scholarly journals Impact of Electrical Topology, Capacity Factor and Line Length on Economic Performance of Offshore Wind Investments

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3191 ◽  
Author(s):  
Sadik Kucuksari ◽  
Nuh Erdogan ◽  
Umit Cali
Keyword(s):  
Sensitivity Analysis ◽  
Transmission Line ◽  
Economic Performance ◽  
Wind Farm ◽  
Line Length ◽  
Capacity Factor ◽  
Offshore Wind ◽  
Farm Size ◽  
Energy Yield ◽  
Levelized Cost Of Electricity

In this study, an economic performance assessment of offshore wind investments is investigated through electrical topology, capacity factor and line length. First, annual energy yield production and electrical system losses for AC and DC offshore wind configurations are estimated by using Weibull probability distributions of wind speed. A cost model for calculating core energy economic metrics for offshore wind environment is developed by using a discount cash flow analysis. A case study is then conducted for a projected offshore wind farm (OWF) rated 100 MW and 300 MW sizes situated in the Aegean sea. Finally, a sensitivity analysis is performed for AC and DC OWFs with three different capacity factors (e.g., 45%, 55% and 60%) and various transmission line lengths ranging from 20 km to 120 km. The OWF is found to be economically viable for both AC and DC configurations with the estimated levelized cost of electricity (LCOE) ranging from 88.34 $/MWh to 113.76 $/MWh and from 97.61 $/MWh to 126.60 $/MWh, respectively. LCOEs for both options slightly change even though the wind farm size was increased three-fold. The sensitivity analysis reveals that, for further offshore locations with higher capacity factors, the superiority of AC configuration over the DC option in terms of LCOE reduces while the advantage of DC configuration over the AC option in terms of electrical losses is significant. Losses in the AC and DC configurations range from 3.75% to 5.86% and 3.75% to 5.34%, respectively, while LCOEs vary between 59.90 $/MWh and 113.76 $/MWh for the AC configuration and 66.21 $/MWh and 124.15 $/MWh for the DC configuration. Capacity factor was found to be more sensitive in LCOE estimation compared to transmission line length while line length is more sensitive in losses estimation compared to capacity factor.

Assessment of levelized cost of electricity of offshore wind energy in Egypt

2017 ◽  
Vol 41 (3) ◽  
pp. 160-173 ◽  
Author(s):  
Suzan Abdelhady ◽  
Domenico Borello ◽  
Ahmed Shaban
Keyword(s):  
Wind Energy ◽  
Mediterranean Sea ◽  
Energy Production ◽  
Capacity Factor ◽  
Offshore Wind ◽  
Offshore Wind Energy ◽  
Levelized Cost Of Electricity ◽  
Cost Of Electricity ◽  
Levelized Cost ◽  
The Mediterranean

Offshore wind turbines are being used to harness the high value of wind energy usually available on the sea sufficiently far from the shore (i.e. some kilometers). The present study provides an assessment of the potential of offshore wind energy along the Mediterranean Sea in Egypt. The techno-economic assessment was conducted considering a 7.0 MW offshore wind turbine at seven sites along the Mediterranean Sea. Fixed platforms were considered, assuming that the maximum sea depth will be 60 m, that is representative of the sea depth in the Mediterranean coast of Egypt at 5 km from the shore. The analysis reveals that a very large amount of energy can be harvested. The minimum energy production is obtained at Alexandria with a capacity factor of 55%, and the maximum energy production is obtained at El Dabaa station with a capacity factor of 63%. The levelized cost of electricity (LCOE) is estimated as to be equal to about 0.075–0.079 US$/kWh which can be considered very competitive with other renewable energy systems in Egypt. The results prove the techno-economic feasibility of the offshore wind energy resource in Egypt, and it would motivate both the research community and the policy makers for more attention regarding this resource.

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.

Floating Axis Wind and Water Turbine for High Utilization of Sea Surface Area: Design of Sub-Megawatt Prototype Turbine

2013 ◽  
Author(s):  
Takuju Nakamura ◽  
Kentaro Mizumukai ◽  
Hiromichi Akimoto ◽  
Yutaka Hara ◽  
Takafumi Kawamura
Keyword(s):  
Surface Area ◽  
Economic Performance ◽  
Wind Farm ◽  
Wind Farms ◽  
Sea Surface ◽  
Offshore Wind ◽  
Water Current ◽  
Additional Energy ◽  
Fishing Activity ◽  
Current Turbine

Paradoxically, sea surface area for offshore wind farms is limited in some countries like Japan. While the distance from the shore to a wind farm is limited due to the cost of electric transmission, the near shore area has considerable traffic of ships and is restricted by complex rights of local fisheries. One approach to the problem is inviting the local fishermen to the management of the wind farm. It requires higher economic performance of the wind farm than the original fishing activity in the same sea surface area. The proposed concept is the combination of a floating wind turbine and counter-rotating water current turbine. The water current turbine partially cancels the reaction torque of electric generator and provides additional energy production from water current. The rotating axis of the turbine is not fixed in the upright position to reduce the size of supporting structure. Regular maintenance work is only in low altitude on the float. These features lead to the reduction of O&M costs and higher utilization of sea surface area. This paper describes the prototype sub-megawatt turbine under construction and its expected economic performance.

scholarly journals 3-D shear-layer model for the simulation of multiple wind turbine wakes: description and first assessment

2017 ◽  
Vol 2 (2) ◽  
pp. 569-586 ◽  
Author(s):  
Davide Trabucchi ◽  
Lukas Vollmer ◽  
Martin Kühn
Keyword(s):  
Wind Turbine ◽  
Shear Layer ◽  
Wind Farm ◽  
Wind Farms ◽  
Theoretical Background ◽  
Offshore Wind ◽  
Energy Yield ◽  
Main Concern ◽  
Layer Model ◽  
New Model

Abstract. The number of turbines installed in offshore wind farms has strongly increased in the last years and at the same time the need for more precise estimations of the wind farm efficiency too. In this sense, the interaction between wakes has become a relevant aspect for the definition of a wind farm layout, for the assessment of its annual energy yield and for the evaluation of wind turbine fatigue loads. For this reason, accurate models for multiple overlapping wakes are a main concern of the wind energy community. Existing engineering models can only simulate single wakes, which are superimposed when they are interacting in a wind farm. This method is a practical solution, but it is not fully supported by a physical background. The limitation to single wakes is given by the assumption that the wake is axisymmetric. As an alternative, we propose a new shear-layer model that is based on the existing engineering wake models but is extended to also simulate non-axisymmetric wakes. In this paper, we present the theoretical background of the model and four application cases. We evaluate the new model for the simulation of single and multiple wakes using large-eddy simulations as reference. In particular, we report the improvements of the new model predictions in comparison to a sum-of-squares superposition approach for the simulation of three interacting wakes. The lower deviation from the reference considering single and multiple wakes encourages the further development of the model and promises a successful application for the simulation of wind farm flows.

scholarly journals An Ocean of Promise

2017 ◽  
Vol 139 (04) ◽  
pp. 30-35
Author(s):  
Dan Ferber
Keyword(s):  
Supply Chain ◽  
Financial Risk ◽  
Wind Farm ◽  
The United States ◽  
Offshore Wind ◽  
Levelized Cost Of Electricity ◽  
Offshore Wind Power ◽  
Financing Costs ◽  
Technical Innovations ◽  
The Cost

This article reviews the growth of the wind industry and the need for engineering expertise and technical innovations for it. Establishing an offshore wind supply chain would spur the development of better ways to manufacture turbine parts, ship them to sea, assemble them, and maintain them. This could create jobs for engineers of all stripes, including civil, electrical, and mechanical engineers. As the offshore wind power industry grows, costs continue to fall, in part because engineers in the industry are developing better and cheaper technologies. The article also highlights that by guaranteeing large and sustained markets for offshore wind, policies can entice large turbine vendors, blade manufacturers, and other major offshore wind vendors to bid on more US projects. After investigating conditions in the industry in Europe and the United States, a research team reported in early 2015 that put-in-place policies to reduce the cost and financial risk of building an offshore wind farm could slash project financing costs and ultimately cut the levelized cost of electricity by 50%. Experience and better logistics are making the European offshore wind supply chain more efficient.

A consideration on loss characteristics and annual capacity factor of offshore wind farm

2012 ◽  
Author(s):  
Naoya Inaba ◽  
Rion Takahashi ◽  
Junji Tamura ◽  
Mamoru Kimura ◽  
Akiyoshi Komura ◽  
...  
Keyword(s):  
Wind Farm ◽  
Capacity Factor ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Annual Capacity

Analysis of Wind Turbine Capacity Factor Improvement by Correcting Yaw Error Using LIDAR

2017 ◽  
Author(s):  
Roozbeh Bakhshi ◽  
Peter Sandborn
Keyword(s):  
Energy Production ◽  
Wind Farm ◽  
Production Capacity ◽  
Wind Farms ◽  
Power Production ◽  
Capacity Factor ◽  
Offshore Wind ◽  
The Common ◽  
Turbine Capacity ◽  
The Cost

Yaw error is the angle between a turbine’s rotor central axis and the wind flow. The presence of yaw error results in lower power production from turbines. Yaw error also puts extra loads on turbine components, which in turn, lowers their reliability. In this study we develop a stochastic model to calculate the average capacity factor of a 50 turbine offshore wind farm and investigate the effects of minimizing the yaw error on the capacity factor. In this paper, we define the capacity factor in terms of energy production, which is consistent with the common practice of wind farms (rather than the power production capacity factor definition that is used in textbooks and research articles). The benefit of using the energy production is that it incorporates both the power production improvements and downtime decreases. For minimizing the yaw error, a nacelle mounted LIDAR is used. While the LIDAR is on a turbine, it collects wind speed and direction data for a period of time, which is used to calculate a correction bias for the yaw controller of the turbine, then it will be moved to another turbine in the farm to perform the same task. The results of our investigation shows that although the improvements of the capacity factor are less than the theoretical values, the extra income from the efficiency improvements is larger than the cost of the LIDAR.

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