本文選題：諧波　切入點：電壓暫降　出處：《華北電力大學》2015年碩士論文　論文類型：學位論文

【摘要】：近年來,電能質量問題逐漸引起人們的重視。一方面,隨著電力電子技術在電力系統(tǒng)的廣泛應用,越來越多的諧波注入到電網中；另一方面,隨著各種復雜、精密設備越來越多的應用,電壓暫降帶來的問題逐漸突出。準確有效的監(jiān)測是發(fā)現(xiàn)和抑制這些電能質量問題的前提和基礎,如何在電網中關鍵節(jié)點合理配置監(jiān)測裝置,利用有限監(jiān)測裝置提供的信息,進行全網整體電能質量等問題的分析,具有重要的意義。本文針對諧波和電壓暫降各自的特點,將二者的監(jiān)測點結合起來統(tǒng)一配置,從而得到同時滿足二者完全可觀測的最優(yōu)配置方案。首先針對電壓暫降,提出了一種基于模糊控制模型和粒子群算法的電壓暫降監(jiān)測裝置的優(yōu)化配置方法。在該方法中,提出了模糊閾值和觀測指數(shù)的概念,考慮了母線觀測能力,建立模糊控制模型以得到優(yōu)化的目標函數(shù),進而采用離散粒子群算法(BPSO)進行優(yōu)化配置。通過對IEEE30節(jié)點測試系統(tǒng)進行仿真分析,并且將其配置結果與傳統(tǒng)方法相比較,表明了所提出方法不僅能夠實現(xiàn)全網電壓暫降完全可觀測,而且實現(xiàn)了監(jiān)測裝置的最優(yōu)配置。在電壓暫降監(jiān)測點配置完成的基礎上,研究了諧波的可觀性分析與狀態(tài)估計方法,建立了統(tǒng)一的優(yōu)化配置模型,以非諧波源網絡拓撲結構的可觀性判斷方法作為約束條件,以電壓暫降監(jiān)測能力指數(shù)作為目標函數(shù),采用離散粒子群算法進行統(tǒng)一優(yōu)化配置,并采用具有先驗信息少、算法簡單、收斂性好等優(yōu)點的最小二乘法作為諧波狀態(tài)估計算法對配置結果進行驗證。對IEEE30節(jié)點標準測試系統(tǒng)進行的仿真計算結果和分析表明所提出方法能夠得到最優(yōu)的電壓暫降監(jiān)測點和最優(yōu)諧波量測點統(tǒng)一配置方案。此外,考慮實際工程情況,文中還對IEEE30節(jié)點進行了欠量測情況下的量測點選擇分析。
[Abstract]:In recent years, people pay more and more attention to the problem of power quality. On the one hand, with the wide application of power electronic technology in power system, more and more harmonics are injected into the power network; on the other hand, with the complexity of various, With more and more applications of precision equipment, the problems brought by voltage sag are becoming more and more prominent. Accurate and effective monitoring is the premise and foundation to find and suppress these power quality problems. It is of great significance to use the information provided by the limited monitoring device to analyze the whole power quality of the whole network. According to the respective characteristics of harmonic and voltage sag, the monitoring points of the two kinds of monitoring points are combined together and configured in a unified manner. An optimal configuration scheme satisfying both of them is obtained. Firstly, a method of optimal configuration of voltage sag monitoring device based on fuzzy control model and particle swarm optimization algorithm is proposed for voltage sag. In this paper, the concepts of fuzzy threshold and observation index are put forward, and the busbar observation ability is considered, and the fuzzy control model is established to obtain the optimized objective function. Then the discrete Particle Swarm Optimization (DPSO) algorithm is used to optimize the configuration of the IEEE30 node test system, and the configuration results are compared with the traditional methods. It is shown that the proposed method can not only realize the complete observability of the voltage sag in the whole network, but also realize the optimal configuration of the monitoring device. On the basis of the completion of the voltage sag monitoring point configuration, the observability analysis and the state estimation method of harmonics are studied. A unified optimal configuration model is established. The observability judgment method of the topology structure of non-harmonic source network is taken as the constraint condition, the voltage sag monitoring capability index is taken as the objective function, and the discrete particle swarm optimization algorithm is used to optimize the configuration. In addition, with little prior information, the algorithm is simple, The least square method with good convergence is used as the harmonic state estimation algorithm to verify the configuration results. The simulation results and analysis of the IEEE30 node standard test system show that the proposed method can obtain the optimal electricity. Unified configuration scheme of pressure sag monitoring points and optimal harmonic measurement points. Considering the actual engineering situation, this paper also analyzes the selection of measuring points for IEEE30 nodes under the condition of under-measurement.
【學位授予單位】：華北電力大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TM933.2;TM935

【參考文獻】

相關期刊論文 前5條

1 楊洪耕,肖先勇,劉俊勇;電能質量問題的研究和技術進展(三)——電力系統(tǒng)的電壓凹陷[J];電力自動化設備;2003年12期

2 劉海濤;韓文新;蘇劍;;電能質量在線綜合監(jiān)測系統(tǒng)[J];電網技術;2006年S2期

3 吳杰;楊陽;盧志剛;;應用粒子群算法的諧波狀態(tài)估計量測點綜合最優(yōu)配置[J];電網技術;2010年09期

4 王艷松;孫桂龍;;基于蟻群算法的配電網諧波量測點優(yōu)化配置[J];中國石油大學學報(自然科學版);2014年01期

5 付聰;沙偉;張海霞;楊亞;;基于差分進化的離散粒子群算法求解TSP問題[J];微處理機;2014年03期

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本文編號：1648710