發(fā)布時間：2018-06-18 08:20

  本文選題：輸電線路 + 山火災(zāi)害　； 參考：《電力系統(tǒng)保護與控制》2017年17期

【摘要】：近年來,輸電線路因山火引起的跳閘停電事故越來越多,嚴重影響了電網(wǎng)的安全穩(wěn)定,山火風(fēng)險防控儼然已成為電網(wǎng)防災(zāi)減災(zāi)的重要研究課題�？紤]到輸電線路山火風(fēng)險的影響因素多而復(fù)雜,提出了一種基于BP神經(jīng)網(wǎng)絡(luò)的山火風(fēng)險評估模型。通過研究分析220 k V及以上輸電線路山火災(zāi)害高發(fā)的實際情況,確定山火主要影響因子作為模型的輸入,將山火風(fēng)險等級作為模型的輸出,利用Matlab建立基于BP神經(jīng)網(wǎng)絡(luò)的山火風(fēng)險評估模型。實驗結(jié)果表明該模型能有效地預(yù)測山火風(fēng)險,對及時發(fā)布預(yù)警消息具有重要意義。
[Abstract]:In recent years, there are more and more tripping blackouts caused by hill fire on transmission lines, which seriously affect the safety and stability of power grid. The prevention and control of mountain fire risk has become an important research topic of power grid disaster prevention and mitigation. Considering that there are many and complex factors affecting mountain fire risk in transmission lines, a BP neural network based mountain fire risk assessment model is proposed. By studying and analyzing the actual situation of high incidence of mountain fire disaster on 220 kV and above transmission lines, the main influencing factors of mountain fire are determined as the input of the model, and the risk level of mountain fire is taken as the output of the model. The model of mountain fire risk assessment based on BP neural network is established by Matlab. The experimental results show that the model can effectively predict the mountain fire risk, and it is of great significance to issue early warning information in time.
【作者單位】： 南瑞集團公司(國網(wǎng)電力科學(xué)研究院);國網(wǎng)電力科學(xué)研究院武漢南瑞有限責(zé)任公司;武漢大學(xué)動力與機械學(xué)院;
【分類號】：TM752;TP183

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本文編號：2034814