低风速风电机组风轮气动优化设计及优化控制研究

发布时间：2018-06-29 01:04

本文选题：低风速风电机组 + 风轮　；参考：《华北电力大学》2014年博士论文

【摘要】：随着规模化风电产业的不断发展,陆上常规较高风速以上风能资源的开发利用技术已接近成熟,开发低风速风能资源逐渐成为一个新的研究方向,低风速风能开发对扩大风能利用范围及补充化石能源短缺现状具有重要意义。低风速风能开发利用的核心在于风电机组对低风速风能的捕获效率,研究低风速风电机组叶片翼型优化、风轮气动性能优化,对提升低风速风能转换效率、降低机组成本、均衡机组载荷起到关键作用。本课题在国家科技支撑项目“5.0MW双馈式变速恒频近海风电机组整机设计、集成及示范(2009BAA22B02)”的资助下,围绕低风速风电机组风轮气动优化设计和机组优化控制方法、理论及关键技术开展了如下主要研究工作： (1)基于叶片气动设计理论和遗传算法优化理论,应用遗传算法优化叶片翼型参数,以中低风速风电机组叶片翼型为优化基准翼型,翼型升阻比为优化适应值函数,叶片上下表面的几何控制参数为翼型优化设计变量,经过遗传进化,获得了低风速风电机组叶片优化翼型系列。与基准翼型相比,优化翼型具有较高的升阻比和更大的升力系数。 (2)基于Navier-Stokes方程的数值模拟方法,应用GAMBIT和FLUENT软件对优化翼型进行流场数值模拟,研究优化翼型的气动性能,包括翼型周围压力分布、速度分布、升阻力系数,数值分析结果验证了优化翼型的有效性。 (3)基于叶素-动量理论,应用遗传算法优化叶片气动设计,以风能利用系数变量dCpmax为优化目标函数,弦长和扭角分布函数系数为叶片优化设计变量,经过遗传进化,获得了低风速风电叶片气动优化模型,并基于该叶片,应用GH Bladed软件,构建3MW低风速风轮动力学模型,分析计算风轮气动性能,结果表明,低风速风电机组风轮具有更高的效率和更宽的高效率区,推力载荷较小,验证了叶片气动优化的有效性。 (4)将模糊控制应用于双馈风电机组最大功率捕获和动态载荷控制,在GHBladed软件环境构建3MW低风速风电机组数学模型,设计转速模糊控制器和机组动态载荷模糊控制器,并进行动态仿真,结果显示应用模糊控制能使风电机组有效捕获最大功率和控制动态载荷。构建了一个基于dSACE控制系统的双馈风电机组在环测试平台,在环测试研究采用模糊控制的双馈风电机组性能,实验结果进一步验证了模糊控制在非线性时变的风电机组系统控制上的显著优点。
[Abstract]:With the continuous development of the large-scale wind power industry, the development and utilization technology of wind energy resources above the conventional high wind speed on land is close to maturity. The development of low wind wind energy resources has gradually become a new research direction. The development of low wind and wind energy is of great significance to expanding the scope of wind energy utilization and replenish the shortage of fossil energy.
The core of the development and utilization of low wind wind and wind energy lies in the efficiency of wind turbines on low wind and wind energy, the optimization of blade airfoil for low wind turbines, the optimization of aerodynamic performance of the wind turbine, the key role of improving the efficiency of wind and wind energy conversion at low wind speed, reducing the cost of the unit and balancing the load of the unit. This topic is in the national science and technology support project "5.0MW double" With the support of integration and demonstration (2009BAA22B02), the main research work is carried out on the aerodynamic optimization design and the unit optimization control method, theory and key technology of the low wind speed wind turbine group.
(1) based on blade aerodynamic design theory and genetic algorithm optimization theory, genetic algorithm is applied to optimize blade airfoil parameters, and the blade airfoil of medium and low wind turbines is optimized as the base airfoil. The airfoil lift drag ratio is optimized. The geometric control parameter of the upper and lower surface of the blade is the optimization design variable of the airfoil, and the genetic evolution has been obtained. Compared with the reference airfoil, the optimized airfoil has a higher lift drag ratio and a greater lift coefficient.
(2) based on the numerical simulation method of Navier-Stokes equation and using GAMBIT and FLUENT software to simulate the flow field of the optimized airfoil, the aerodynamic performance of the airfoil is optimized, including the pressure distribution around the airfoil, the velocity distribution, the rise drag coefficient, and the numerical analysis results verify the effectiveness of the optimized airfoil.
(3) based on the leaf prime momentum theory, a genetic algorithm is applied to optimize the aerodynamic design of the blade. The wind energy is optimized by using the coefficient variable dCpmax as the objective function, the string length and the torsion angle distribution function coefficient are optimized for the blade design variables. After genetic evolution, the aerodynamic optimization model of the wind turbine blade with low wind speed is obtained. Based on the blade, the GH Bladed software is applied. The dynamic model of 3MW low wind speed wind wheel is constructed and the aerodynamic performance of the wind turbine is analyzed and calculated. The results show that the wind wheel of the low wind turbine has a higher efficiency and a wider high efficiency zone, and the thrust load is smaller, which proves the effectiveness of the aerodynamic optimization of the blade.
(4) the fuzzy control is applied to the maximum power capture and dynamic load control of the doubly fed wind turbine. The mathematical model of the 3MW low wind wind turbine is constructed in the GHBladed software environment, the fuzzy controller of the rotational speed and the dynamic load fuzzy controller of the unit are designed, and the dynamic simulation is carried out. The result shows that the fuzzy control can effectively capture the wind turbine. The maximum power and control dynamic load. A double fed wind turbine based on the dSACE control system is constructed. The performance of the fuzzy control double fed wind turbine is used in the loop test. The experimental results verify the remarkable advantages of the fuzzy control in the control of the nonlinear time-varying wind turbine system.
【学位授予单位】：华北电力大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TM315

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