面向電網(wǎng)監(jiān)測(cè)的無(wú)線傳感器網(wǎng)絡(luò)關(guān)鍵技術(shù)研究

李 婧, 溫 蜜, 薛 梅

(上海電力學(xué)院 計(jì)算機(jī)科學(xué)與技術(shù)學(xué)院, 上海 200090)

面向電網(wǎng)監(jiān)測(cè)的無(wú)線傳感器網(wǎng)絡(luò)關(guān)鍵技術(shù)研究

李 婧, 溫 蜜, 薛 梅

(上海電力學(xué)院 計(jì)算機(jī)科學(xué)與技術(shù)學(xué)院, 上海 200090)

電網(wǎng)監(jiān)測(cè)的WSN中存在網(wǎng)絡(luò)路由路徑單一、負(fù)載不均衡、生命周期短和可維護(hù)性差等問(wèn)題,因此引入局部壓縮感知和低占空比機(jī)制對(duì)其網(wǎng)絡(luò)性能進(jìn)行優(yōu)化.對(duì)面向電網(wǎng)監(jiān)測(cè)的無(wú)線傳感器網(wǎng)絡(luò)中存在的關(guān)鍵技術(shù)進(jìn)行了詳細(xì)分析,并具體闡述了國(guó)內(nèi)外對(duì)于該領(lǐng)域的研究現(xiàn)狀及進(jìn)展,提出針對(duì)局部壓縮感知數(shù)據(jù)的有效恢復(fù)、低占空比機(jī)制中精確時(shí)間同步、電網(wǎng)監(jiān)測(cè)環(huán)境下傳感器網(wǎng)絡(luò)的最優(yōu)化配置等3個(gè)關(guān)鍵問(wèn)題的研究,可以延長(zhǎng)電網(wǎng)監(jiān)測(cè)WSN的整體生存時(shí)間,為電網(wǎng)監(jiān)測(cè)提供有QoS保證的數(shù)據(jù)采集與傳輸,推動(dòng)WSN在電力系統(tǒng)成功應(yīng)用.

壓縮感知; 電網(wǎng)監(jiān)測(cè); 無(wú)線傳感器網(wǎng)絡(luò); 低占空比

隨著智能電網(wǎng)建設(shè)規(guī)模的不斷增加,系統(tǒng)的復(fù)雜性不斷提高,加之自然災(zāi)害頻繁發(fā)生,電網(wǎng)的安全運(yùn)行和電力供應(yīng)的可靠性變得尤為重要.傳統(tǒng)的電網(wǎng)輸電線路安全主要依靠人力巡檢,運(yùn)行效率低,周期長(zhǎng),更缺乏實(shí)時(shí)的監(jiān)測(cè)手段,無(wú)法反映線路的真實(shí)狀態(tài).電網(wǎng)的輸電線路監(jiān)測(cè)具有分散性大、距離長(zhǎng)、難以維護(hù)等特點(diǎn),對(duì)于很多布置在偏遠(yuǎn)山區(qū)的輸電塔,采用有線網(wǎng)絡(luò)傳輸方式的施工成本高,線路布局困難而難以實(shí)現(xiàn).而無(wú)線傳感器網(wǎng)絡(luò)(Wireless Sensor Network,WSN)技術(shù)的發(fā)展,使電網(wǎng)輸電線路狀態(tài)的實(shí)時(shí)監(jiān)測(cè)成為現(xiàn)實(shí),從而使電網(wǎng)運(yùn)行于可視可控之中.

采用無(wú)線傳感器網(wǎng)絡(luò)對(duì)高壓輸電線路的監(jiān)測(cè)主要包括輸電線路的溫度監(jiān)測(cè)、絕緣子漏電監(jiān)測(cè)、線路覆冰監(jiān)測(cè)、輸電塔的傾斜度監(jiān)測(cè)，以及塔邊的風(fēng)速和雨量等氣象信息監(jiān)測(cè).對(duì)電網(wǎng)的輸電線路進(jìn)行實(shí)時(shí)的狀態(tài)數(shù)據(jù)采集,為電網(wǎng)的管理人員提供更全面、完整的電網(wǎng)運(yùn)行數(shù)據(jù),有助于確定決策系統(tǒng)控制實(shí)施方案和應(yīng)對(duì)預(yù)案,提高電力系統(tǒng)的運(yùn)行效率,及時(shí)發(fā)現(xiàn)故障隱患,提高輸電可靠性,保障電網(wǎng)的運(yùn)行安全.

與一般WSN不同,面向電網(wǎng)監(jiān)測(cè)的WSN具有節(jié)點(diǎn)局部密集、感知數(shù)據(jù)稀疏、網(wǎng)絡(luò)維護(hù)困難等特點(diǎn),因此很多問(wèn)題更突出,如路由路徑單一、負(fù)載不均衡、網(wǎng)絡(luò)生命周期短、可維護(hù)性和可靠性差等.

根據(jù)以上電網(wǎng)監(jiān)測(cè)WSN的特點(diǎn),為了確保電網(wǎng)監(jiān)測(cè)數(shù)據(jù)的實(shí)時(shí)傳輸,需要建立穩(wěn)定可靠的無(wú)線傳感器網(wǎng)絡(luò),本文擬將壓縮感知(Compressed Sensing,CS)概念[1]和低占空比(Low-Duty-Cycle)機(jī)制[2]引入電網(wǎng)監(jiān)測(cè)的WSN,對(duì)其網(wǎng)絡(luò)性能進(jìn)行優(yōu)化.根據(jù)CS理論,只要信號(hào)在某些基上能稀疏表示,就可以通過(guò)少量隨機(jī)線性觀測(cè)值來(lái)重構(gòu)該信號(hào).而我們所提出的局部壓縮感知(Regional Compressed Sensing,RCS)是指在無(wú)線傳感器網(wǎng)絡(luò)監(jiān)控的場(chǎng)景中劃分可重疊區(qū)域,某個(gè)特定的傳感器可以從屬于兩個(gè)或兩個(gè)以上區(qū)域,屬于一個(gè)區(qū)域的傳感器節(jié)點(diǎn)將采用壓縮感知的方式向數(shù)據(jù)采集點(diǎn)發(fā)送數(shù)據(jù).因此,將局部壓縮感知技術(shù)引入的目的是在獲得顯著數(shù)據(jù)壓縮效果的同時(shí),解決“熱點(diǎn)”現(xiàn)象問(wèn)題,從而大大降低數(shù)據(jù)處理的算法復(fù)雜度和能量消耗,延長(zhǎng)網(wǎng)絡(luò)的整體生存時(shí)間.而采用Low-Duty-Cycle的傳感器節(jié)點(diǎn)會(huì)階段性地睡眠,節(jié)點(diǎn)處于睡眠狀態(tài)時(shí),會(huì)關(guān)閉其他所有的功能模塊,僅留下一個(gè)計(jì)時(shí)器,以備將來(lái)喚醒自己.一旦醒來(lái),即可與鄰節(jié)點(diǎn)進(jìn)行數(shù)據(jù)的發(fā)送和接收.該模式減少了節(jié)點(diǎn)監(jiān)聽(tīng)的時(shí)間,從而減少了相應(yīng)的功率消耗,達(dá)到了有效節(jié)約節(jié)點(diǎn)能量的目的.

采用局部壓縮感知和Low-Duty-Cycle機(jī)制,對(duì)面向電網(wǎng)監(jiān)測(cè)的無(wú)線傳感器網(wǎng)絡(luò)性能進(jìn)行優(yōu)化,不僅能延長(zhǎng)無(wú)線傳感器網(wǎng)絡(luò)的生存時(shí)間,而且能為電網(wǎng)監(jiān)測(cè)提供有QoS保證的數(shù)據(jù)采集與傳輸服務(wù),這對(duì)WSN在電力系統(tǒng)的成功應(yīng)用起到有效的推動(dòng)作用.

1 面臨的挑戰(zhàn)

由于面向電網(wǎng)監(jiān)測(cè)的無(wú)線傳感器網(wǎng)絡(luò)具有特殊性,我們采用局部壓縮感知和Low-Duty-Cycle機(jī)制對(duì)其性能進(jìn)行優(yōu)化,可以在保證節(jié)點(diǎn)數(shù)據(jù)采集率的前提下,盡可能節(jié)約能量,解決“熱點(diǎn)”現(xiàn)象問(wèn)題,提高網(wǎng)絡(luò)的生存周期,優(yōu)化網(wǎng)絡(luò)的配置.但這也給面向電網(wǎng)監(jiān)測(cè)的無(wú)線傳感器網(wǎng)絡(luò)帶來(lái)了新的技術(shù)難題,提出了不少挑戰(zhàn)性問(wèn)題.

(1) 電網(wǎng)監(jiān)測(cè)WSN的局部壓縮感知數(shù)據(jù)有效恢復(fù)困難.現(xiàn)有的研究表明,使用局部壓縮感知可以有效提高網(wǎng)絡(luò)的數(shù)據(jù)采集率,延長(zhǎng)網(wǎng)絡(luò)生存時(shí)間.基于該理論,可以利用電網(wǎng)監(jiān)測(cè)WSN感知數(shù)據(jù)的稀疏特性,在遠(yuǎn)小于Nyquist采樣率的條件下,用隨機(jī)采樣的方式獲取感知數(shù)據(jù)的離散樣本,然后通過(guò)非線性算法重構(gòu)感知數(shù)據(jù).采用局部壓縮感知技術(shù),大幅減少了每個(gè)節(jié)點(diǎn)發(fā)送的感知數(shù)據(jù)包數(shù)量,降低了sink附近節(jié)點(diǎn)的能量消耗,并且每個(gè)中間結(jié)點(diǎn)只需做簡(jiǎn)單的線性運(yùn)算,大大降低了數(shù)據(jù)處理的算法復(fù)雜度和能量消耗.但此方法只對(duì)一維網(wǎng)絡(luò)有效,而對(duì)于最常見(jiàn)的二維網(wǎng)絡(luò),卻無(wú)法在感知數(shù)據(jù)包發(fā)送數(shù)量不變的前提下,保證感知數(shù)據(jù)的有效恢復(fù).在電網(wǎng)監(jiān)測(cè)環(huán)境下,絕大多數(shù)都是二維或三維網(wǎng)絡(luò),如何針對(duì)電網(wǎng)監(jiān)測(cè)無(wú)線傳感器網(wǎng)絡(luò),提出有效的感知數(shù)據(jù)恢復(fù)方法,是一個(gè)全新的技術(shù)難題.

(2) Low-Duty-Cycle機(jī)制下,WSN的精確時(shí)鐘同步問(wèn)題.在采用Low-Duty-Cycle的無(wú)線傳感器網(wǎng)絡(luò)中,為避免數(shù)據(jù)發(fā)送失敗或傳輸延遲過(guò)大,鄰居節(jié)點(diǎn)間的同步是一個(gè)必要條件.傳統(tǒng)的時(shí)間同步是通過(guò)廣播消息來(lái)對(duì)多個(gè)接收者進(jìn)行時(shí)間漂移的補(bǔ)償,但是在Low-Duty-Cycle機(jī)制中,廣播的方式將不起作用,需要研究適合Low-Duty-Cycle模式下WSN的時(shí)間同步協(xié)議.另外,電網(wǎng)監(jiān)測(cè)WSN對(duì)時(shí)鐘同步精確度有很高的要求,需要在設(shè)計(jì)時(shí)鐘同步機(jī)制的同時(shí),考慮各種因素(包括電網(wǎng)監(jiān)測(cè)的應(yīng)用場(chǎng)景等)對(duì)時(shí)鐘同步的影響,以提高同步的精確度.在Low-Duty-Cycle機(jī)制中,如何實(shí)現(xiàn)精確的時(shí)鐘同步,是電網(wǎng)監(jiān)測(cè)WSN有待解決的一個(gè)重要問(wèn)題.

(3) 在電網(wǎng)監(jiān)測(cè)環(huán)境下,如何解決沖突,實(shí)現(xiàn)WSN的最優(yōu)化配置.在電網(wǎng)監(jiān)測(cè)WSN中,采用局部壓縮感知和Low-Duty-Cycle機(jī)制,實(shí)現(xiàn)網(wǎng)絡(luò)的最優(yōu)化配置,存在一些沖突.首先,基于局部壓縮感知的電網(wǎng)監(jiān)測(cè)WSN,網(wǎng)絡(luò)吞吐量和時(shí)延存在沖突.有研究表明,大規(guī)模網(wǎng)絡(luò)吞吐量的提高會(huì)導(dǎo)致網(wǎng)絡(luò)時(shí)延的增加[3],二者之間的關(guān)系如何變化尚不明確.其次,在Low-Duty-Cycle機(jī)制中,如何設(shè)置合適的占空比,仍然是一個(gè)富有挑戰(zhàn)性的問(wèn)題.如果將占空比設(shè)置過(guò)低,當(dāng)節(jié)點(diǎn)在較短的活躍時(shí)間段內(nèi)醒來(lái)時(shí),可能會(huì)出現(xiàn)多個(gè)傳感器節(jié)點(diǎn)同時(shí)向該節(jié)點(diǎn)發(fā)送數(shù)據(jù)的情況,從而引起數(shù)據(jù)包沖突.而且需要花費(fèi)更長(zhǎng)的時(shí)間等待網(wǎng)絡(luò)形成一個(gè)期望的拓?fù)浣Y(jié)構(gòu)來(lái)提供常見(jiàn)的網(wǎng)絡(luò)操作,這也使得系統(tǒng)對(duì)于監(jiān)測(cè)事件和事故的響應(yīng)時(shí)間變長(zhǎng).如果將占空比設(shè)置過(guò)高,雖然可以保證網(wǎng)絡(luò)的傳輸性能,但無(wú)法兼顧節(jié)能的目的.同時(shí),還會(huì)造成網(wǎng)絡(luò)通信負(fù)載的不均衡分配,導(dǎo)致網(wǎng)絡(luò)的生存時(shí)間縮短.因此,針對(duì)上述沖突問(wèn)題進(jìn)行研究,實(shí)現(xiàn)傳感器網(wǎng)絡(luò)的最優(yōu)化配置,使得電網(wǎng)監(jiān)測(cè)無(wú)線傳感器網(wǎng)絡(luò)既能使生存時(shí)間得以延長(zhǎng),又能保證良好的網(wǎng)絡(luò)性能,這是電網(wǎng)監(jiān)測(cè)WSN能夠成功實(shí)施的關(guān)鍵.

2 國(guó)內(nèi)外研究現(xiàn)狀及發(fā)展動(dòng)態(tài)

近幾年,國(guó)內(nèi)外針對(duì)電網(wǎng)監(jiān)測(cè)的無(wú)線傳感器網(wǎng)絡(luò)進(jìn)行了一些研究,提出了不同的實(shí)現(xiàn)思路和應(yīng)用模型,并取得了一定的研究成果.文獻(xiàn)[4]設(shè)計(jì)了一個(gè)電網(wǎng)輸電線路監(jiān)測(cè)無(wú)線傳感器網(wǎng)絡(luò)的分層通信拓?fù)浣Y(jié)構(gòu),并對(duì)采集數(shù)據(jù)進(jìn)行多信息集成和融合,從而實(shí)現(xiàn)了對(duì)輸電線路故障的實(shí)時(shí)監(jiān)測(cè).文獻(xiàn)[5]在抄表系統(tǒng)中利用無(wú)線傳感器網(wǎng)絡(luò) ZigBee技術(shù),完成了無(wú)線遠(yuǎn)程集中抄表功能.文獻(xiàn)[6]提出了一種基于無(wú)線傳感器網(wǎng)絡(luò)的配電線路故障定位算法,運(yùn)用配電線路故障定位原理實(shí)現(xiàn)故障的精確定位.文獻(xiàn)[7]構(gòu)建了一套基于無(wú)線傳感器網(wǎng)絡(luò)的冰災(zāi)監(jiān)測(cè)預(yù)警機(jī)制.

2.1 基于壓縮感知的無(wú)線傳感器網(wǎng)絡(luò)技術(shù)研究進(jìn)展

以上研究成果中所提出的壓縮感知技術(shù)主要針對(duì)一維(線狀)的WSN有效,而對(duì)于二維WSN的性能提高不一定有效.這是由于二維WSN的數(shù)據(jù)采集節(jié)點(diǎn)有多個(gè)鄰居節(jié)點(diǎn)(假設(shè)為a個(gè)),如果每個(gè)節(jié)點(diǎn)都發(fā)送M個(gè)數(shù)據(jù)包,那么數(shù)據(jù)采集節(jié)點(diǎn)將收到aM個(gè)數(shù)據(jù)包,而aM有可能大于N.若面向電網(wǎng)監(jiān)測(cè)的WSN是二維或三維網(wǎng)絡(luò),則無(wú)法直接運(yùn)用已有的研究成果.

2.2 基于Low-Duty-Cycle機(jī)制的無(wú)線傳感器網(wǎng)絡(luò)技術(shù)研究進(jìn)展

目前,國(guó)內(nèi)外研究者針對(duì)Low-Duty-Cycle無(wú)線傳感器網(wǎng)絡(luò)的研究工作主要集中在節(jié)能高效網(wǎng)絡(luò)的設(shè)計(jì)、生存時(shí)間最大化等方面.由于能源的有限性和高需求之間的矛盾越來(lái)越明顯,研究者已經(jīng)開(kāi)始認(rèn)識(shí)到在Low-Duty-Cycle無(wú)線傳感器網(wǎng)絡(luò)中保持較低的占空比的重要性.文獻(xiàn)[18]提出了一種廣播傳輸方法,其中傳輸過(guò)程是根據(jù)接收者的控制消息所標(biāo)明的信息進(jìn)行調(diào)度.文獻(xiàn)[19]采用投機(jī)性的Flooding機(jī)制,實(shí)現(xiàn)了延遲和能源方面的高效率.文獻(xiàn)[20]提出了一種Flooding方案,從而減少了能源消耗.文獻(xiàn)[21]設(shè)計(jì)了一個(gè)動(dòng)態(tài)數(shù)據(jù)包轉(zhuǎn)發(fā)機(jī)制,優(yōu)化了采集數(shù)據(jù)時(shí)消耗的能量.文獻(xiàn)[22]提出了Dutycon來(lái)實(shí)現(xiàn)動(dòng)態(tài)的占空比控制,從而獲得端到端的延遲最小化.文獻(xiàn)[23]研究了Low-Duty-Cycle傳感器網(wǎng)絡(luò)中的多任務(wù)調(diào)度問(wèn)題,提出了一種包含性能分析的近似算法,針對(duì)實(shí)際網(wǎng)絡(luò)設(shè)計(jì)了一種分布式的任務(wù)調(diào)度協(xié)議.

Tiny-sync算法[24]和mini-sync同步算法[25]是兩個(gè)輕量的時(shí)間同步算法,通過(guò)交換少量的消息就能夠提供具有確定誤差上界的頻偏和相偏.這兩個(gè)算法的前提假設(shè)是,節(jié)點(diǎn)的時(shí)間是“真實(shí)時(shí)間”的線性變化,它的時(shí)鐘偏移和相偏不變,這對(duì)于需要長(zhǎng)期監(jiān)測(cè)的無(wú)線傳感器網(wǎng)絡(luò)來(lái)說(shuō),很難保證.文獻(xiàn)[26]研究了Low-Duty-Cycle傳感器網(wǎng)絡(luò)的時(shí)間同步精度.還有很多工作致力于解決時(shí)鐘不確定性以及縮減時(shí)鐘同步代價(jià),如在文獻(xiàn)[27]中,引入了按需精確同步的思想;文獻(xiàn)[28]開(kāi)發(fā)出溫度補(bǔ)償機(jī)制來(lái)緩和時(shí)鐘偏移問(wèn)題;文獻(xiàn)[29]通過(guò)在每個(gè)節(jié)點(diǎn)上使用兩個(gè)不同精度的時(shí)鐘來(lái)維持一個(gè)共同的時(shí)間.

以上有關(guān)時(shí)鐘同步協(xié)議的研究成果,沒(méi)有考慮內(nèi)部和外部網(wǎng)絡(luò)因素對(duì)無(wú)線傳感器網(wǎng)絡(luò)的影響,同時(shí)也未探討如何設(shè)計(jì)和實(shí)施有效的QoS保證協(xié)議,更沒(méi)有涉及電網(wǎng)監(jiān)測(cè)應(yīng)用場(chǎng)景對(duì)時(shí)鐘同步的影響.因此,無(wú)法解決電網(wǎng)監(jiān)測(cè)Low-Duty-Cycle無(wú)線傳感器網(wǎng)絡(luò)精確時(shí)鐘同步問(wèn)題.

2.3 無(wú)線傳感器網(wǎng)絡(luò)的最優(yōu)化配置技術(shù)研究進(jìn)展

為了提高Low-Duty-Cycle網(wǎng)絡(luò)的生命周期性,文獻(xiàn)[30]提出了兩種算法,通過(guò)使用動(dòng)態(tài)的sink來(lái)進(jìn)行數(shù)據(jù)采集.文獻(xiàn)[31]提出使用流動(dòng)性圖表來(lái)預(yù)測(cè)移動(dòng)用戶(hù)未來(lái)的數(shù)據(jù)收集位置,避免了靜態(tài)sink導(dǎo)致的網(wǎng)絡(luò)壽命過(guò)短.SOHRABI K等人[32]提出了一種基于表驅(qū)動(dòng)的 SAR 路由機(jī)制,在無(wú)線傳感器網(wǎng)絡(luò)中首次提出QoS概念,在確立路由樹(shù)的同時(shí)將每條路徑上節(jié)點(diǎn)能效與可靠性作為考慮因素.文獻(xiàn)[33]中采用基于先驗(yàn)的鏈路知識(shí)選取最優(yōu)的數(shù)據(jù)傳輸路徑的靜態(tài)路由規(guī)劃技術(shù),具有算法簡(jiǎn)單、路由決策速度快等特點(diǎn).但該策略只有當(dāng)鏈路發(fā)生故障和擁塞后,才會(huì)重新選擇路徑.靜態(tài)路由規(guī)劃技術(shù)為了提高數(shù)據(jù)傳輸?shù)姆€(wěn)定性,必須建立冗余路徑的方式,但這種方式會(huì)導(dǎo)致網(wǎng)絡(luò)擁堵、成本開(kāi)銷(xiāo)增大.文獻(xiàn)[34]采用動(dòng)態(tài)路由規(guī)劃技術(shù),基于網(wǎng)絡(luò)的拓?fù)渥兓瘉?lái)預(yù)測(cè)網(wǎng)絡(luò)當(dāng)前的通信狀態(tài),而采用動(dòng)態(tài)性路由決策的過(guò)程,將會(huì)增加數(shù)據(jù)傳輸?shù)臅r(shí)間開(kāi)銷(xiāo).

以上研究成果沒(méi)有涉及局部壓縮感知WSN的網(wǎng)絡(luò)吞吐量和時(shí)延的沖突解決方案,也未給出占空比設(shè)置的參考方法,更沒(méi)有考慮在電網(wǎng)監(jiān)測(cè)的特定環(huán)境下,QoS保證的協(xié)議設(shè)計(jì)和最大化網(wǎng)絡(luò)生存時(shí)間的能量均衡問(wèn)題.

3 結(jié) 語(yǔ)

目前，對(duì)于電網(wǎng)監(jiān)測(cè)無(wú)線傳感器網(wǎng)絡(luò)的研究工作主要集中在不同的應(yīng)用層面上,缺乏對(duì)電網(wǎng)監(jiān)測(cè)無(wú)線傳感器網(wǎng)絡(luò)的時(shí)延、吞吐量、整體生存時(shí)間等性能的研究.而圍繞局部壓縮感知和Low-Duty-Cycle機(jī)制在無(wú)線傳感器網(wǎng)絡(luò)的相關(guān)研究已提出了很多方法,但還存在很多未解決的問(wèn)題,且這些研究工作都是針對(duì)一般的應(yīng)用環(huán)境或一些WSN實(shí)驗(yàn)原型系統(tǒng)來(lái)展開(kāi)研究,很難在大規(guī)模WSN的應(yīng)用中進(jìn)行推廣,也不能直接應(yīng)用到電網(wǎng)監(jiān)測(cè)無(wú)線傳感器網(wǎng)絡(luò)中.因此,基于電網(wǎng)監(jiān)測(cè)無(wú)線傳感器網(wǎng)絡(luò)的特點(diǎn),有必要針對(duì)局部壓縮感知數(shù)據(jù)的有效恢復(fù)、Low-Duty-Cycle機(jī)制中精確時(shí)間同步、電網(wǎng)監(jiān)測(cè)環(huán)境下傳感器網(wǎng)絡(luò)的最優(yōu)化配置等方面開(kāi)展有針對(duì)性的研究,從而提高電網(wǎng)監(jiān)測(cè)無(wú)線傳感器網(wǎng)絡(luò)的相關(guān)性能,推動(dòng)WSN在電力系統(tǒng)包括智能電網(wǎng)的大規(guī)模應(yīng)用.

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(編輯 白林雪)

ResearchonKeyTechnologiesofWirelessSensorNetworksforPowerGridMonitoring

LIJing,WENMi,XUEMei

(SchoolofComputerScienceandTechnology,ShanghaiUniversityofElectricPower,Shanghai200090,China)

In the WSN of power grid system,there are many practical challenges in the designs of WSN,such as the limited choices of routing paths,imbalanced network traffic,limited life-time of WSN,and the complexity of maintenance.To address these challenges,it is proposed to investigate and optimize the performance of WSNs based on regional compressed sensing (RCS) and low-duty-cycle (LDC) mechanism.The key technologies of wireless sensor networks for grid monitoring are introduced.In addition,the research status and progress of this field at domestic and abroad are described in detail.Three key technologies are proposed including how to realize RCS so that we can reconstruct original data efficiently,how to improve the accuracy of clock synchronization and how to optimize the setting of WSN for real-time power-grid monitoring.With these research topics,it will increase life-time of WSN,supply efficient and QoS guaranteed data collection and translation and facilitate the deployment of smart grid system.

compressed sensing; grid monitoring; wireless sensor network; low-duty-cycle

10.3969/j.issn.1006-4729.2017.04.012

2017-03-09

李婧(1980-),女,博士,副教授,山東海陽(yáng)人.主要研究方向?yàn)榫W(wǎng)絡(luò)通信協(xié)議,智能電網(wǎng).E-mail:lijing@shiep.edu.cn.

國(guó)家自然科學(xué)基金(61572310).

TM764;TN929.5;TP212.9

A

1006-4729(2017)04-0367-05