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基于邊緣計算的變電站風(fēng)險預(yù)警管控系統(tǒng)設(shè)計
2023年電子技術(shù)應(yīng)用第4期
莊莉1,劉寶升2,王秋琳1,呂君玉1,陳桂良1
(1.福建億榕信息技術(shù)有限公司,福建 福州350001;2.國家電網(wǎng)有限公司,北京 100031)
摘要: 為實(shí)現(xiàn)變電站風(fēng)險預(yù)警的實(shí)多維度管控,設(shè)計基于邊緣計算的變電站風(fēng)險預(yù)警管控系統(tǒng)。感知層通過物聯(lián)網(wǎng)設(shè)備采集變電站設(shè)備的運(yùn)行相關(guān)數(shù)據(jù),利用邊緣設(shè)備和外部設(shè)備之間的通信傳送數(shù)據(jù)至邊緣層;邊緣層接收數(shù)據(jù)后,通過通信協(xié)議解析該數(shù)據(jù),完成數(shù)據(jù)的一致性,包裝云服務(wù)下行數(shù)據(jù)傳送至云計算層;云計算層利用云計算計算和分析變電站設(shè)備數(shù)據(jù)并傳送至應(yīng)用層;應(yīng)用層采用支持向量機(jī)算法建立風(fēng)險預(yù)警機(jī)制劃分風(fēng)險數(shù)據(jù)的屬性、獲取預(yù)警值,在此基礎(chǔ)上,通過Logistic回歸風(fēng)險預(yù)測模型預(yù)測預(yù)警值對應(yīng)的風(fēng)險情況,得出故障發(fā)生概率完成變電站風(fēng)險預(yù)警,同時將預(yù)警結(jié)果呈現(xiàn)在可視化界面,并由控制通道管控相應(yīng)的風(fēng)險預(yù)警。測試結(jié)果顯示:系統(tǒng)的通信抖動結(jié)果均在15 ms以下,能夠?qū)崿F(xiàn)風(fēng)險概率的計算,獲取變電站各類風(fēng)險預(yù)警數(shù)量,具備良好的工作能效,能多維度實(shí)現(xiàn)變電站風(fēng)險預(yù)警管控。
中圖分類號:TP273
文獻(xiàn)標(biāo)志碼:A
DOI: 10.16157/j.issn.0258-7998.222968
中文引用格式: 莊莉,劉寶升,王秋琳,等. 基于邊緣計算的變電站風(fēng)險預(yù)警管控系統(tǒng)設(shè)計[J]. 電子技術(shù)應(yīng)用,2023,49(4):92-97.
英文引用格式: Zhuang Li,Liu Baosheng,Wang Qiulin,et al. Design of substation risk early warning and control system based on edge calculation[J]. Application of Electronic Technique,2023,49(4):92-97.
Design of substation risk early warning and control system based on edge calculation
Zhuang Li1,Liu Baosheng2,Wang Qiulin1,Lv Junyu1,Chen Guiliang1
(1.Fujian YiRong Information Technology Co., Ltd., Fuzhou 350001,China;2.State Grid Co., Ltd., Beijing 100031,China)
Abstract: In order to realize real-time and multi-dimensional control of substation risk early warning, a substation risk early warning and control system based on edge computing is designed. The sensing layer collects the operation data of substation equipment through the Internet of Things equipment, and transmits the data to the edge layer through the communication between edge equipment and external equipment. After receiving data, edge layer parses the data through the communication protocol to complete data consistency, and packages cloud services downstream data sending to the cloud computing layer. The layer uses cloud computing to compute and analyze substation equipment data and transmit it to the application layer. The application layer adopts support vector machine (SVM) algorithm to establish a risk early warning mechanism, divide the risk data attribute, and obtain warning value. Based on this, the risk situation corresponding to the early warning value is predicted by the logistic regression risk prediction model, and the probability of failure is obtained to complete the substation risk warning. Meanwhile, the early warning results are presented on the visual interface, and the corresponding risk warning is controlled and controlled by the control channel. The test results show that the communication jitter results of the system are all below 15 ms, which can realize the calculation of risk probability, obtain the number of various risk warnings of the substation, have good work energy efficiency, and realize the multi-dimensional risk warning and control of the substation.
Key words : edge calculation;substation;risk warning and control;risk warning mechanism;data analysis;the early warning value

0 引言

電力系統(tǒng)中用于完成電力能源接收和分配的場所稱為變電站,由一類和二類設(shè)備組成其可完成電網(wǎng)中電壓和電流的變換,按照電壓的等級對其分類,可將其分為四類。由于變電站的結(jié)構(gòu)較為復(fù)雜,因此電力企業(yè)在對變電站實(shí)行管理過程中,為保證變電站的運(yùn)行安全,安全監(jiān)控則是主要手段。并且變電站在安全管控過程中存在突發(fā)性、未知性,因此,導(dǎo)致對變電站風(fēng)險因素的變動趨勢掌控存在一定不足,其風(fēng)險預(yù)警則產(chǎn)生一定的不確定性。邊緣計算是一種能夠提供最近端服務(wù)的技術(shù),其可在邊緣側(cè)發(fā)起應(yīng)用程序,實(shí)現(xiàn)網(wǎng)絡(luò)服務(wù)的快速相應(yīng),滿足業(yè)務(wù)的實(shí)時、智能應(yīng)用以及安全保護(hù)等需求。

周敬嵩等人和楊至元等人針對變電站安全管控過程中存在的問題,分別對變電站的安全管控實(shí)行分析后,基于移動式紅外測溫、基于Cyber-net與學(xué)習(xí)算法分別研究變電站的安全管控方法。上述方法在管控過程中,僅在變電站設(shè)備溫度預(yù)警、故障預(yù)警方面具備較好效果,但是無法完成微小風(fēng)險的提前預(yù)防,實(shí)現(xiàn)多維度風(fēng)險預(yù)警。因此,本文設(shè)計基于邊緣計算的變電站風(fēng)險預(yù)警管控系統(tǒng),結(jié)合邊緣計算和云計算的優(yōu)勢,實(shí)現(xiàn)變電站風(fēng)險預(yù)警管控。



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作者信息:

莊莉1,劉寶升2,王秋琳1,呂君玉1,陳桂良1

(1.福建億榕信息技術(shù)有限公司,福建 福州350001;2.國家電網(wǎng)有限公司,北京 100031)


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