本文選題：電網(wǎng)故障診斷 + Petri網(wǎng)��； 參考：《南京理工大學》2017年碩士論文

【摘要】：隨著電網(wǎng)的規(guī)模不斷擴大,不同區(qū)域間的互聯(lián)越來越緊密,當電網(wǎng)發(fā)生故障時,故障對系統(tǒng)的影響將越來越大�，F(xiàn)有電網(wǎng)故障診斷方法多是基于斷路器跳閘、保護動作等開關量信息。然而,這種利用某種智能算法對開關量進行處理得到故障診斷結(jié)果的方式,對斷路器與保護信息的完整性與準確性具有很高的要求,不同程度的完整性與準確性對診斷結(jié)果具有很大影響。.本文研究了利用多數(shù)據(jù)源信息進行電網(wǎng)故障診斷的方法。首先介紹了課題的研究背景以及國內(nèi)外的發(fā)展現(xiàn)狀;其次,介紹了目前電網(wǎng)故障診斷的各種故障信息源;接下來本文對基于開關量信息的電網(wǎng)故障診斷進行分析,針對現(xiàn)有Petri網(wǎng)診斷模型的網(wǎng)絡適應性與不確定信息容錯性問題,提出時序加權模糊有色Petri網(wǎng)電網(wǎng)故障診斷模型;同時,本文對基于電氣量信息的電網(wǎng)故障診斷進行分析,針對HHT對故障電流分析時出現(xiàn)的過包絡與欠包絡現(xiàn)象,提出一種改進的經(jīng)驗模態(tài)分解方式,從而改進HHT得到更為準確的診斷結(jié)果;在上述方法的基礎上,本文提出基于D-S證據(jù)理論的電網(wǎng)故障診斷融合模型和基于改進C均值算法的診斷決策模型;最后,基于Matlab仿真分析軟件,通過綜合算例仿真分析來驗證本文所提出方法的有效性。
[Abstract]:With the continuous expansion of the scale of the power grid, the interconnection between different regions is becoming more and more close. When the power network fails, the influence of the fault on the system will become more and more serious. Most of the existing fault diagnosis methods are based on switching information such as circuit breaker tripping, protection operation and so on. However, the method of using some intelligent algorithm to process the switch quantity to get the fault diagnosis result has high requirements for the integrity and accuracy of the information of circuit breaker and protection. Different degrees of completeness and accuracy have great influence on the diagnosis results. In this paper, the method of fault diagnosis based on multiple data sources is studied. Firstly, it introduces the research background and the development status at home and abroad; secondly, it introduces the various fault information sources of current power network fault diagnosis; then, this paper analyzes the power network fault diagnosis based on switch quantity information. Aiming at the problem of network adaptability and fault tolerance of uncertain information in existing Petri net diagnosis model, a time-series weighted fuzzy colored Petri net fault diagnosis model is proposed, and the fault diagnosis model based on electrical information is analyzed in this paper. An improved empirical mode decomposition (EMD) method is proposed to solve the overenvelope and underenvelope phenomena in the fault current analysis of HHT, which improves the HHT to get more accurate diagnosis results. In this paper, a fault diagnosis fusion model based on D-S evidence theory and a diagnosis decision model based on improved C-means algorithm are proposed. The effectiveness of the proposed method is verified by a comprehensive example.
【學位授予單位】：南京理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM711

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