基于阻尼轉矩理論的PSS設計與控制
發(fā)布時間：2018-12-12 13:19
【摘要】：本文詳細地介紹了電力系統(tǒng)阻尼轉矩理論�；诖死碚�,可以用協(xié)同設計法對PSS進行設計。常見的協(xié)同設計方法是將設計問題轉換成對一個目標函數(shù)進行參數(shù)尋優(yōu)的過程。這樣PSS的參數(shù)的設置就可以通過在PSS的參數(shù)空間上對目標函數(shù)進行尋優(yōu)來完成。本文提出了一種簡單的協(xié)同設計方法。在多機電力系統(tǒng)中對M臺PSS進行協(xié)同設計時,在參數(shù)空間上對維數(shù)進行簡化。尋優(yōu)過程是在M維參數(shù)空間中進行,尋找最優(yōu)解的效率也隨著參數(shù)空間維數(shù)的簡化而提高。本文提出的尋優(yōu)方法分為兩個步驟。首先,在多機系統(tǒng)中計算一臺PSS向所有同步發(fā)電機提供的阻尼轉矩,設置每一臺PSS參數(shù),使其能夠向目標機電振蕩模式提供最大的阻尼。文中證明了這種設置方法可以使得PSS提供阻尼的方式最為高效。所有PSS的參數(shù)都按照一定的順序進行設置。接著,通過參數(shù)優(yōu)化的方法對所有PSS的增益進行設計。在對M臺PSS的尋優(yōu)是在M維參數(shù)空間下進行。文中通過了一個多機系統(tǒng)的算例對這種方法的正確性進行了解釋和驗證。為了更深入地解釋這種協(xié)同設計方法,測試并比較了不同形式下的常用目標函數(shù)。本文還在三維圖形上表示出其集合,并且在這些圖形當中,可以找到使得增益和最小的一個組合。對于目標函數(shù)的討論能夠有助于對尋優(yōu)和目標函數(shù)之間的關系有更深入的認識。為了克服PSS參數(shù)優(yōu)化的非線性、多極值的特點,最后介紹了一種智能優(yōu)化算法——魚群算法對PSS參數(shù)進行優(yōu)化,并在含有裝有阻尼控制器的UPFC和PSS的江蘇電網(wǎng)以及一個四機兩區(qū)域的系統(tǒng)中進行了算例驗證。最后對比并分析了UPFC上的阻尼控制器和發(fā)電機上的PSS對振蕩模式的影響,發(fā)現(xiàn)UPFC上的阻尼控制器對振蕩模式的影響很小。因此,將UPFC上的阻尼控制器去掉,重新設計PSS上的參數(shù),并且根據(jù)設計的結果,在BPA中對系統(tǒng)進行仿真。結果表明,這種設計方法能夠有效地提高系統(tǒng)的穩(wěn)定性。
[Abstract]:In this paper, the damping torque theory of power system is introduced in detail. Based on this theory, PSS can be designed by collaborative design method. The common collaborative design method is to transform the design problem into the process of parameter optimization for an objective function. In this way, the parameters of PSS can be set by optimizing the objective function in the parameter space of PSS. A simple collaborative design method is presented in this paper. In the collaborative design of M PSS in multi-machine power system, the dimension is simplified in parameter space. The optimization process is carried out in the M-dimensional parameter space, and the efficiency of finding the optimal solution increases with the simplification of the dimension of the parameter space. The optimization method proposed in this paper is divided into two steps. First, the damping torque provided by a PSS to all synchronous generators is calculated in a multi-machine system, and each PSS parameter is set to provide maximum damping to the target electromechanical oscillation mode. This method is proved to be the most efficient way for PSS to provide damping. All PSS parameters are set in a certain order. Then, the gain of all PSS is designed by the method of parameter optimization. The optimization of M-station PSS is carried out in M-dimensional parameter space. The correctness of this method is explained and verified by a multi-machine system. In order to explain the cooperative design method more deeply, the common objective functions in different forms are tested and compared. In this paper, we also show the set on 3D graphics, and in these graphs, we can find a combination of gain and minimum. The discussion of objective function can help us to understand the relationship between optimization and objective function. In order to overcome the nonlinear and multi-extremum characteristics of PSS parameter optimization, an intelligent optimization algorithm, fish swarm algorithm, is introduced to optimize PSS parameters. An example is given in Jiangsu Power Grid with UPFC and PSS with damping controller and a four-machine and two-area system. Finally, the effects of damping controller on UPFC and PSS on generator on oscillation mode are compared and analyzed. It is found that the damping controller on UPFC has little effect on oscillation mode. Therefore, the damping controller on UPFC is removed and the parameters on PSS are redesigned. According to the design results, the system is simulated in BPA. The results show that this design method can effectively improve the stability of the system.
【學位授予單位】：華北電力大學(北京)
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM712
本文編號：2374638
[Abstract]:In this paper, the damping torque theory of power system is introduced in detail. Based on this theory, PSS can be designed by collaborative design method. The common collaborative design method is to transform the design problem into the process of parameter optimization for an objective function. In this way, the parameters of PSS can be set by optimizing the objective function in the parameter space of PSS. A simple collaborative design method is presented in this paper. In the collaborative design of M PSS in multi-machine power system, the dimension is simplified in parameter space. The optimization process is carried out in the M-dimensional parameter space, and the efficiency of finding the optimal solution increases with the simplification of the dimension of the parameter space. The optimization method proposed in this paper is divided into two steps. First, the damping torque provided by a PSS to all synchronous generators is calculated in a multi-machine system, and each PSS parameter is set to provide maximum damping to the target electromechanical oscillation mode. This method is proved to be the most efficient way for PSS to provide damping. All PSS parameters are set in a certain order. Then, the gain of all PSS is designed by the method of parameter optimization. The optimization of M-station PSS is carried out in M-dimensional parameter space. The correctness of this method is explained and verified by a multi-machine system. In order to explain the cooperative design method more deeply, the common objective functions in different forms are tested and compared. In this paper, we also show the set on 3D graphics, and in these graphs, we can find a combination of gain and minimum. The discussion of objective function can help us to understand the relationship between optimization and objective function. In order to overcome the nonlinear and multi-extremum characteristics of PSS parameter optimization, an intelligent optimization algorithm, fish swarm algorithm, is introduced to optimize PSS parameters. An example is given in Jiangsu Power Grid with UPFC and PSS with damping controller and a four-machine and two-area system. Finally, the effects of damping controller on UPFC and PSS on generator on oscillation mode are compared and analyzed. It is found that the damping controller on UPFC has little effect on oscillation mode. Therefore, the damping controller on UPFC is removed and the parameters on PSS are redesigned. According to the design results, the system is simulated in BPA. The results show that this design method can effectively improve the stability of the system.
【學位授予單位】：華北電力大學(北京)
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM712
【參考文獻】
相關期刊論文 前10條
1 祁桂剛;黎燦兵;曹一家;李欣然;周煉;曾龍;;SVC和TCSC控制器間動態(tài)交互影響分析[J];電力自動化設備;2014年07期
2 胡曉波;楊利民;陳中;王海風;唐國慶;;基于人工魚群算法的PSS參數(shù)優(yōu)化[J];電力自動化設備;2009年02期
3 王青;閔勇;張毅威;;電力系統(tǒng)低頻振蕩的機理研究和主要分析方法[J];電氣應用;2006年07期
4 張劍,許鎮(zhèn)琳,王天將;基于單神經(jīng)元的參數(shù)自學習模糊控制器的研究[J];中小型電機;2005年02期
5 寧聯(lián)輝,程時杰,文勁宇,彭曉濤;可控串補(TCSC)的自適應單神經(jīng)元控制[J];繼電器;2005年02期
6 李穎,賀仁睦;負荷與PSS的相互作用對系統(tǒng)動態(tài)穩(wěn)定的影響[J];電力系統(tǒng)自動化;2004年08期
7 孫衢,徐光虎,陳陳;負荷模型動態(tài)特性不確定性對低頻振蕩的影響[J];電力系統(tǒng)自動化;2003年10期
8 楊琳,趙書強;H_∞電力系統(tǒng)穩(wěn)定器的設計及其降階[J];電力自動化設備;2003年03期
9 楊曉東,房大中,劉長勝,宋文南;阻尼聯(lián)絡線低頻振蕩的SVC自適應模糊控制器研究[J];中國電機工程學報;2003年01期
10 王鐵強,賀仁睦,王衛(wèi)國,徐東杰,魏立民,肖利民;電力系統(tǒng)低頻振蕩機理的研究[J];中國電機工程學報;2002年02期
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