本文選題：低風(fēng)速風(fēng)電機(jī)組 + 風(fēng)輪　； 參考：《華北電力大學(xué)》2014年博士論文

【摘要】：隨著規(guī)模化風(fēng)電產(chǎn)業(yè)的不斷發(fā)展,陸上常規(guī)較高風(fēng)速以上風(fēng)能資源的開發(fā)利用技術(shù)已接近成熟,開發(fā)低風(fēng)速風(fēng)能資源逐漸成為一個(gè)新的研究方向,低風(fēng)速風(fēng)能開發(fā)對(duì)擴(kuò)大風(fēng)能利用范圍及補(bǔ)充化石能源短缺現(xiàn)狀具有重要意義。 低風(fēng)速風(fēng)能開發(fā)利用的核心在于風(fēng)電機(jī)組對(duì)低風(fēng)速風(fēng)能的捕獲效率,研究低風(fēng)速風(fēng)電機(jī)組葉片翼型優(yōu)化、風(fēng)輪氣動(dòng)性能優(yōu)化,對(duì)提升低風(fēng)速風(fēng)能轉(zhuǎn)換效率、降低機(jī)組成本、均衡機(jī)組載荷起到關(guān)鍵作用。本課題在國(guó)家科技支撐項(xiàng)目“5.0MW雙饋式變速恒頻近海風(fēng)電機(jī)組整機(jī)設(shè)計(jì)、集成及示范(2009BAA22B02)”的資助下,圍繞低風(fēng)速風(fēng)電機(jī)組風(fēng)輪氣動(dòng)優(yōu)化設(shè)計(jì)和機(jī)組優(yōu)化控制方法、理論及關(guān)鍵技術(shù)開展了如下主要研究工作： (1)基于葉片氣動(dòng)設(shè)計(jì)理論和遺傳算法優(yōu)化理論,應(yīng)用遺傳算法優(yōu)化葉片翼型參數(shù),以中低風(fēng)速風(fēng)電機(jī)組葉片翼型為優(yōu)化基準(zhǔn)翼型,翼型升阻比為優(yōu)化適應(yīng)值函數(shù),葉片上下表面的幾何控制參數(shù)為翼型優(yōu)化設(shè)計(jì)變量,經(jīng)過遺傳進(jìn)化,獲得了低風(fēng)速風(fēng)電機(jī)組葉片優(yōu)化翼型系列。與基準(zhǔn)翼型相比,優(yōu)化翼型具有較高的升阻比和更大的升力系數(shù)。 (2)基于Navier-Stokes方程的數(shù)值模擬方法,應(yīng)用GAMBIT和FLUENT軟件對(duì)優(yōu)化翼型進(jìn)行流場(chǎng)數(shù)值模擬,研究?jī)?yōu)化翼型的氣動(dòng)性能,包括翼型周圍壓力分布、速度分布、升阻力系數(shù),數(shù)值分析結(jié)果驗(yàn)證了優(yōu)化翼型的有效性。 (3)基于葉素-動(dòng)量理論,應(yīng)用遺傳算法優(yōu)化葉片氣動(dòng)設(shè)計(jì),以風(fēng)能利用系數(shù)變量dCpmax為優(yōu)化目標(biāo)函數(shù),弦長(zhǎng)和扭角分布函數(shù)系數(shù)為葉片優(yōu)化設(shè)計(jì)變量,經(jīng)過遺傳進(jìn)化,獲得了低風(fēng)速風(fēng)電葉片氣動(dòng)優(yōu)化模型,并基于該葉片,應(yīng)用GH Bladed軟件,構(gòu)建3MW低風(fēng)速風(fēng)輪動(dòng)力學(xué)模型,分析計(jì)算風(fēng)輪氣動(dòng)性能,結(jié)果表明,低風(fēng)速風(fēng)電機(jī)組風(fēng)輪具有更高的效率和更寬的高效率區(qū),推力載荷較小,驗(yàn)證了葉片氣動(dòng)優(yōu)化的有效性。 (4)將模糊控制應(yīng)用于雙饋風(fēng)電機(jī)組最大功率捕獲和動(dòng)態(tài)載荷控制,在GHBladed軟件環(huán)境構(gòu)建3MW低風(fēng)速風(fēng)電機(jī)組數(shù)學(xué)模型,設(shè)計(jì)轉(zhuǎn)速模糊控制器和機(jī)組動(dòng)態(tài)載荷模糊控制器,并進(jìn)行動(dòng)態(tài)仿真,結(jié)果顯示應(yīng)用模糊控制能使風(fēng)電機(jī)組有效捕獲最大功率和控制動(dòng)態(tài)載荷。構(gòu)建了一個(gè)基于dSACE控制系統(tǒng)的雙饋風(fēng)電機(jī)組在環(huán)測(cè)試平臺(tái),在環(huán)測(cè)試研究采用模糊控制的雙饋風(fēng)電機(jī)組性能,實(shí)驗(yàn)結(jié)果進(jìn)一步驗(yàn)證了模糊控制在非線性時(shí)變的風(fēng)電機(jī)組系統(tǒng)控制上的顯著優(yōu)點(diǎn)。
[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.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM315

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