Economic Evaluation of Large-Scale Offshore Wind Farm considering Wind Speed and Wind Turbine Capacity

2021 ◽  
Vol 70 (7) ◽  
pp. 953-960
Author(s):  
Won-Sik Moon ◽  
Joong-Woo Shin ◽  
Kwang-Hoon Yoon
Keyword(s):  
Economic Evaluation ◽  
Wind Speed ◽  
Wind Turbine ◽  
Large Scale ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Turbine Capacity

Techno-Economic Analysis and Planning for the Development of Large Scale Offshore Wind Farm in India

2020 ◽  
Vol 10 (2) ◽  
pp. 257-268
Author(s):  
Mohammad Mushir Riaz ◽  
Badrul Hasan Khan
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Large Scale ◽  
Wind Farm ◽  
Offshore Wind ◽  
Maintenance Cost ◽  
Offshore Wind Farm ◽  
Emission Analysis ◽  
Suitable Site ◽  
Power Curves

Despite India's great potential for offshore wind energy development, no offshore wind farm exists in the country. This study aims to plan a large scale offshore wind farm in the south coastal region of India. Seven potential sites were selected for the wind resource assessment study to choose the most suitable site for offshore wind farm development. An optimally matched wind turbine was also selected for each site using the respective power curves and wind speed characteristics. Weibull shape and scale parameters were estimated using WAsP, openwind, maximum likelihood (MLH), and least square regression (LSR) algorithms. The maximum energy-carrying wind speed and the most frequent wind speed were determined using these algorithmic methods. The correlation coefficient (R2) indicated the efficiency of these methods and showed that all four methods represented wind data at all sites accurately; however, openwind was slightly better than MLH, followed by LSR and WAsP methods. The coastal site, Zone-B with RE power 6.2 M152 wind turbine, was found to be the most suitable site for developing an offshore wind farm. Furthermore, the financial analysis that included preventive maintenance cost and carbon emission analysis was also done. Results show that it is feasible to develop a 430 MW wind farm in the region, zone B, by installing seventy RE power 6.2 M152 offshore wind turbines. The proposed wind farm would provide a unit price of Rs. 6.84 per kWh with a payback period of 5.9 years and, therefore, would be substantially profitable.

scholarly journals Recovery Processes in a Large Offshore Wind Farm

2021 ◽  
Author(s):  
Tanvi Gupta ◽  
Somnath Baidya Roy
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Mesoscale Model ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Recovery Processes ◽  
Mesoscale Processes

Abstract. Wind turbines in a wind farm extract energy from the atmospheric flow and convert it into electricity, resulting in a localized momentum deficit in the wake that reduces energy availability for downwind turbines. Atmospheric momentum convergence from above, below and sides into the wakes replenish the lost momentum, at least partially, so that turbines deep inside a wind farm can continue to function. In this study, we explore recovery processes in a hypothetical offshore wind farm with particular emphasis on comparing the spatial patterns and magnitudes of horizontal and vertical recovery processes and understanding the role of mesoscale processes in momentum recovery in wind farms. For this purpose, we use the Weather Research and Forecasting (WRF) model, a state-of-the-art mesoscale model equipped with a wind turbine parameterization, to simulate a hypothetical large offshore wind farm with different wind turbine spacings under realistic initial and boundary conditions. Results show that vertical turbulent transport of momentum from aloft is the main contributor to recovery in wind farms except in cases with strong background winds and high inter-turbine spacing where horizontal advective momentum transport can also contribute equally. Vertical recovery shows a systematic dependence on wind speed and wind farm density that can be quantified using low-order empirical equations. Wind farms significantly alter the mesoscale flow patterns, especially for densely packed wind farms under high wind speed conditions. In these cases, the mesoscale circulations created by the wind farms can transport high momentum air from aloft into the atmospheric boundary layer (ABL) and thus aid in recovery in wind farms. This is a novel study that is one of the first to look at wind farm replenishment processes under realistic meteorological conditions including the role of mesoscale processes. Overall, this study significantly advances our understanding of recovery processes in wind farms and wind farm-ABL interactions.

scholarly journals Dynamic Loads and Response of a Spar Buoy Wind Turbine with Pitch-Controlled Rotating Blades: An Experimental Study

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3598
Author(s):  
Sara Russo ◽  
Pasquale Contestabile ◽  
Andrea Bardazzi ◽  
Elisa Leone ◽  
Gregorio Iglesias ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Degrees Of Freedom ◽  
Large Scale ◽  
Laboratory Data ◽  
Nonlinear Behavior ◽  
Offshore Wind ◽  
Small Scale ◽  
Wave Steepness ◽  
Design Factor

New large-scale laboratory data are presented on a physical model of a spar buoy wind turbine with angular motion of control surfaces implemented (pitch control). The peculiarity of this type of rotating blade represents an essential aspect when studying floating offshore wind structures. Experiments were designed specifically to compare different operational environmental conditions in terms of wave steepness and wind speed. Results discussed here were derived from an analysis of only a part of the whole dataset. Consistent with recent small-scale experiments, data clearly show that the waves contributed to most of the model motions and mooring loads. A significant nonlinear behavior for sway, roll and yaw has been detected, whereas an increase in the wave period makes the wind speed less influential for surge, heave and pitch. In general, as the steepness increases, the oscillations decrease. However, higher wind speed does not mean greater platform motions. Data also indicate a significant role of the blade rotation in the turbine thrust, nacelle dynamic forces and power in six degrees of freedom. Certain pairs of wind speed-wave steepness are particularly unfavorable, since the first harmonic of the rotor (coupled to the first wave harmonic) causes the thrust force to be larger than that in more energetic sea states. The experiments suggest that the inclusion of pitch-controlled, variable-speed blades in physical (and numerical) tests on such types of structures is crucial, highlighting the importance of pitch motion as an important design factor.

Research of Large-Scale Offshore Wind Farm Collection System Short Circuit Equivalent Network

2013 ◽  
Vol 448-453 ◽  
pp. 1732-1737
Author(s):  
Liu Bin ◽  
Hong Wei Cui ◽  
Li Xu ◽  
Kun Wang ◽  
Zhu Zhan ◽  
...  
Keyword(s):  
Large Scale ◽  
Wind Farm ◽  
Short Circuit ◽  
Short Circuit Current ◽  
System Optimization ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Collection System ◽  
Medium Voltage ◽  
The Impact

This paper analyses the characteristics of large-scale offshore wind farm collection network and the impact of the medium voltage collection system optimization,while from the electrical technology point,it proposes the short circuit current of the collection network computational model and algorithms,based on the principle of equivalent circuit.Taking a wind power coolection system planned for a certain offshore wind farm planning for example, the validity of the model and algorithm is verified.

Fatigue Life Analysis of Offshore Wind Turbine Support Structures in an Offshore Wind Farm

2018 ◽  
Author(s):  
Bryan Nelson ◽  
Yann Quéméner
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
The Body ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Analysis Tool ◽  
Support Structures ◽  
Offshore Wind Farm ◽  
Actuator Disk

This study evaluated, by time-domain simulations, the fatigue lives of several jacket support structures for 4 MW wind turbines distributed throughout an offshore wind farm off Taiwan’s west coast. An in-house RANS-based wind farm analysis tool, WiFa3D, has been developed to determine the effects of the wind turbine wake behaviour on the flow fields through wind farm clusters. To reduce computational cost, WiFa3D employs actuator disk models to simulate the body forces imposed on the flow field by the target wind turbines, where the actuator disk is defined by the swept region of the rotor in space, and a body force distribution representing the aerodynamic characteristics of the rotor is assigned within this virtual disk. Simulations were performed for a range of environmental conditions, which were then combined with preliminary site survey metocean data to produce a long-term statistical environment. The short-term environmental loads on the wind turbine rotors were calculated by an unsteady blade element momentum (BEM) model of the target 4 MW wind turbines. The fatigue assessment of the jacket support structure was then conducted by applying the Rainflow Counting scheme on the hot spot stresses variations, as read-out from Finite Element results, and by employing appropriate SN curves. The fatigue lives of several wind turbine support structures taken at various locations in the wind farm showed significant variations with the preliminary design condition that assumed a single wind turbine without wake disturbance from other units.

scholarly journals Correlations of power output fluctuations in an offshore wind farm using high-resolution SCADA data

2021 ◽  
Vol 6 (4) ◽  
pp. 997-1014
Author(s):  
Janna Kristina Seifert ◽  
Martin Kraft ◽  
Martin Kühn ◽  
Laura J. Lukassen
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Power Output ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Flow Conditions ◽  
Output Fluctuations ◽  
Power Difference ◽  
Time Correlations

Abstract. Space–time correlations of power output fluctuations of wind turbine pairs provide information on the flow conditions within a wind farm and the interactions of wind turbines. Such information can play an essential role in controlling wind turbines and short-term load or power forecasting. However, the challenges of analysing correlations of power output fluctuations in a wind farm are the highly varying flow conditions. Here, we present an approach to investigate space–time correlations of power output fluctuations of streamwise-aligned wind turbine pairs based on high-resolution supervisory control and data acquisition (SCADA) data. The proposed approach overcomes the challenge of spatially variable and temporally variable flow conditions within the wind farm. We analyse the influences of the different statistics of the power output of wind turbines on the correlations of power output fluctuations based on 8 months of measurements from an offshore wind farm with 80 wind turbines. First, we assess the effect of the wind direction on the correlations of power output fluctuations of wind turbine pairs. We show that the correlations are highest for the streamwise-aligned wind turbine pairs and decrease when the mean wind direction changes its angle to be more perpendicular to the pair. Further, we show that the correlations for streamwise-aligned wind turbine pairs depend on the location of the wind turbines within the wind farm and on their inflow conditions (free stream or wake). Our primary result is that the standard deviations of the power output fluctuations and the normalised power difference of the wind turbines in a pair can characterise the correlations of power output fluctuations of streamwise-aligned wind turbine pairs. Further, we show that clustering can be used to identify different correlation curves. For this, we employ the data-driven k-means clustering algorithm to cluster the standard deviations of the power output fluctuations of the wind turbines and the normalised power difference of the wind turbines in a pair. Thereby, wind turbine pairs with similar power output fluctuation correlations are clustered independently from their location. With this, we account for the highly variable flow conditions inside a wind farm, which unpredictably influence the correlations.

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