【摘要】：隨著風(fēng)力發(fā)電技術(shù)日趨成熟,新建風(fēng)電場趨于大型化和集中化,風(fēng)電固有的隨機性、波動性和相關(guān)性為電力系統(tǒng)安全運行帶來巨大挑戰(zhàn)。概率潮流是研究風(fēng)電并網(wǎng)對系統(tǒng)運行影響的有力工具。針對含風(fēng)電系統(tǒng)潮流計算問題,研究了單風(fēng)電場內(nèi)風(fēng)機等值模型、多風(fēng)電場間風(fēng)速相關(guān)性模型及考慮相關(guān)性的概率潮流計算方法。提出了新的等值建模及概率潮流算法,為電力系統(tǒng)的經(jīng)濟調(diào)度以及安全分析提供了新的思路。為了在保證風(fēng)機等值精度的基礎(chǔ)上降低風(fēng)電場仿真模型的復(fù)雜度,考慮到實際風(fēng)電場內(nèi)尾流效應(yīng)及風(fēng)機控制方式不同的情況,借鑒層次分析法的思想提出了兩步分群法。考慮風(fēng)電機組間尾流效應(yīng)計算輸入風(fēng)速,根據(jù)機組槳距角動作情況進(jìn)行初次分群,通過轉(zhuǎn)子電流受擾曲線識別動態(tài)特性相近的風(fēng)機實現(xiàn)再次分群。在保證風(fēng)電機組功率輸出特性和電壓差恒定的基礎(chǔ)上,進(jìn)行風(fēng)機和集電線路參數(shù)等值,得到了風(fēng)電場多機等值模型。仿真算例表明,與傳統(tǒng)等值方法相比,該模型能精確地反映風(fēng)機初始運行點以及動態(tài)特性。多風(fēng)電場間風(fēng)速存在不同程度的相關(guān)性,選擇最佳Copula函數(shù)是相關(guān)性建模的關(guān)鍵。采用非參數(shù)核密度估計風(fēng)速邊緣分布,在單一擬合度評價指標(biāo)的基礎(chǔ)上引入Copula熵作為相關(guān)性評價指標(biāo),提出一種基于熵權(quán)模糊綜合評價的Copula函數(shù)優(yōu)選方法。通過所優(yōu)選的Copula函數(shù)進(jìn)一步建立風(fēng)電場出力相關(guān)性模型,以華北地區(qū)兩個風(fēng)電場為例驗證模型的合理性。針對現(xiàn)有概率潮流計算方法存在計算精度和速度之間的矛盾,引入一種基于Nataf變換的概率潮流三點估計法。該方法能夠有效的處理風(fēng)電場間出力的相關(guān)性,并能在縮短計算時間的基礎(chǔ)上保證計算精度。分別采用該方法與蒙特卡洛法對含多風(fēng)電場的IEEE30節(jié)點系統(tǒng)進(jìn)行概率潮流計算,將二者計算結(jié)果進(jìn)行對比,驗證了該方法的高效性和精確性。
[Abstract]:With the development of wind power generation technology, new wind farms tend to be large-scale and centralized. The inherent randomness, volatility and correlation of wind power bring great challenges to the safe operation of power system. Probabilistic power flow is a powerful tool to study the influence of wind power grid on system operation. Aiming at the problem of power flow calculation in wind power system with wind power, the equivalent model of wind turbine in a single wind farm, the model of wind speed correlation between multi-wind farms and the calculation method of probabilistic power flow considering the correlation are studied. A new equivalent modeling and probabilistic power flow algorithm is proposed, which provides a new idea for economic dispatch and security analysis of power system. In order to reduce the complexity of wind farm simulation model on the basis of ensuring the equivalent precision of wind turbine, considering the different wake effect and fan control mode in actual wind farm, a two-step clustering method is proposed for reference to the idea of analytic hierarchy process (AHP). Considering the wake effect of wind turbines, the input wind speed is calculated, and the initial grouping is carried out according to the pitch angle of the units, and the fan with similar dynamic characteristics is identified by the disturbance curve of rotor current. On the basis of ensuring the constant power output characteristics and voltage difference of wind turbine, the equivalent parameters of fan and collector circuit are obtained, and the equivalent model of wind farm is obtained. The simulation results show that compared with the traditional equivalence method, the model can accurately reflect the initial operating point and dynamic characteristics of the fan. There is different correlation between wind speed in multi-wind farms, and the key of correlation modeling is to select the best Copula function. The nonparametric kernel density is used to estimate the edge distribution of wind speed. On the basis of a single fitness evaluation index, Copula entropy is introduced as the correlation evaluation index, and a Copula function optimization method based on fuzzy comprehensive evaluation of entropy weight is proposed. The model of wind farm output correlation is further established by the selected Copula function. Two wind farms in North China are taken as examples to verify the rationality of the model. In view of the contradiction between the accuracy and speed of the existing probabilistic power flow calculation methods, a three-point estimation method of probabilistic power flow based on Nataf transform is introduced. This method can effectively deal with the correlation between wind farm forces and ensure the calculation accuracy on the basis of shortening the calculation time. The probabilistic power flow calculation of IEEE30 node system with multi-wind farm is carried out by using this method and Monte Carlo method respectively. The results of the two methods are compared to verify the efficiency and accuracy of the method.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM614;TM744

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 謝敏;熊靖;劉明波;周尚籌;;基于Copula的多風(fēng)電場出力相關(guān)性建模及其在電網(wǎng)經(jīng)濟調(diào)度中的應(yīng)用[J];電網(wǎng)技術(shù);2016年04期

2 方斯頓;程浩忠;徐國棟;曾平良;姚良忠;;基于Nataf變換和準(zhǔn)蒙特卡洛模擬的隨機潮流方法[J];電力自動化設(shè)備;2015年08期

3 劉利民;劉俊勇;劉友波;;Nataf變換三點估計分布式發(fā)電網(wǎng)絡(luò)的概率潮流分析[J];電力系統(tǒng)自動化;2015年12期

4 董建政;李征;蔡旭;;基于RT-LAB的雙饋風(fēng)電場動態(tài)建模[J];電力系統(tǒng)保護與控制;2015年07期

5 張元;郝麗麗;戴嘉祺;;風(fēng)電場等值建模研究綜述[J];電力系統(tǒng)保護與控制;2015年06期

6 潘學(xué)萍;張弛;鞠平;吳峰;金宇清;張源;;風(fēng)電場同調(diào)動態(tài)等值研究[J];電網(wǎng)技術(shù);2015年03期

7 高元海;王淳;;基于全概率公式的含風(fēng)電配電系統(tǒng)概率潮流計算[J];中國電機工程學(xué)報;2015年02期

8 楊睿茜;陳紅坤;陶玉波;繆蕓;胡倩;王嶺;;雙饋式風(fēng)機控制器參數(shù)整定的實用方法[J];電力系統(tǒng)保護與控制;2015年02期

9 王小紅;周步祥;張樂;傅利;羅歡;劉建華;;基于時變Copula函數(shù)的風(fēng)電出力相關(guān)性分析[J];電力系統(tǒng)及其自動化學(xué)報;2015年01期

10 徐瀟源;嚴(yán)正;馮冬涵;王毅;曹路;;基于輸入變量秩相關(guān)系數(shù)的概率潮流計算方法[J];電力系統(tǒng)自動化;2014年12期

相關(guān)博士學(xué)位論文 前2條

1 趙寧;基于Copula熵的資本資產(chǎn)定價研究[D];大連理工大學(xué);2012年

2 蘇勛文;風(fēng)電場動態(tài)等值建模方法研究[D];華北電力大學(xué)（河北）;2010年

相關(guān)碩士學(xué)位論文 前2條

1 陳坤;計及相關(guān)性的風(fēng)電場出力模型及其應(yīng)用研究[D];華北電力大學(xué);2016年

2 熊強;考慮多風(fēng)電場相關(guān)性的場景概率潮流計算及其在無功優(yōu)化中的應(yīng)用[D];西南交通大學(xué);2015年

，

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