【摘要】：由于風(fēng)能具有隨機(jī)波動(dòng)性,大規(guī)模風(fēng)電并網(wǎng)給電力系統(tǒng)的安全和經(jīng)濟(jì)運(yùn)行帶來(lái)不利影響,而準(zhǔn)確的風(fēng)電場(chǎng)功率預(yù)測(cè)是緩解上述問(wèn)題的有效途徑�；贑FD流場(chǎng)預(yù)計(jì)算的風(fēng)電場(chǎng)功率預(yù)測(cè)方法一方面可以針對(duì)復(fù)雜地形有目的性地細(xì)化計(jì)算模型,準(zhǔn)確模擬風(fēng)電場(chǎng)的空氣流動(dòng)特征,通過(guò)精細(xì)的流場(chǎng)計(jì)算提高預(yù)測(cè)精度；另一方面將流場(chǎng)計(jì)算放在功率預(yù)測(cè)之前進(jìn)行,大幅提高模型的計(jì)算效率。該方法無(wú)需歷史數(shù)據(jù)訓(xùn)練建模,適用于歷史數(shù)據(jù)不足、地形復(fù)雜、氣候多變的風(fēng)電場(chǎng)。 論文主要內(nèi)容和研究結(jié)果包括： (1)針對(duì)復(fù)雜地形風(fēng)電場(chǎng)建立了功率預(yù)測(cè)的CFD模型及預(yù)計(jì)算數(shù)據(jù)庫(kù) 研究了平坦地形風(fēng)電場(chǎng)功率預(yù)測(cè)CFD方法的預(yù)測(cè)誤差特點(diǎn),通過(guò)分析風(fēng)速、風(fēng)向?qū)︻A(yù)測(cè)誤差的影響規(guī)律,提出了基于風(fēng)況離散的預(yù)計(jì)算數(shù)據(jù)庫(kù)優(yōu)化方法,局部細(xì)化CFD模型和預(yù)計(jì)算數(shù)據(jù)庫(kù),在準(zhǔn)確模擬風(fēng)電場(chǎng)流場(chǎng)特征的同時(shí),盡可能提高模型的計(jì)算效率。 (2)建立了基于預(yù)計(jì)算方法的風(fēng)電場(chǎng)功率預(yù)測(cè)模型 預(yù)計(jì)算方法是根據(jù)流場(chǎng)特征建立預(yù)計(jì)算數(shù)據(jù)庫(kù),預(yù)存儲(chǔ)風(fēng)電場(chǎng)CFD模型的計(jì)算結(jié)果,在實(shí)際運(yùn)行中根據(jù)實(shí)際風(fēng)況調(diào)用數(shù)據(jù)庫(kù)中的相應(yīng)功率預(yù)測(cè)結(jié)果,實(shí)現(xiàn)風(fēng)電場(chǎng)功率預(yù)測(cè)。以中國(guó)西北部的某復(fù)雜地形風(fēng)電場(chǎng)為例驗(yàn)證模型精度,結(jié)果表明,預(yù)計(jì)算方法在輸出功率短時(shí)間內(nèi)由滿發(fā)降至零出力、由零出力增至滿發(fā)以及大幅波動(dòng)這三種對(duì)電網(wǎng)沖擊最大的風(fēng)電場(chǎng)出力變化狀態(tài)下表現(xiàn)出良好的跟蹤能力。 (3)建立了三種數(shù)值天氣預(yù)報(bào)風(fēng)速修正模型 基于最小二乘、支持向量機(jī)、徑向基神經(jīng)網(wǎng)絡(luò)原理建立了三種數(shù)值天氣預(yù)報(bào)風(fēng)速的修正模型,以提高數(shù)值天氣預(yù)報(bào)和整體功率預(yù)測(cè)的精度；分別以實(shí)測(cè)、原始NWP及三種修正NWP風(fēng)速為模型輸入,研究了不同修正方法的誤差修正效果,并分析了模型輸入誤差對(duì)基于CFD流場(chǎng)預(yù)計(jì)算的功率預(yù)測(cè)精度的影響。
[Abstract]:Due to the random fluctuation of wind power, the large-scale wind power grid connection brings adverse effects on the security and economic operation of the power system, and accurate wind farm power prediction is an effective way to alleviate the above-mentioned problems. On the one hand, the wind farm power prediction method based on the precomputation of CFD flow field can, on the one hand, refine the calculation model for complex terrain, accurately simulate the air flow characteristics of wind farm, and improve the prediction precision by fine calculation of flow field. On the other hand, the calculation of flow field is carried out before the power prediction, which greatly improves the computational efficiency of the model. This method does not require historical data training and modeling, and is suitable for wind farms with insufficient historical data, complex topography and changeable climate. The main contents and results of this paper are as follows: (1) the CFD model of power prediction for complex terrain wind farm is established and the prediction error characteristics of the CFD method for power prediction of flat terrain wind farm are studied, and the prediction error characteristics of CFD method for power prediction of flat terrain wind farm are studied. Based on the analysis of the influence of wind speed and wind direction on the prediction error, the optimization method of precomputation database based on wind condition discretization is put forward. The CFD model and precomputation database are refined locally, and the flow field characteristics of wind farm are simulated accurately at the same time. The computational efficiency of the model is improved as much as possible. (2) the pre-calculation method of wind farm power prediction model based on precomputation method is to establish the precomputation database according to the characteristics of the flow field, and store the calculation results of the CFD model of wind storage farm. In the actual operation, the corresponding power prediction results in the database are called according to the actual wind conditions, and the wind farm power prediction is realized. A complex terrain wind farm in northwest China is taken as an example to verify the accuracy of the model. The results show that the precomputation method decreases from full output to zero output in a short time. The three wind farms, which have the biggest impact on the power grid, show good tracking ability under the condition of zero output increasing to full generation and large fluctuation. (3) based on the principle of least square, support vector machine and radial basis function neural network, three kinds of modified models of numerical weather forecast wind speed are established, which are based on the principle of least square, support vector machine and radial basis function neural network. In order to improve the accuracy of numerical weather forecast and overall power prediction; Taking the measured, original NWP and three modified NWP wind speeds as the model inputs, the error correction effects of different correction methods are studied, and the influence of the model input errors on the power prediction accuracy based on the CFD flow field prediction is analyzed.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TM614

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