發(fā)布時間：2018-01-07 00:34

  本文關(guān)鍵詞：基于模糊理論和時間序列分析的開關(guān)柜在線健康狀態(tài)評估與預測輔助系統(tǒng)研究　出處：《安徽師范大學》2016年碩士論文　論文類型：學位論文

  更多相關(guān)文章： 模糊綜合評判法 時間序列分析 狀態(tài)評估與預測 動態(tài)權(quán)重 自適應指數(shù)平滑 在線監(jiān)測

【摘要】：開關(guān)柜作為電網(wǎng)系統(tǒng)中最關(guān)鍵和最復雜的設備之一,在保證電網(wǎng)系統(tǒng)的安全可靠上發(fā)揮著重要作用。但總會因為凝露、局部放電、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,嚴重影響設備的使用壽命,甚至會誘發(fā)重大事故,造成生命財產(chǎn)的損失。從目前開關(guān)柜運行、維護的實際情況看,開關(guān)柜中的很多隱患都不能被實時監(jiān)控,事故發(fā)生后也不能進行取證和重新推演事故發(fā)生過程;另外,在日常運行過程中,尚未對開關(guān)柜的健康狀態(tài)進行科學評估,更未對其狀態(tài)的變化趨勢做適度預測。針對上述問題和需求,本文研究并設計了一套基于模糊理論和時間序列分析的開關(guān)柜在線健康狀態(tài)評估與預測輔助系統(tǒng),對開關(guān)柜的重要運行狀態(tài)參數(shù)進行實時在線監(jiān)測,并根據(jù)實時監(jiān)測到的最新狀態(tài)數(shù)據(jù)對開關(guān)柜的健康狀態(tài)進行全面綜合評估,同時利用系統(tǒng)監(jiān)測采集到的歷史數(shù)據(jù)對開關(guān)柜的狀態(tài)變化趨勢進行預測,實現(xiàn)了對開關(guān)柜的狀態(tài)評估和事故預警,方便了巡檢人員實時了解開關(guān)柜的健康狀態(tài)和發(fā)展趨勢,為設備檢修提供重要的參考信息。首先,基于預警動態(tài)修正權(quán)重的模糊綜合評判法,建立了開關(guān)柜健康狀態(tài)綜合評估模型,實驗結(jié)果表明本文建立的評估模型符合電力行業(yè)的實際標準和需求。然后,基于粒子群優(yōu)化的動態(tài)自適應指數(shù)平滑模型,以開關(guān)柜的歷史監(jiān)測數(shù)據(jù)作為時間序列,建立了開關(guān)柜狀態(tài)變化預測模型。仿真結(jié)果表明該模型較好地把握了開關(guān)柜狀態(tài)變化的趨勢,有助于電力巡檢人員對設備的巡檢。最后,根據(jù)電力行業(yè)對開關(guān)柜實時運行狀態(tài)的需求,設計了一套基于模糊理論和時間序列分析的開關(guān)柜在線健康狀態(tài)評估與預測輔助系統(tǒng)。該系統(tǒng)利用傳感器網(wǎng)絡實現(xiàn)了數(shù)據(jù)采集、存儲、管理、評估與預測一體化,對電網(wǎng)安全可靠運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.
【學位授予單位】：安徽師范大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：O159;O211.61;TM591

【參考文獻】

相關(guān)期刊論文 前10條

1 張樺;魏本剛;李可軍;梁永亮;;基于變壓器馬爾可夫狀態(tài)評估模型和熵權(quán)模糊評價方法的風險評估技術(shù)研究[J];電力系統(tǒng)保護與控制;2016年05期

2 劉麗燕;鄒小燕;;GARCH族模型在電力市場電價預測中的比較研究[J];電力系統(tǒng)保護與控制;2016年04期

3 徐鵬;楊勝春;李峰;馮樹海;王珂;石飛;;基于層次分析和變權(quán)重機制的電網(wǎng)安全指標計算及展示方法[J];電力系統(tǒng)自動化;2015年08期

4 周念成;周川;王強鋼;張靜;李題印;;基于改進拉普拉斯分值的開關(guān)柜故障特征選擇和診斷方法[J];電網(wǎng)技術(shù);2015年03期

5 崔和瑞;彭旭;;基于ARIMAX模型的夏季短期電力負荷預測[J];電力系統(tǒng)保護與控制;2015年04期

6 劉愛國;薛云濤;胡江鷺;劉路平;;基于GA優(yōu)化SVM的風電功率的超短期預測[J];電力系統(tǒng)保護與控制;2015年02期

7 謝靜;束洪春;王科;彭晶;向恩新;;基于模糊分層理論的高壓開關(guān)柜狀態(tài)評估算法[J];高電壓技術(shù);2014年10期

8 李玲;劉成學;;中壓開關(guān)柜內(nèi)部故障電弧計算及防護措施[J];高壓電器;2014年09期

9 謝靜;束洪春;王科;張文英;陳仕龍;馬奎;;基于突變級數(shù)法的高壓開關(guān)柜狀態(tài)評價算法[J];高電壓技術(shù);2014年08期

10 王國權(quán);王森;劉華勇;薛永端;周平;;基于自適應的動態(tài)三次指數(shù)平滑法的風電場風速預測[J];電力系統(tǒng)保護與控制;2014年15期

相關(guān)碩士學位論文 前1條

1 孔杰;變壓器狀態(tài)監(jiān)測與故障診斷系統(tǒng)研究[D];華中科技大學;2006年

，

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