發(fā)布時(shí)間：2018-01-07 00:34

  本文關(guān)鍵詞：基于模糊理論和時(shí)間序列分析的開(kāi)關(guān)柜在線健康狀態(tài)評(píng)估與預(yù)測(cè)輔助系統(tǒng)研究　出處：《安徽師范大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 模糊綜合評(píng)判法 時(shí)間序列分析 狀態(tài)評(píng)估與預(yù)測(cè) 動(dòng)態(tài)權(quán)重 自適應(yīng)指數(shù)平滑 在線監(jiān)測(cè)

【摘要】：開(kāi)關(guān)柜作為電網(wǎng)系統(tǒng)中最關(guān)鍵和最復(fù)雜的設(shè)備之一,在保證電網(wǎng)系統(tǒng)的安全可靠上發(fā)揮著重要作用。但總會(huì)因?yàn)槟丁⒕植糠烹�、絕緣老化、電弧光以及觸頭發(fā)熱等一系列異常狀況的發(fā)生,嚴(yán)重影響設(shè)備的使用壽命,甚至?xí)T發(fā)重大事故,造成生命財(cái)產(chǎn)的損失。從目前開(kāi)關(guān)柜運(yùn)行、維護(hù)的實(shí)際情況看,開(kāi)關(guān)柜中的很多隱患都不能被實(shí)時(shí)監(jiān)控,事故發(fā)生后也不能進(jìn)行取證和重新推演事故發(fā)生過(guò)程;另外,在日常運(yùn)行過(guò)程中,尚未對(duì)開(kāi)關(guān)柜的健康狀態(tài)進(jìn)行科學(xué)評(píng)估,更未對(duì)其狀態(tài)的變化趨勢(shì)做適度預(yù)測(cè)。針對(duì)上述問(wèn)題和需求,本文研究并設(shè)計(jì)了一套基于模糊理論和時(shí)間序列分析的開(kāi)關(guān)柜在線健康狀態(tài)評(píng)估與預(yù)測(cè)輔助系統(tǒng),對(duì)開(kāi)關(guān)柜的重要運(yùn)行狀態(tài)參數(shù)進(jìn)行實(shí)時(shí)在線監(jiān)測(cè),并根據(jù)實(shí)時(shí)監(jiān)測(cè)到的最新?tīng)顟B(tài)數(shù)據(jù)對(duì)開(kāi)關(guān)柜的健康狀態(tài)進(jìn)行全面綜合評(píng)估,同時(shí)利用系統(tǒng)監(jiān)測(cè)采集到的歷史數(shù)據(jù)對(duì)開(kāi)關(guān)柜的狀態(tài)變化趨勢(shì)進(jìn)行預(yù)測(cè),實(shí)現(xiàn)了對(duì)開(kāi)關(guān)柜的狀態(tài)評(píng)估和事故預(yù)警,方便了巡檢人員實(shí)時(shí)了解開(kāi)關(guān)柜的健康狀態(tài)和發(fā)展趨勢(shì),為設(shè)備檢修提供重要的參考信息。首先,基于預(yù)警動(dòng)態(tài)修正權(quán)重的模糊綜合評(píng)判法,建立了開(kāi)關(guān)柜健康狀態(tài)綜合評(píng)估模型,實(shí)驗(yàn)結(jié)果表明本文建立的評(píng)估模型符合電力行業(yè)的實(shí)際標(biāo)準(zhǔn)和需求。然后,基于粒子群優(yōu)化的動(dòng)態(tài)自適應(yīng)指數(shù)平滑模型,以開(kāi)關(guān)柜的歷史監(jiān)測(cè)數(shù)據(jù)作為時(shí)間序列,建立了開(kāi)關(guān)柜狀態(tài)變化預(yù)測(cè)模型。仿真結(jié)果表明該模型較好地把握了開(kāi)關(guān)柜狀態(tài)變化的趨勢(shì),有助于電力巡檢人員對(duì)設(shè)備的巡檢。最后,根據(jù)電力行業(yè)對(duì)開(kāi)關(guān)柜實(shí)時(shí)運(yùn)行狀態(tài)的需求,設(shè)計(jì)了一套基于模糊理論和時(shí)間序列分析的開(kāi)關(guān)柜在線健康狀態(tài)評(píng)估與預(yù)測(cè)輔助系統(tǒng)。該系統(tǒng)利用傳感器網(wǎng)絡(luò)實(shí)現(xiàn)了數(shù)據(jù)采集、存儲(chǔ)、管理、評(píng)估與預(yù)測(cè)一體化,對(duì)電網(wǎng)安全可靠運(yùn)行起到了輔助決策的作用。
[Abstract]:As one of the most important and complex equipments in power system, switchgear plays an important role in ensuring the safety and reliability of power system. However, it is always due to condensation, partial discharge, insulation aging. The occurrence of a series of abnormal conditions, such as arc light and contact heating, seriously affects the service life of the equipment, and even causes serious accidents, resulting in the loss of life and property. The actual situation of maintenance, many hidden dangers in the switchgear can not be real-time monitoring, after the accident can not be obtained evidence and re-extrapolation of the accident process; In addition, in the course of daily operation, the health status of switchgear has not been scientifically evaluated, and the change trend of its state has not been properly predicted. Based on fuzzy theory and time series analysis, a set of on-line health evaluation and prediction assistant system for switchgear is studied and designed in this paper, and real-time on-line monitoring of important operating state parameters of switchgear is carried out. According to the latest state data of real-time monitoring, the health status of switchgear is comprehensively evaluated, and the trend of state change of switchgear is forecasted by using the historical data collected by system monitoring. It realizes the state evaluation and accident warning of switchgear, facilitates the inspectors to understand the health status and development trend of switchgear in real time, and provides important reference information for equipment maintenance. Based on the fuzzy comprehensive evaluation method of dynamic modification weight of early warning, a comprehensive assessment model of switchgear health state is established. The experimental results show that the evaluation model established in this paper accords with the actual standards and needs of the power industry. Then. A dynamic adaptive exponential smoothing model based on particle swarm optimization (PSO) is proposed. The historical monitoring data of switchgear are used as time series. The simulation results show that the model has a good grasp of the state change trend of the switchgear, which is helpful for the inspection of the equipment by the power inspector. Finally, the simulation results show that the model has a good understanding of the trend of the state change of the switchgear. According to the needs of the power industry to the real-time operation of switchgear. Based on fuzzy theory and time series analysis, an on-line health evaluation and prediction assistant system for switchgear is designed, which realizes data acquisition, storage and management by using sensor network. The integration of evaluation and prediction plays an auxiliary role in power grid safe and reliable operation.
【學(xué)位授予單位】：安徽師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：O159;O211.61;TM591

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本文編號(hào)：1390220