Recovery processes in coastal wind farms

Author(s):  
Tanvi Gupta ◽  
Somnath Baidya Roy

<p>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 hypothetical offshore wind farms with particular emphasis on comparing the spatial patterns and magnitudes of horizontal and vertical recovery processes and understanding the role of mesoscale phenomena like sea breezes in momentum recovery in wind farms.</p><p>For this study, we use the Weather Research and Forecasting (WRF) model, a state-of-the-art mesoscale model equipped with a wind turbine parameterization, to simulate deep offshore and coastal wind farms with different wind turbine spacings under realistic initial and boundary conditions. The wind farms consist of 10000 turbines rated 3 MW spread over a 50 km x 50 km area. We conduct experiments with various background conditions, including low wind, high wind, and sea breeze cases identified using Borne’s method.</p><p>Results show that for deep offshore wind farms, power generation peaks at the upwind edge and monotonically decreases downwind into the interior due to cumulative wake effects of multiple rows of turbines. Vertical turbulent transport of momentum from aloft is the main contributor to recovery except in cases with strong background winds and high inter-turbine spacing where horizontal advective momentum transport can also contribute equally. Coastal wind farms behave similarly in the absence of sea-breezes.  However, under sea breeze conditions, the power production is high at the upwind edge and decreases thereafter but starts to increase again towards the downwind edge of the wind farm because of the sea breeze. The results further show that the contribution of horizontal (vertical) recovery in case of sea breeze conditions increases (decreases) to around 14% (86%) as compared to the non-sea breeze conditions where the horizontal (vertical) recovery contributes 9% (90%) to the momentum recovery in the wind farms. Vertical recovery shows a systematic dependence on wind farm density and wind speed. This relationship can be quantified using low-order empirical equations that can perhaps be used to develop parameterizations for replenishment in linear wake models. Overall, this study is likely to significantly advance our understanding of recovery processes in wind farms and wind farm-ABL interactions.</p>

2021 ◽  
Vol 56 ◽  
pp. 129-139
Author(s):  
Tanvi Gupta ◽  
Somnath Baidya Roy

Abstract. With the rapid growth in offshore wind energy, it is important to understand the dynamics of offshore wind farms. Most of the offshore wind farms are currently installed in coastal regions where they are often affected by sea-breezes. In this work, we quantitatively study the recovery processes for coastal wind farms under sea-breeze conditions. We use a modified Borne's method to identify sea breeze days off the west coast of India in the Arabian Sea. For the identified sea breeze days, we simulate a hypothetical wind farm covering 50×50 km2 area using the Weather Research and Forecasting (WRF) model driven by realistic initial and boundary conditions. We use three wind farm layouts with the turbines spaced 0.5, 1, and 2 km apart. The results show an interesting power generation pattern with a peak at the upwind edge and another peak at the downwind edge due to sea breeze. Wind farms affect the circulation patterns, but the effects of these modifications are very weak compared to the sea breezes. Vertical recovery is the dominant factor with more than half of the momentum extracted by wind turbines being replenished by vertical turbulent mixing. However, horizontal recovery can also play a strong role for sparsely packed wind farms. Horizontal recovery is stronger at the edges where the wind speeds are higher whereas vertical recovery is stronger in the interior of the wind farms. This is one of the first studies to examine replenishment processes in offshore wind farms under sea breeze conditions. It can play an important role in advancing our understanding wind farm-atmospheric boundary layer interactions.


2017 ◽  
Vol 2 (2) ◽  
pp. 603-614 ◽  
Author(s):  
Lukas Vollmer ◽  
Gerald Steinfeld ◽  
Martin Kühn

Abstract. The estimation of the cost of energy of offshore wind farms has a high uncertainty, which is partly due to the lacking accuracy of information on wind conditions and wake losses inside of the farm. Wake models that aim to reduce the uncertainty by modeling the wake interaction of turbines for various wind conditions need to be validated with measurement data before they can be considered as a reliable estimator. In this paper a methodology that enables a direct comparison of modeled with measured flow data is evaluated. To create the simulation data, a model chain including a mesoscale model, a large-eddy-simulation (LES) model and a wind turbine model is used. Different setups are compared to assess the capability of the method to reproduce the wind conditions at the hub height of current offshore wind turbines. The 2-day-long simulation of the ambient wind conditions and the wake simulation generally show good agreements with data from a met mast and lidar measurements, respectively. Wind fluctuations due to boundary layer turbulence and synoptic-scale motions are resolved with a lower representation of mesoscale fluctuations. Advanced metrics to describe the wake shape and development are derived from simulations and measurements but a quantitative comparison proves to be difficult due to the scarcity and the low sampling rate of the available measurement data. Due to the implementation of changing synoptic wind conditions in the LES, the methodology could also be beneficial for case studies of wind farm performance or wind farm control.


2021 ◽  
Author(s):  
Tanvi Gupta ◽  
Somnath Baidya Roy

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.


2020 ◽  
Vol 12 (14) ◽  
pp. 5761 ◽  
Author(s):  
Chakib El Mokhi ◽  
Adnane Addaim

Wind energy is currently one of the fastest-growing renewable energy sources in the world. For this reason, research on methods to render wind farms more energy efficient is reasonable. The optimization of wind turbine positions within wind farms makes the exploitation of wind energy more efficient and the wind farms more competitive with other energy resources. The investment costs alone for substation and electrical infrastructure for offshore wind farms run around 15–30% of the total investment costs of the project, which are considered high. Optimizing the substation location can reduce these costs, which also minimizes the overall cable length within the wind farm. In parallel, optimizing the cable routing can provide an additional benefit by finding the optimal grid network routing. In this article, the authors show the procedure on how to create an optimized wind farm already in the design phase using metaheuristic algorithms. Besides the optimization of wind turbine positions for more energy efficiency, the optimization methods of the substation location and the cable routing for the collector system to avoid cable losses are also presented.


2015 ◽  
Vol 8 (4) ◽  
pp. 3481-3522 ◽  
Author(s):  
P. J. H. Volker ◽  
J. Badger ◽  
A. N. Hahmann ◽  
S. Ott

Abstract. We describe the theoretical basis, implementation and validation of a new parametrisation that accounts for the effect of large offshore wind farms on the atmosphere and can be used in mesoscale and large-scale atmospheric models. This new parametrisation, referred to as the Explicit Wake Parametrisation (EWP), uses classical wake theory to describe the unresolved wake expansion. The EWP scheme is validated against filtered in situ measurements from two meteorological masts situated a few kilometres away from the Danish offshore wind farm Horns Rev I. The simulated velocity deficit in the wake of the wind farm compares well to that observed in the measurements and the velocity profile is qualitatively similar to that simulated with large eddy simulation models and from wind tunnel studies. At the same time, the validation process highlights the challenges in verifying such models with real observations.


2021 ◽  
Author(s):  
Morteza Bahadori ◽  
Hassan Ghassemi

Abstract In recent years, as more offshore wind farms have been constructed, the possibility of integrating various offshore renewable technologies is increased. Using offshore wind and solar power resources as a hybrid system provides several advantages including optimized marine space utilization, reduced maintenance and operation costs, and relieving wind variability on output power. In this research, both offshore wind and solar resources are analyzed based on accurate data through a case study in Shark Bay (Australia), where bathymetric information confirms using offshore bottom-fixed wind turbine regarding the depth of water. Also, the power production of the hybrid system of co-located bottom-fixed wind turbine and floating photovoltaic are investigated with the technical characteristics of commercial mono-pile wind turbine and photovoltaic panels. Despite the offshore wind, the solar energy output has negligible variation across the case study area, therefore using the solar platform in deep water is not an efficient option. It is demonstrated that the floating solar has a power production rate nearly six times more than a typical offshore wind farm with the same occupied area. Also, output energy and surface power density of the hybrid offshore windsolar system are improved significantly compared to a standalone offshore wind farm. The benefits of offshore wind and solar synergies augment the efficiency of current offshore wind farms throughout the world.


Author(s):  
Alexander Štrbac ◽  
Tanja Martini ◽  
Daniel H. Greiwe ◽  
Frauke Hoffmann ◽  
Michael Jones

AbstractThe use of offshore wind farms in Europe to provide a sustainable alternative energy source is now considered normal. Particularly in the North Sea, a large number of wind farms exist with a significant distance from the coast. This is becoming standard practice as larger areas are required to support operations. Efficient transport and monitoring of these wind farms can only be conducted using helicopters. As wind turbines continue to grow in size, there is a need to continuously update operational requirements for these helicopters, to ensure safe operations. This study assesses German regulations for flight corridors within offshore wind farms. A semi-empirical wind turbine wake model is used to generate velocity data for the research flight simulator AVES. The reference offshore wind turbine NREL 5 MW has been used and scaled to represent wind turbine of different sizes. This paper reports result from a simulation study concerning vortex wake encounter during offshore operations. The results have been obtained through piloted simulation for a transport case through a wind farm. Both subjective and objective measures are used to assess the severity of vortex wake encounters.


2020 ◽  
Vol 184 ◽  
pp. 01094
Author(s):  
C Lavanya ◽  
Nandyala Darga Kumar

Wind energy is the renewable sources of energy and it is used to generate electricity. The wind farms can be constructed on land and offshore where higher wind speeds are prevailing. Most offshore wind farms employ fixed-foundation wind turbines in relatively shallow water. In deep waters floating wind turbines have gained popularity and are recent development. This paper discusses the various types of foundations which are in practice for use in wind turbine towers installed on land and offshore. The applicability of foundations based on depth of seabed and distance of wind farm from the shore are discussed. Also, discussed the improvement methods of weak or soft soils for the foundations of wind turbine towers.


Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1960
Author(s):  
Hsing-Yu Wang ◽  
Hui-Ming Fang ◽  
Yun-Chih Chiang

In this study, a hydrodynamic model was used that includes the effects of wave–current interactions to simulate the wave and current patterns before and after offshore wind turbine installation in western Taiwan. By simulating the waves and currents after the offshore wind turbine was established, the waves and currents caused by the wind turbine were seen to have a limited range of influence, which is probably within an area about four to five times the size of the diameter (12–15 m) of the foundation structure. Overall, the analysis of the simulation results of the wave and current patterns after the offshore wind turbines were established shows that the underwater foundation only affected the local area near the pile structure. The wind farm (code E) of the research case can be equipped with about 720 cage cultures; if this is extended to other wind farms in the western sea area, it should be possible to produce economic-scale farming operations such as offshore wind power and fisheries. However, this study did not consider the future operation of the entire offshore wind farm. If the operation and maintenance of offshore wind farms are not affected, and if the consent of the developer is obtained, it should be possible to use this method to provide economically large-scale farming areas as a mutually beneficial method for offshore wind power generation and fisheries.


2017 ◽  
Vol 9 (6) ◽  
pp. 1461-1484 ◽  
Author(s):  
Long Wang ◽  
Guoping Chen ◽  
Tongguang Wang ◽  
Jiufa Cao

AbstractWith lower turbulence and less rigorous restrictions on noise levels, offshore wind farms provide favourable conditions for the development of high-tip-speed wind turbines. In this study, the multi-objective optimization is presented for a 5MW wind turbine design and the effects of high tip speed on power output, cost and noise are analysed. In order to improve the convergence and efficiency of optimization, a novel type of gradient-based multi-objective evolutionary algorithm is proposed based on uniform decomposition and differential evolution. Optimization examples of the wind turbines indicate that the new algorithm can obtain uniformly distributed optimal solutions and this algorithm outperforms the conventional evolutionary algorithms in convergence and optimization efficiency. For the 5MW wind turbines designed, increasing the tip speed can greatly reduce the cost of energy (COE). When the tip speed increases from 80m/s to 100m/s, under the same annual energy production, the COE decreases by 3.2% in a class I wind farm and by 5.1% in a class III one, respectively, while the sound pressure level increases by a maximum of 4.4dB with the class III wind farm case.


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