)},

were Γ is the Gamma function.…”

Section: Coe Modelmentioning

confidence: 99%

Section: Coe Modelmentioning

confidence: 99%

A techno‐economic assessment and optimization of Dumat Al‐Jandal wind farm in Kingdom of Saudi Arabia

Marouani,

Fouad,

Mrad

2023

Energy Science & Engineering

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“…For the successful deployment of wind power, onshore or offshore, comprehensive and accurate understanding of its potential is critical [1]. As the world is transiting towards cleaner and sustainable sources of electricity generation, offshore wind power has emerged as a potential solution [2,3].…”

Section: Introductionmentioning

confidence: 99%

“…As the world is transiting towards cleaner and sustainable sources of electricity generation, offshore wind power has emerged as a potential solution [2,3]. Offshore wind farms have attracted the interest of legislators, energy companies, and environmentalists as a result of their vast untapped potential to generate substantial quantities of renewable energy [1]. Accordingly, in recent times, offshore wind power installed capacities have expanded from 3.056 GW to 54.259 GW, corresponding to the years 2010 to 2021, and reached 63.2 GW in 2022 [4].…”

Section: Introductionmentioning

confidence: 99%

Offshore Wind Power Resource Assessment in the Gulf of North Suez

Rehman,

Irshad,

Ibrahim

et al. 2023

Sustainability

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Growing population, industrialization, and power requirements are adversely affecting the environment through increased greenhouse gases resulting from fossil fuel burning. Global greenhouse gas mitigation targets have led nations to promote clean and self-renewable sources of energy to address this environmental issue. Offshore wind power resources are relatively more attractive due to high winds, less turbulence, minimal visualization effects, and no interaction of infrastructure. The present study aims at conducting an offshore wind power resource assessment (OWPRA) at some locations in the Gulf of North Suez. For this purpose, the long-term hourly mean wind speed (WS) and wind direction above mean sea level (AMSL), as well as temperature and pressure data near the surface, are used. The data is obtained from ERA5 (fifth generation global climate reanalysis) at six (L1–L6) chosen offshore locations. The data covers a period of 43 years, between 1979 and 2021. The WS and direction are provided at 100 m AMSL, while temperature and pressure are available near water-surface level. At the L1 to L6 locations, the log-term mean WS and wind power density (WPD) values are found to be 7.55 m/s and 370 W/m2, 6.37 m/s and 225 W/m2, 6.91 m/s and 281 W/m2, 5.48 m/s and 142 W/m2, 4.30 m/s and 77 W/m2, and 5.03 and 115 W/m2 and at 100 m AMSL, respectively. The higher magnitudes of monthly and annual windy site identifier indices (MWSI and AWSI) of 18.68 and 57.41 and 12.70 and 42.94 at the L1 and L3 sites, and generally lower values of wind variability indices, are indicative of a favorable winds source, which is also supported by higher magnitudes of mean WS, WPD, annual energy yields, plant capacity factors, and wind duration at these sites. The cost of energy for the worst and the best cases are estimated as 10.120 USD/kWh and 1.274 USD/kWh at the L5 and L1 sites, corresponding to wind turbines WT1 and WT4. Based on this analysis, sites L1, L3, and L2 are recommended for wind farm development in order of preference. The wind variability and windy site identifier indices introduced will help decision-makers in targeting potential windy sites with more confidence.

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Statistical investigation of wave power potential in the North Aegean Sea

Pinar

Alkanat

2023

Clean Techn Environ Policy

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The technical and economical feasibility study of offshore wind farms in Turkey

Cited by 12 publications

References 57 publications

A techno‐economic assessment and optimization of Dumat Al‐Jandal wind farm in Kingdom of Saudi Arabia

A techno‐economic assessment and optimization of Dumat Al‐Jandal wind farm in Kingdom of Saudi Arabia

Offshore Wind Power Resource Assessment in the Gulf of North Suez

Statistical investigation of wave power potential in the North Aegean Sea

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