本文選題：塔式太陽(yáng)能吸熱器 + 溫度分布預(yù)測(cè)��； 參考：《華北電力大學(xué)(北京)》2017年博士論文

【摘要】：作為新能源產(chǎn)業(yè)的重要組成部分,塔式太陽(yáng)能發(fā)電系統(tǒng)被認(rèn)為是一種具有廣闊發(fā)展前景的發(fā)電技術(shù)。隨著國(guó)家對(duì)光熱發(fā)電產(chǎn)業(yè)政策的陸續(xù)出臺(tái)和不斷完善,塔式太陽(yáng)能技術(shù)將在清潔能源領(lǐng)域扮演舉足輕重的角色。吸熱器將太陽(yáng)輻射能轉(zhuǎn)化為熱能,是塔式電站的核心部分,直接影響到整個(gè)發(fā)電系統(tǒng)的效率和經(jīng)濟(jì)性。為理解吸熱器中所涉及的復(fù)雜物理機(jī)制,確保塔式太陽(yáng)能電站安全、高效運(yùn)行,本文對(duì)吸熱器的熱特性進(jìn)行深入研究。主要工作如下:(1)建立了吸熱器流動(dòng)-傳熱-力學(xué)效應(yīng)耦合的復(fù)雜多物理場(chǎng)模型,數(shù)值研究了管壁的溫度分布和熱應(yīng)力分布,熔鹽的溫度分布和流速分布,揭示了在不同風(fēng)速條件下熔鹽出口平均溫度和最高溫度、管壁最高溫度隨熔鹽進(jìn)口溫度和進(jìn)口流速的變化規(guī)律,以及管壁熱應(yīng)力和位移分布規(guī)律。(2)建立了基于BP神經(jīng)網(wǎng)絡(luò)(Back-propagation neural network,BPNN)的吸熱器熔鹽溫度和管壁溫度預(yù)測(cè)模型,克服了傳統(tǒng)數(shù)值計(jì)算方法需要求解復(fù)雜的控制方程,計(jì)算復(fù)雜性高,計(jì)算時(shí)間長(zhǎng),難以準(zhǔn)確給定初始條件、邊界條件、幾何條件、物性參數(shù)等弊端。數(shù)值研究結(jié)果證實(shí)了該方法具有預(yù)測(cè)精度高、魯棒性好、泛化能力強(qiáng)等優(yōu)點(diǎn)。(3)基于熱傳遞和?傳遞理論,建立了吸熱器獲得最大有用能的最優(yōu)化模型,利用萬(wàn)有引力(Gravitational search,GS)算法和模擬退火(Simulated annealing,SA)算法分別求解單根吸熱管以及整個(gè)吸熱器獲得最大能源利用效率的最優(yōu)化問(wèn)題,獲得最優(yōu)運(yùn)行工況。揭示了在管內(nèi)熔鹽最優(yōu)進(jìn)口溫度和流速下沿熔鹽流動(dòng)方向能量傳遞的數(shù)量和質(zhì)量的細(xì)節(jié),為高效利用太陽(yáng)能提供了科學(xué)依據(jù)。(4)提出了基于傳熱反問(wèn)題的利用有限溫度測(cè)量數(shù)據(jù)反演吸熱管外熱流分布的方法,克服難以直接測(cè)量管外熱流分布難題。通過(guò)建立目標(biāo)泛函將反問(wèn)題轉(zhuǎn)化為一個(gè)最優(yōu)化問(wèn)題的求解,采用Broyden-Fletcher-Goldfarb-Shanno(BFGS)算法有效地求解該模型。數(shù)值實(shí)驗(yàn)表明,該方法能夠利用有限的溫度測(cè)量數(shù)據(jù)準(zhǔn)確反演管外熱流分布,為在實(shí)際應(yīng)用中獲取吸熱器表面熱流分布提供一種有效方法。(5)提出一種利用最小二乘支持向量機(jī)(Least square support vector machine,LSSVM)和高斯過(guò)程回歸(Gaussian process regression,GPR)快速預(yù)測(cè)吸熱管中兩相對(duì)流換熱系數(shù)的方法,克服了實(shí)驗(yàn)方法周期長(zhǎng)、成本高,數(shù)值計(jì)算方法時(shí)間成本高、計(jì)算復(fù)雜性高,尤其是經(jīng)驗(yàn)公式(Empirical correlation,EC)法需要預(yù)先確定函數(shù)關(guān)系式等弊端。利用群搜索(Group search optimizer,GSO)算法優(yōu)化最小二乘支持向量機(jī)模型的超參數(shù),改善預(yù)測(cè)質(zhì)量。該方法有利于減少實(shí)驗(yàn)次數(shù)和實(shí)驗(yàn)成本,縮短設(shè)計(jì)周期,為研究吸熱器中氣液兩相流的換熱特性提供一種有效方法。研究發(fā)現(xiàn)對(duì)確保吸熱器安全高效運(yùn)行、促進(jìn)太陽(yáng)能光熱發(fā)電技術(shù)大規(guī)模應(yīng)用提供了科學(xué)依據(jù),為我國(guó)的節(jié)能減排戰(zhàn)略做出貢獻(xiàn)。
[Abstract]:As an important part of the new energy industry, the tower solar power generation system is considered to be a kind of power generation technology with broad development prospects.With the introduction and improvement of national policies on photothermal power generation industry, tower solar energy technology will play an important role in the field of clean energy.Heat absorber converts solar radiation energy into heat energy, which is the core part of tower power station, which directly affects the efficiency and economy of the whole power generation system.In order to understand the complex physical mechanism involved in the heat absorber and ensure the safe and efficient operation of the tower solar power station, the thermal characteristics of the absorber are studied in this paper.The main work is as follows: (1) A complex multi-physical field model coupled with flow-heat transfer and mechanical effects of heat exchanger is established. The temperature distribution and thermal stress distribution of tube wall, the temperature distribution and velocity distribution of molten salt are numerically studied.The variation of the average and maximum temperature at the outlet of molten salt and the maximum temperature of pipe wall with the inlet temperature and inlet velocity of molten salt under different wind speeds are revealed.Based on BP neural network Back-propagation neural Network (BPNN), the prediction model of molten salt temperature and pipe wall temperature of heat absorber is established. It overcomes the need of solving complex control equation by traditional numerical calculation method, and the complexity of calculation is high.It is difficult to accurately set initial condition, boundary condition, geometry condition, physical parameter and so on.The numerical results show that the proposed method has the advantages of high prediction accuracy, good robustness and strong generalization ability.Based on the transfer theory, an optimization model for the maximum useful energy of the heat absorber is established. Using the Gravitational search (GS) algorithm and the simulated annealing simulated annealing (SA) algorithm, the optimization problems of the single endothermic tube and the whole heat absorber to obtain the maximum energy efficiency are solved, respectively.The optimal operating conditions are obtained.The details of the quantity and quality of energy transfer along the flow direction of molten salt under the optimum inlet temperature and velocity of molten salt in the tube are revealed.This paper provides a scientific basis for the efficient use of solar energy. (4) A method for retrieving the heat flux distribution outside the endothermic tube using finite temperature measurement data based on the inverse heat transfer problem is proposed to overcome the difficulty of directly measuring the heat flux distribution outside the tube.The inverse problem is transformed into an optimization problem by establishing the objective functional, and the Broyden-Fletcher-Goldfarb-ShannoBFGSalgorithm is used to solve the model effectively.Numerical experiments show that the proposed method can accurately retrieve the heat flux distribution outside the tube using the limited temperature measurement data.In order to provide an effective method for obtaining heat flux distribution on the surface of heat absorber in practical application, a fast prediction method of two-phase convection heat transfer coefficient in endothermic pipes using least square support vector machine (LSSVM) and Gao Si process regression Gaussian process regression (GPRs) is presented.It overcomes the disadvantages of long period, high cost, high time cost and high computational complexity of the experimental method, especially the empirical formula empirical correlation (ECC) method needs to determine the function relation in advance.The group search group search optimizer (GSO) algorithm is used to optimize the super-parameters of the least squares support vector machine (LS-SVM) model to improve the prediction quality.This method is helpful to reduce the number and cost of experiments, shorten the design period, and provide an effective method for studying the heat transfer characteristics of gas-liquid two-phase flow in an absorber.It is found that it provides a scientific basis for ensuring the safe and efficient operation of the absorber and promotes the large-scale application of solar photothermal power generation technology and contributes to the strategy of energy saving and emission reduction in China.
【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TM615

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