scholarly journals Evaluation of the impact of active wake control techniques on ultimate loads for a 10 MW wind turbine

2022 ◽  
Vol 7 (1) ◽  
pp. 1-17
Author(s):  
Alessandro Croce ◽  
Stefano Cacciola ◽  
Luca Sartori
Keyword(s):  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Control Techniques ◽  
Control Optimization ◽  
Cost Of Energy ◽  
The Individual ◽  
The Cost ◽  
Wind Statistics ◽  
The Impact

Abstract. Wind farm control is one of the solutions recently proposed to increase the overall energy production of a wind power plant. A generic wind farm control is typically synthesized so as to optimize the energy production of the entire wind farm by reducing the detrimental effects due to wake–turbine interactions. As a matter of fact, the performance of a farm control is typically measured by looking at the increase in the power production, properly weighted through the wind statistics. Sometimes, fatigue loads are also considered in the control optimization problem. However, an aspect which is rather overlooked in the literature on this subject is the evaluation of the impact that a farm control law has on the individual wind turbine in terms of maximum loads and dynamic response under extreme conditions. In this work, two promising wind farm controls, based on wake redirection (WR) and dynamic induction control (DIC) strategy, are evaluated at the level of a single front-row wind turbine. To do so, a two-pronged analysis is performed. Firstly, the control techniques are evaluated in terms of the related impact on some specific key performance indicators, with special emphasis on ultimate loads and maximum blade deflection. Secondarily, an optimal blade redesign process is performed with the goal of quantifying the modification in the structure of the blade entailed by a possible increase in ultimate values due to the presence of wind farm control. Such an analysis provides for an important piece of information for assessing the impact of the farm control on the cost-of-energy model.

scholarly journals Evaluation of the impact of wind farm control techniques on fatigue and ultimate loads

2020 ◽  
Author(s):  
Alessandro Croce ◽  
Stefano Cacciola ◽  
Luca Sartori ◽  
Paride De Fidelibus
Keyword(s):  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Dynamic Responses ◽  
Control Techniques ◽  
Cost Of Energy ◽  
The Individual ◽  
The Cost ◽  
The Impact ◽  
Do So

Abstract. Wind farm control is one of the solutions recently proposed to increase the overall energy production of a wind power plant. A generic wind farm control is typically synthesized so as to optimize the energy production of the entire wind farm by reducing the detrimental effects due to wake-turbine interactions. As a matter of fact, the performance of a farm control is typically measured by looking mainly at the increase of produced power, possibly weighted with the wind Weibull and rose at a specific place, and, sometimes, by looking also at the fatigue loads. However, an aspect which is rather overlooked is the evaluation of the impact that a farm control law has on the maximum loads and on the dynamic responses under extreme conditions of the individual wind turbine. In this work, two promising wind farm controls, based respectively on Wake Redirection (WR) and Dynamic Induction Control (DIC) strategy, are evaluated at a single wind turbine level. To do so, a two-pronged analysis is performed. Firstly, the control techniques are evaluated in terms of the related impact on some specific key performance indicators (e.g. fatigue and ultimate loads, actuator duty cycle and annual energy production). Secondarily, an optimal blade redesign process, which takes into account the presence of the wind farm control, is performed with the goal of quantifying the possible modification in the structure of the blade and hence of quantifying the impact of the control on the Cost of Energy model.

A Techno-Economic Analysis of a Proposed 1.5 MW Wind Turbine With a Hydrostatic Drive Train

2009 ◽  
Author(s):  
James R. Browning ◽  
Jon G. McGowan ◽  
James F. Manwell
Keyword(s):  
Wind Turbine ◽  
Energy Production ◽  
Capital Cost ◽  
Performance Model ◽  
Drive Train ◽  
Cost Models ◽  
Initial Capital ◽  
Cost Of Energy ◽  
The Cost ◽  
Utility Scale

Although decreases in the cost of energy from utility scale wind turbine generators has made them competitive with conventional forms of utility power generation, further reductions can increase the presence of wind energy in the global energy mix. The cost of energy from a wind turbine can be reduced by increasing the annual energy production, reducing the initial capital cost of the turbine, or doing both. In this study, the cost of energy is estimated for a theoretical 1.5 MW wind turbine utilizing a continuously variable ratio hydrostatic drive train between the rotor and the generator. The estimated cost of energy is then compared to that of a conventional wind turbine of equivalent rated power. The annual energy production is estimated for the theoretical hydrostatic turbine using an assumed wind speed distribution and a turbine power curve resulting from a steady state performance model of the turbine. The initial capital cost of the turbine is estimated using cost models developed for various components unique to the hydrostatic turbine as well as economic parameters and models developed by the National Renewable Energy Lab (NREL) for their 2004 WindPACT advanced wind turbine drive train study. The resulting cost of energy, along with various performance characteristics of interest, are presented and compared to those of the WindPACT baseline turbine intended to represent a conventional utility scale wind turbine.

scholarly journals Integrated wind farm layout and control optimization

2020 ◽  
Author(s):  
Mads M. Pedersen ◽  
Gunner C. Larsen
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Design Space ◽  
Wind Farm Layout ◽  
Control Optimization ◽  
Mean Wind Speed ◽  
The Individual ◽  
And Control ◽  
Selection Of

Abstract. Design of an optimal wind farm topology and wind farm control scheduling depends on the chosen metric. The objective of this paper is to investigate the influence of optimal wind farm control on the optimal wind farm layout in terms of power production. A successful fulfilment of this goal requires: 1) an accurate and fast flow model; 2) selection of the minimum set of design parameters that rules the problem; and 3) selection of an optimization algorithm with good scaling properties. For control of the individual wind farm turbines, the two most obvious strategies are wake steering based on active wind turbine yaw control and wind turbine derating. The present investigation is a priori limited to wind turbine derating. A high-speed linearized CFD RANS solver models the flow field and the crucial wind turbine wake interactions inside the wind farm. The actuator disk method is used to model the wind turbines, and utilizing an aerodynamic model, the design space of the optimization problem is reduced to only three variables per turbine – two geometric and one carefully selected variable specifying the individual wind turbine derating setting for each mean wind speed and direction. The full design space spanned by these (2N + Nd Ns N) parameters, where N is the number of wind farm turbines, Nd is the number of direction bins, and Ns is the number of mean wind speed bins. This design space is decomposed in two subsets, which in turn define a nested set of optimization problems to achieve the fastest possible optimization procedure. Following a simplistic sanity check of the platform functionality regarding wind farm layout and control optimization, the capabilities of the developed optimization platform is demonstrated on the Swedish offshore wind farm. For this particular wind farm, the analysis demonstrates that the expected annual energy production can be increased by 4 % by integrating the wind farm control in the design of the wind farm layout, which is 1.2 % higher than what is achieved by optimizing the layout only.

scholarly journals Integrated wind farm layout and control optimization

2020 ◽  
Vol 5 (4) ◽  
pp. 1551-1566
Author(s):  
Mads M. Pedersen ◽  
Gunner C. Larsen
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Design Space ◽  
Wind Farm Layout ◽  
Control Optimization ◽  
Mean Wind Speed ◽  
The Individual ◽  
Full Design ◽  
And Control ◽  
Selection Of

Abstract. The objective of this paper is to investigate the joint optimization of wind farm layout and wind farm control in terms of power production. A successful fulfilment of this goal requires the following: (1) an accurate and fast flow model, (2) selection of the minimum set of design parameters that rules or governs the problem, and (3) selection of an optimization algorithm with good scaling properties. For control of the individual wind farm turbines with the aim of wind farm production optimization, the two most obvious strategies are wake steering based on active wind turbine yaw control and wind turbine derating. The present investigation is limited to wind turbine derating. A high-speed linearized computational fluid dynamics (CFD) Reynolds-averaged Navier–Stokes (RANS) solver models the flow field and the crucial wind turbine wake interactions inside the wind farm. The actuator disc method is used to model the wind turbines, and utilizing an aerodynamic model, the design space of the optimization problem is reduced to only three variables per turbine – two geometric and one carefully selected variable specifying the individual wind turbine derating setting for each mean wind speed and direction. The full design space is spanned by these (2N+NdNsN) parameters, where N is the number of wind farm turbines, Nd is the number of direction bins, and Ns is the number of mean wind speed bins. This design space is decomposed into two subsets, which in turn define a nested set of optimization problems to achieve a significantly faster optimization procedure compared to a direct optimization based on the full design space. Following a simplistic sanity check of the platform functionality regarding wind farm layout and control optimization, the capability of the developed optimization platform is demonstrated on a Swedish offshore wind farm. For this particular wind farm, the analysis demonstrates that the expected annual energy production can be increased by 4 % by integrating the wind farm control into the design of the wind farm layout, which is 1.2 % higher than what is achieved by optimizing the layout only.

scholarly journals Comparison between upwind and downwind designs of a 10 MW wind turbine rotor

2018 ◽  
Author(s):  
Pietro Bortolotti ◽  
Abinhav Kapila ◽  
Carlo L. Bottasso
Keyword(s):  
Wind Turbine ◽  
Energy Production ◽  
Turbine Rotor ◽  
Design Tool ◽  
Operating Conditions ◽  
Cost Of Energy ◽  
Potential Benefits ◽  
The Cost ◽  
Interesting Alternative ◽  
Wind Turbine Rotor

Abstract. The size of wind turbines has been steadily growing in the pursuit of a lower cost of energy by an increased wind capture. In this trend, the vast majority of wind turbine rotors has been designed based on the conventional three-bladed upwind concept. This paper aims at assessing the optimality of this configuration with respect to a three-bladed downwind design, with and without an actively controlled variable coning used to reduce the cantilever loading of the blades. A 10 MW wind turbine is used for the comparison of the various design solutions, which are obtained by an automated comprehensive aerostructural design tool. Results show that, for this turbine size, downwind rotors lead to blade mass and cost reductions of 6 % and 2 %, respectively, compared to equivalent upwind configurations. Due to a more favorable rotor attitude, the annual energy production of downwind rotors may also slightly increase in complex terrain conditions characterized by a wind upflow, leading to an overall reduction in the cost of energy. However, in more standard operating conditions, upwind rotors return the lowest cost of energy. Finally, active coning is effective in alleviating loads by reducing both blade mass and cost, but these potential benefits are negated by an increased system complexity and reduced energy production. In summary, a conventional design appears difficult to beat even at these turbine sizes, although a downwind non-aligned configuration might result in an interesting alternative.

Optimizing the Layout of Offshore Wind Energy Systems

2008 ◽  
Vol 42 (2) ◽  
pp. 19-27 ◽  
Author(s):  
Christopher N. Elkinton ◽  
James F. Manwell ◽  
Jon G. McGowan
Keyword(s):  
Wind Energy ◽  
Energy Production ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Energy ◽  
Offshore Wind Farm ◽  
Wind Farm Layout ◽  
Trade Offs ◽  
Cost Of Energy ◽  
The Cost

Offshore wind energy technology is a reality in Europe and is poised to make a significant contribution to the U.S. energy supply in the near future as well. The layout of an offshore wind farm is a complex problem involving many trade-offs. For example, energy production increases with turbine spacing, as do electrical costs and losses. Energy production also increases with distance from shore, but so do O&M (operations and maintenance), foundation, transmission, and installation costs. Determining which of these factors dominates requires a thorough understanding of the physics behind these trade-offs, can lead to the optimal layout, and helps lower the cost of energy from these farms. This paper presents the results of a study carried out to investigate these trade-offs and to develop a method for optimizing the wind farm layout during the micrositing phase of an offshore wind energy system design. It presents a method for analyzing the cost of energy from offshore wind farms as well as a summary of the development of an offshore wind farm layout optimization tool. In addition to an initial validation of the optimization tool, an example of the use of this tool for the design of an offshore wind farm in Hull, Massachusetts, is also given.

scholarly journals Objectives and Constraints for Wind Turbine Optimization

2014 ◽  
Vol 136 (4) ◽  
Author(s):  
S. Andrew Ning ◽  
Rick Damiani ◽  
Patrick J. Moriarty
Keyword(s):  
Wind Turbine ◽  
Energy Production ◽  
Optimization Problems ◽  
Large Fraction ◽  
High Fidelity ◽  
Variable Diameter ◽  
Cost Of Energy ◽  
Physics Modeling ◽  
The Cost ◽  
Structural Metrics

Efficient extraction of wind energy is a complex, multidisciplinary process. This paper examines common objectives used in wind turbine optimization problems. The focus is not on the specific optimized designs, but rather on understanding when certain objectives and constraints are necessary, and what their limitations are. Maximizing annual energy production, or even using sequential aero/structural optimization, is shown to be significantly suboptimal compared to using integrated aero/structural metrics. Minimizing the ratio of turbine mass to annual energy production can be effective for fixed rotor diameter designs, as long as the tower mass is estimated carefully. For variable-diameter designs, the predicted optimal diameter may be misleading. This is because the mass of the tower is a large fraction of the total turbine mass, but the cost of the tower is a much smaller fraction of overall turbine costs. Minimizing the cost of energy is a much better metric, though high fidelity in the cost modeling is as important as high fidelity in the physics modeling. Furthermore, deterministic cost of energy minimization can be inadequate, given the stochastic nature of the wind and various uncertainties associated with physical processes and model choices. Optimization in the presence of uncertainty is necessary to create robust turbine designs.

scholarly journals Tourist Viewshed Externalities and Wind Energy Production

2017 ◽  
Vol 46 (2) ◽  
pp. 224-241 ◽  
Author(s):  
Jacob R. Fooks ◽  
Kent D. Messer ◽  
Joshua M. Duke ◽  
Janet B. Johnson ◽  
Tongzhe Li ◽  
...  
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Production ◽  
Hotel Room ◽  
Negative Effect ◽  
The Impact ◽  
Large Wind

This study uses an experiment where ferry passengers are sold hotel room “views” to evaluate the impact of wind turbines views on tourists’ vacation experience. Participants purchase a chance for a weekend hotel stay. Information about the hotel rooms was limited to the quality of the hotel and its distance from a large wind turbine, as well as whether or not a particular room would have a view of the turbine. While there was generally a negative effect of turbine views, this did not hold across all participants, and did not seem to be effected by distance or hotel quality.

Evaluating the effect of climate variation on the cost efficiency of a crop permit policy in Southern Sweden

2013 ◽  
Vol 4 (2) ◽  
pp. 110-117
Author(s):  
Dennis Collentine ◽  
Holger Johnsson
Keyword(s):  
Cost Efficiency ◽  
Agricultural Sector ◽  
Policy Design ◽  
Correlation Coefficients ◽  
Nitrogen Loads ◽  
Weather Variation ◽  
The Baltic ◽  
The Individual ◽  
The Cost ◽  
The Impact

Current international agreements call for a significant reduction of nitrogen loads to the Baltic Sea. New measures to reduce nitrogen loads from the agricultural sector and an increased focus on cost efficiency will be needed to meet reduction targets. For policy design and evaluation it is important to understand the impact of weather on the efficiency of abatement measures. One new proposed policy is the use of crop permits based on weather normalized average leaching. This paper describes the use of the Spearman method to determine the efficiency of this policy with annual weather variation. The conclusion is that the values of the Spearman correlation coefficients in the study indicate that using average leaching for the individual crops on specific soil types for calculating crop permit requirements is an efficient policy. The Spearman method is demonstrated to be a simple useful tool for evaluating the impact of weather and is recommended for use in new studies.

scholarly journals Inter-annual variability of wind climates and wind turbine annual energy production

2018 ◽  
Author(s):  
Sara C. Pryor ◽  
Tristan J. Shepherd ◽  
Rebecca J. Barthelmie
Keyword(s):  
Standard Deviation ◽  
Wind Energy ◽  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Speeds ◽  
Annual Variability ◽  
Eastern Usa

Abstract. Inter-annual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in pre-construction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derives in part from variability in wind climates. However, the magnitude of IAV in wind speeds at/close to wind turbine hub-heights is poorly constrained and maybe overestimated by the 6 % standard deviation of annual mean wind speeds that is widely applied within the wind energy industry. Thus there is a need for improved understanding of the long-term wind resource and the inter-annual variability therein in order to generate more robust predictions of the financial value of a wind energy project. Long-term simulations of wind speeds near typical wind turbine hub-heights over the eastern USA indicate median gross capacity factors (computed using 10-minute wind speeds close to wind turbine hub-heights and the power curve of the most common wind turbine deployed in the region) that are in good agreement with values derived from operational wind farms. The IAV of annual mean wind speeds at/near to typical wind turbine hub-heights in these simulations is lower than is implied by assuming a standard deviation of 6 %. Indeed, rather than in 9 in 10 years exhibiting AEP within 0.9 and 1.1 times the long-term mean AEP, results presented herein indicate that over 90 % of the area in the eastern USA that currently has operating wind turbines simulated AEP lies within 0.94 and 1.06 of the long-term average. Further, IAV of estimated AEP is not substantially larger than IAV in mean wind speeds. These results indicate it may be appropriate to reduce the IAV applied to pre-construction AEP estimates to account for variability in wind climates, which would decrease the cost of capital for wind farm developments.

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