發(fā)布時間：2018-04-20 21:05

  本文選題：小電流接地系統(tǒng) + 故障選線�。� 參考：《中國礦業(yè)大學(xué)》2014年碩士論文

【摘要】：小電流接地系統(tǒng)單相接地故障選線一直是配電網(wǎng)中的重點和難點。當前，雖然各種選線裝置層出不窮，但是選線效果甚微。究其原因，主要是單一的選線方法有其局限性，難以滿足復(fù)雜多變工況下的選線要求，選線精度較低。因此，融合多種選線原理進行選線是未來發(fā)展的趨勢。本文就是結(jié)合神經(jīng)網(wǎng)絡(luò)算法和D-S證據(jù)理論融合多種故障選線原理，對小電流接地系統(tǒng)單相接地故障選線進行深入的研究，，以提高配電網(wǎng)故障選線的精度，改善供電質(zhì)量。 首先，本文介紹了小電流接地系統(tǒng)單相接地故障選線這一領(lǐng)域在國內(nèi)外的研究現(xiàn)狀，介紹了當前主流的選線原理與選線方法，并進行了相應(yīng)的Matlab/Simulink仿真模型的搭建，同時在模型的基礎(chǔ)上進行基于傳統(tǒng)故障選線方法的仿真，為文中后半部分的選線原理的融合打下扎實的理論基礎(chǔ)。同時，大量的仿真數(shù)據(jù)可以為日后的融合驗證提供數(shù)據(jù)保障。 其次，本文根據(jù)穩(wěn)態(tài)及暫態(tài)特征量的特點，構(gòu)造故障測度函數(shù)，以處理仿真得到的各項數(shù)據(jù)，作為融合算法的輸入值。接著，簡單介紹了BP神經(jīng)網(wǎng)絡(luò)、基于遺傳算法優(yōu)化的BP神經(jīng)網(wǎng)絡(luò)以及D-S證據(jù)理論，將小電流接地系統(tǒng)故障選線同上述智能算法進行結(jié)合，使智能算法與實際問題相結(jié)合來解決這一難題。 最后，利用具體算例來詳細介紹本文所提出的基于遺傳算法優(yōu)化的BP神經(jīng)網(wǎng)絡(luò)以及D-S證據(jù)理論雙融合算法，通過仿真實例來介紹該方法的優(yōu)越性和選線的高精度。驗證結(jié)果說明,該算法相比其他選線方法更有優(yōu)勢。
[Abstract]:Single-phase grounding fault line selection in low-current grounding system has always been the focus and difficulty in distribution network. At present, although a variety of line selection devices emerge in endlessly, but the effect of line selection is very little. The main reason is that the single route selection method has its limitations, it is difficult to meet the requirements of complex and changeable working conditions, and the accuracy of line selection is low. Therefore, it is the trend of future development to combine various principles of line selection. Combined with neural network algorithm and D-S evidence theory, this paper studies the single-phase grounding fault line selection of small current grounding system in order to improve the accuracy of fault line selection and improve the quality of power supply. Firstly, this paper introduces the research status of single-phase grounding fault line selection in small current grounding system at home and abroad, introduces the current mainstream line selection principle and method, and builds the corresponding Matlab/Simulink simulation model. At the same time, the simulation based on the traditional fault line selection method is carried out on the basis of the model, which lays a solid theoretical foundation for the fusion of the line selection principle in the second half of the paper. At the same time, a lot of simulation data can provide data guarantee for future fusion verification. Secondly, according to the characteristics of steady-state and transient characteristic variables, the fault measure function is constructed to process the simulated data as the input value of the fusion algorithm. Then, the BP neural network, based on BP neural network optimized by genetic algorithm and D-S evidence theory, is introduced briefly. The fault line selection of small current grounding system is combined with the intelligent algorithm mentioned above. The intelligent algorithm is combined with the practical problem to solve this problem. Finally, the BP neural network based on genetic algorithm optimization and the double fusion algorithm of D-S evidence theory proposed in this paper are introduced in detail by a concrete example. The superiority of the method and the high accuracy of line selection are introduced by a simulation example. The results show that the algorithm has more advantages than other routing methods.
【學(xué)位授予單位】：中國礦業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TM862

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本文編號：1779427