本文關(guān)鍵詞： 電力系統(tǒng) 暫態(tài)穩(wěn)定 軌跡特征根 事故篩選 波動方差　出處：《西南交通大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：電力系統(tǒng)的安全穩(wěn)定運行與否直接影響到社會經(jīng)濟(jì)的發(fā)展,實際中電力系統(tǒng)不可避免地遭受各種擾動。若不能夠判斷出擾動后系統(tǒng)的暫態(tài)穩(wěn)定性以及識別擾動的類型,及時采取相應(yīng)措施進(jìn)行處理,恢復(fù)正常供電,故障范圍可能會擴(kuò)大,進(jìn)而引發(fā)電力系統(tǒng)大事故的產(chǎn)生。更嚴(yán)重的情況下造成系統(tǒng)振蕩甚至解列,將產(chǎn)生不可估量的經(jīng)濟(jì)損失和難以預(yù)測的社會影響。為了準(zhǔn)確地判斷擾動后系統(tǒng)暫態(tài)穩(wěn)定性并對擾動的類型進(jìn)行篩選,在深入研究已有方法的基礎(chǔ)上,針對已有方法存在的不足,本文嘗試用擾動后系統(tǒng)軌跡特征根的波動特性進(jìn)行系統(tǒng)暫態(tài)穩(wěn)定性判斷和擾動類型篩選,并對其中的關(guān)鍵性問題進(jìn)行分析和討論。首先,建立高階系統(tǒng)線性化模型,充分考慮調(diào)速器和勵磁系統(tǒng)等系統(tǒng)主要元件對系統(tǒng)線性化模型的影響。調(diào)速器和勵磁系統(tǒng)模型在線性化處理時考慮到模型的復(fù)雜性,嘗試一種利用拉普拉斯逆變換實現(xiàn)復(fù)雜模塊模型在非平衡點處的線性化處理方法。其次,將擾動后系統(tǒng)軌跡特征根的波動情況與對應(yīng)擾動下發(fā)電機(jī)相對功角曲線判斷得出的系統(tǒng)暫態(tài)穩(wěn)定性結(jié)果進(jìn)行比較,發(fā)現(xiàn)系統(tǒng)擾動后暫態(tài)穩(wěn)定時,軌跡特征根衰減性振蕩,并最終收斂于小范圍的波動。系統(tǒng)擾動后如果暫態(tài)不穩(wěn)定,則軌跡特征根無規(guī)律振蕩,并無收斂趨勢。根據(jù)這個規(guī)律,本文提出了一種基于擾動后系統(tǒng)軌跡特征根的暫態(tài)穩(wěn)定性判斷方法,該方法判定系統(tǒng)遭受預(yù)想事故的暫態(tài)穩(wěn)定性雖然耗時較長,但是由于軌跡特征根曲線是綜合所有變量求取的結(jié)果,包括發(fā)電機(jī)功角、機(jī)端電壓等變量,因此準(zhǔn)確性較傳統(tǒng)單一變量判斷系統(tǒng)暫態(tài)穩(wěn)定性有較大的提高,適用于電力規(guī)劃和運行調(diào)度的離線暫態(tài)穩(wěn)定性分析。最后,通過分析發(fā)現(xiàn)擾動的大小和類型對軌跡特征根的影響程度各不相同,尤其是軌跡特征根的波動范圍有明顯差別。有害擾動和無害擾動作用下系統(tǒng)軌跡特征根波動特性之間的差別尤為顯著,引用方差對擾動后的軌跡特征根曲線進(jìn)行振蕩和離散程度的量化分析,并以此量化指標(biāo)為依據(jù),根據(jù)系統(tǒng)軌跡特征根曲線的波動方差與擾動類型的對應(yīng)關(guān)系,本文提出一種基于擾動后系統(tǒng)軌跡特征根波動方差的擾動類型識別方法。在解決快速性問題上,該方法采用擾動發(fā)生后的第一個搖擺周期作為時間截面,計算該時間截面軌跡特征根的波動方差。并通過算例進(jìn)行驗證,結(jié)果表明,預(yù)想擾動設(shè)置的類型與擾動識別區(qū)識別的結(jié)果相一致,論證了這種方法能夠有效滿足系統(tǒng)暫態(tài)分析中對擾動類型快速、準(zhǔn)確篩選的要求。
[Abstract]:The safe and stable operation of power system has a direct impact on the development of social economy. In practice, the power system is inevitably subjected to various disturbances. If the transient stability of the system after disturbance can not be judged and the type of disturbance can be identified, Timely measures should be taken to deal with it, restore normal power supply, and the range of faults may be enlarged, which may lead to the occurrence of major accidents in the power system. In more serious cases, the system will oscillate or even be desegregated. In order to accurately judge the transient stability of the system after disturbance and screen out the types of disturbance, based on the existing methods, In view of the shortcomings of the existing methods, this paper attempts to use the characteristic root of the system trajectory after disturbance to judge the transient stability of the system and to screen out the types of disturbance. The key problems are analyzed and discussed. The linearization model of higher-order system is established, and the influence of the main components of the governor and excitation system on the linearization model of the system is fully considered. The complexity of the model is taken into account when the governor and the excitation system model are linearized. This paper tries to use Laplace inverse transform to realize the linearization of complex module model at the non-equilibrium point. Secondly, By comparing the fluctuation of the system trajectory characteristic root after disturbance with the transient stability of the system determined by the relative power angle curve of the generator under the corresponding disturbance, it is found that the trajectory characteristic root attenuates oscillation when the system is transient stability after disturbance. And finally converges to a small range of fluctuations. If the system is disturbed by transient instability, the trajectory characteristic root oscillates irregularly and has no convergence trend. In this paper, a method of judging transient stability based on the characteristic root of the system trajectory after disturbance is proposed. This method takes a long time to judge the transient stability of the system subjected to the expected accident. However, because the trajectory characteristic root curve is the result of synthesizing all variables, such as generator power angle, terminal voltage and so on, the accuracy of the trajectory characteristic root curve is much higher than that of the traditional single variable in judging the transient stability of the system. It is suitable for off-line transient stability analysis of power planning and operation dispatching. Finally, it is found that the magnitude and type of disturbance have different influence on the trajectory characteristic root. Especially, the fluctuation range of trajectory characteristic root is obviously different, especially between harmful disturbance and harmless disturbance. The oscillation and dispersion degree of the trajectory characteristic root curve after disturbance is analyzed quantitatively by using variance, and based on the quantization index, according to the relation between the fluctuation variance of the characteristic root curve and the type of disturbance, In this paper, a disturbance type identification method based on the variance of the characteristic root fluctuation of the trajectory of the perturbed system is proposed. In order to solve the problem of rapidity, the first rocking period after disturbance is used as the time section. The fluctuation variance of the characteristic root of the track of the time section is calculated and verified by an example. The results show that the type of the preconceived disturbance is consistent with the result of the identification of the disturbance. It is demonstrated that this method can effectively meet the requirement of fast and accurate screening of disturbance types in transient analysis of systems.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM712

【相似文獻(xiàn)】

相關(guān)期刊論文 前10條

1 潘學(xué)萍;薛禹勝;鞠平;;關(guān)于軌跡特征根的再思考[J];電力系統(tǒng)自動化;2013年23期

2 呂毅;李成忠;杜曉春;;彈性飛行器動態(tài)系統(tǒng)特征根對參數(shù)的敏感性研究[J];飛行力學(xué);1987年02期

3 殷建;以-1為特征根的圖[J];山東大學(xué)學(xué)報(工學(xué)版);2004年04期

4 郝思鵬;薛禹勝;唐茂林;李建;;通過軌跡特征根分析時變振蕩特性[J];電力系統(tǒng)自動化;2009年06期

5 潘學(xué)萍;薛禹勝;張曉明;鐘志勇;黃杰波;;軌跡特征根的解析估算及其誤差分析[J];電力系統(tǒng)自動化;2008年19期

6 陸丹丹;楊飛燕;王建全;;基于軌跡特征根的快速事故篩選方法[J];電力系統(tǒng)自動化;2013年05期

7 譚偉;沈沉;李穎;倪敬敏;劉鋒;;基于軌跡特征根的機(jī)組分群方法[J];電力系統(tǒng)自動化;2010年01期

8 李漢強(qiáng);特征根在系統(tǒng)穩(wěn)定性上的應(yīng)用[J];武漢交通科技大學(xué)學(xué)報;1994年04期

9 李欣,賈秀芳;矩陣特征根的理論研究及應(yīng)用[J];佳木斯大學(xué)學(xué)報(自然科學(xué)版);2000年02期

10 梁偉;吳峰;鞠平;;異步風(fēng)力發(fā)電系統(tǒng)的特征根靈敏度分析[J];可再生能源;2012年12期

相關(guān)會議論文 前1條

1 傅向榮;龍馭球;;分區(qū)加速Müller法計算Ⅴ型切口特征根[A];第十一屆全國結(jié)構(gòu)工程學(xué)術(shù)會議論文集第Ⅰ卷[C];2002年

相關(guān)博士學(xué)位論文 前1條

1 潘學(xué)萍;基于EEAC理論分析受擾軌跡的時變非線性動態(tài)模式[D];浙江大學(xué);2008年

相關(guān)碩士學(xué)位論文 前3條

1 李曉東;帶有非共振特征根和傾斜翻轉(zhuǎn)的雙同宿環(huán)分支[D];東北師范大學(xué);2015年

2 王騰;基于軌跡特征根靈敏度的電力系統(tǒng)機(jī)電動態(tài)特性研究[D];西南交通大學(xué);2015年

3 袁優(yōu);基于軌跡特征根的系統(tǒng)暫態(tài)穩(wěn)定判斷與擾動類型篩選方法[D];西南交通大學(xué);2017年

，

本文編號：1495165