Optimization Study of Machine Parameters for 10-MW Salient-Pole Wind Turbine HTS Generators

Purpose Wind turbines are one of the best candidates to solve the problem of increasing energy demand in the world. The aim of this paper is to apply a multi-objective structural optimization study to a Phase II wind turbine blade produced by the National Renewable Energy Laboratory to obtain a more efficient small-scale wind turbine. Design/methodology/approach To solve this structural optimization problem, a new Non-Dominated Sorting Genetic Algorithm (NSGA-II) was performed. In the optimization study, the objective function was on minimization of mass and cost of the blade, and design parameters were composite material type and spar cap layer number. Design constraints were deformation, strain, stress, natural frequency and failure criteria. ANSYS Composite PrepPost (ACP) module was used to model the composite materials of the blade. Moreover, fluid–structure interaction (FSI) model in ANSYS was used to carry out flow and structural analysis on the blade. Findings As a result, a new original blade was designed using the multi-objective structural optimization study which has been adapted for aerodynamic optimization, the NSGA-II algorithm and FSI. The mass of three selected optimized blades using carbon composite decreased as much as 6.6%, 11.9% and 14.3%, respectively, while their costs increased by 23.1%, 29.9% and 38.3%. This multi-objective structural optimization-based study indicates that the composite configuration of the blade could be altered to reach the desired weight and cost for production. Originality/value ACP module is a novel and advanced composite modeling technique. This study is a novel study to present the NSGA-II algorithm, which has been adapted for aerodynamic optimization, together with the FSI. Unlike other studies, complex composite layup, fiber directions and layer orientations were defined by using the ACP module, and the composite blade analyzed both aerodynamic pressure and structural design using ACP and FSI modules together.

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Optimization Study of Shrouded Horizontal Axis Wind Turbine

2018 Wind Energy Symposium ◽

10.2514/6.2018-0996 ◽

2018 ◽

Cited By ~ 4

Author(s):

Tariq A. Khamlaj ◽

Markus Rumpfkeil

Keyword(s):

Wind Turbine ◽

Horizontal Axis ◽

Horizontal Axis Wind Turbine ◽

Optimization Study

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Structural optimization study of composite wind turbine blade

Materials & Design (1980-2015) ◽

10.1016/j.matdes.2012.10.036 ◽

2013 ◽

Vol 46 ◽

pp. 247-255 ◽

Cited By ~ 36

Author(s):

Jin Chen ◽

Quan Wang ◽

Wen Zhong Shen ◽

Xiaoping Pang ◽

Songlin Li ◽

...

Keyword(s):

Structural Optimization ◽

Wind Turbine ◽

Turbine Blade ◽

Wind Turbine Blade ◽

Optimization Study

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Optimization study of a catenary mooring system for a spar floating wind turbine based on its hydrodynamic responses

Proceedings of the Institution of Mechanical Engineers Part M Journal of Engineering for the Maritime Environment ◽

10.1177/1475090220917812 ◽

2020 ◽

pp. 147509022091781

Author(s):

Shima Tafazzoli ◽

Rouzbeh Shafaghat ◽

Rezvan Alamian

Keyword(s):

Wind Turbine ◽

Degrees Of Freedom ◽

Wave Spectrum ◽

Heuristic Method ◽

Prototype Model ◽

Mooring System ◽

The Caspian Sea ◽

Irregular Wave ◽

Optimization Study ◽

Proper Behavior

In this article, selecting an appropriate mooring system for the spar platform of a wind turbine consisting of chain–cable–chain is investigated based on a meta-heuristic method. A boundary element software is applied to hydrodynamics analysis, and the numerical results are verified by experimental results. According to the characteristics of the experimental mooring system, an appropriate chain is selected for the prototype model, and then a mooring system consisting of chain–cable–chain replaces the chain-based mooring system. Environmental forces have been applied by the conditions of the Caspian Sea. Analysis is done in time domain for irregular wave spectrum of Joint North Sea Wave Project. For the cable in the middle, seven lengths in the range of 30–210 m were considered. The simulations showed that in the cable length of 180 m, the structure exhibits a proper behavior. Also, in order to increase the reliability of the anchor, a portion of the initial chain was reduced and was added to the anchor chain; for this purpose, five different chain lengths from 25 to 65 m have been considered. The results show that for the heave, roll, pitch, and yaw degrees of freedom, the minimum structure oscillation happens in the length of 25 m, finally considering the proper behavior of the structure in the length of 25 m; this length of chain was added to the anchor chain.

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A new three-dimensional wake model for the real wind farm layout optimization

Energy Exploration & Exploitation ◽

10.1177/01445987211056989 ◽

2021 ◽

pp. 014459872110569

Author(s):

Zhaohui Luo ◽

Wei Luo ◽

Junhang Xie ◽

Jian Xu ◽

Longyan Wang

Keyword(s):

Wind Turbine ◽

Power Output ◽

Wind Farm ◽

Three Dimensional ◽

Wind Condition ◽

Wind Farm Layout ◽

Wind Farm Layout Optimization ◽

Optimization Study ◽

Wake Model

The utilization of wind energy has attracted extensive attentions in the last few decades around the world, providing a sustainable and clean source to generate electricity. It is a common phenomenon of wake interference among wind turbines and hence the optimization of wind farm layout is of great importance to improve the wind turbine yields. More specifically, the accuracy of the three-dimensional wake model is critical to the optiamal design of a real wind farm layout considering the combinatorial effect of wind turbine interaction and topography. In this paper, a novel learning-based three-dimensional wake model is proposed and subsequently validated by comparison to the high-fidelity wake simulation results. Moreover, due to the fact that the inevitable deviation of actual wind scenario from the anticipated one can greatly jeopardize the wind farm optimization outcome, the inaccuracy of wind condition prediction using the existing meteorologic data with limited-time measurement is incorporated into the optimization study. Different scenarios including short-, medium-, and long-term wind data are studied specifically with the wind speed/direction prediction errors of [Formula: see text] 0.25 m/s, [Formula: see text] 5.62 [Formula: see text], [Formula: see text] 0.08 m/s, [Formula: see text] 1.75 [Formula: see text] and [Formula: see text] 0.025 m/s, [Formula: see text] 0.56 [Formula: see text], respectively. An advanced objective function which simultaneously maximizes the power output and minimizes the power variance is employed for the optimization study. Through comparison, it is found that the optimized wind farm layout yields over 210 kW more total power output on average than the existed wind farm layout, which verifies the effectiveness of the wind farm layout optimization tool. The results show that as the measurement time for predicting the wind condition gets longer, the total wind farm power output average increases while the error of power output prediction decreases. For the wind farm with 20 wind turbines installed, the individual power output is above 500 kW with an error of 90 kW under the short-term wind [Formula: see text] 0.25 m/s, [Formula: see text] 5.62 [Formula: see text], while it is above 530 kW with an error of 10 kW under the long-term wind [Formula: see text] 0.025 m/s, [Formula: see text] 0.56 [Formula: see text].

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