本文選題：智能電網(wǎng) + 狀態(tài)估計��； 參考：《華北電力大學(xué)(北京)》2017年碩士論文

【摘要】：虛假數(shù)據(jù)注入攻擊(False Data Injection Attacks,FDIAs)是針對智能電網(wǎng)中電力系統(tǒng)狀態(tài)估計的新型攻擊手段,是一種典型的數(shù)據(jù)完整性攻擊方式。FDIAs通過篡改電網(wǎng)狀態(tài)估計值,成功繞過傳統(tǒng)不良數(shù)據(jù)檢測機(jī)制,使控制中心做出錯誤決策,引發(fā)嚴(yán)重的物理電網(wǎng)故障。研究高效可行的FDIAs檢測方法,對構(gòu)建安全、穩(wěn)定運(yùn)行的智能電網(wǎng)信息物理系統(tǒng)具有非常重要的意義。針對FDIAs,本文重點(diǎn)研究其檢測方法。通過分析FDIAs原理及國內(nèi)外研究現(xiàn)狀,對現(xiàn)有檢測方法從集中式檢測和分布式檢測兩個角度進(jìn)行對比分析�，F(xiàn)有檢測方法大多忽略了FDIAs對電網(wǎng)物理特性的影響以及兩者之間的關(guān)系;當(dāng)檢測到FDIAs時,很少有檢測方法提出恢復(fù)系統(tǒng)測量量使系統(tǒng)在較短時間內(nèi)恢復(fù)正常運(yùn)行狀態(tài);現(xiàn)有分布式檢測方法通常為基于不同地理區(qū)域?qū)㈦娋W(wǎng)劃分為不同子網(wǎng)系統(tǒng),耗費(fèi)較高的經(jīng)濟(jì)成本。為解決上述問題,本文從集中式和分布式兩個角度,分別提出基于節(jié)點(diǎn)電壓穩(wěn)定性指標(biāo)的檢測方法和基于矩陣分割的零空間映射兩級檢測方法�；诠�(jié)點(diǎn)電壓穩(wěn)定性指標(biāo)的檢測方法中,引入節(jié)點(diǎn)電壓穩(wěn)定性指標(biāo)(Node Voltage Stability Index,NVSI),分析FDIAs對NVSI值的影響。根據(jù)系統(tǒng)中節(jié)點(diǎn)NVSI值,運(yùn)用改進(jìn)的聚類算法對節(jié)點(diǎn)進(jìn)行聚類,辨識節(jié)點(diǎn)脆弱性等級;針對脆弱性等級高的節(jié)點(diǎn),提出狀態(tài)預(yù)測檢測法實(shí)現(xiàn)FDIAs檢測。若FDIAs存在,則利用測量量預(yù)測值更新測量量,使系統(tǒng)恢復(fù)正常運(yùn)行狀態(tài)�；诰仃嚪指畹牧憧臻g映射兩級檢測方法中,分析雅克比矩陣H各行間的線性相關(guān)性,設(shè)計基于矩陣相似度的矩陣分割算法,對待檢測電網(wǎng)系統(tǒng)進(jìn)行劃分;在每個子網(wǎng)系統(tǒng)中,提出零空間映射檢測方法實(shí)現(xiàn)FDIAs檢測;當(dāng)FDIAs存在時,則利用零空間逆映射方法進(jìn)行測量量恢復(fù)。針對所提兩種檢測方法,本文運(yùn)用Matpower電力仿真包,在IEEE 14-bus,IEEE30-bus和IEEE 118-bus標(biāo)準(zhǔn)測試系統(tǒng)中進(jìn)行仿真實(shí)驗,驗證方法可行性與有效性。實(shí)驗結(jié)果表明,基于節(jié)點(diǎn)電壓穩(wěn)定性指標(biāo)的檢測方法在規(guī)模較小的系統(tǒng)中計算NVSI值所需時間較短,開銷較小,能夠快速檢測到FDIAs;當(dāng)系統(tǒng)規(guī)模較大時,基于矩陣分割的零空間映射檢測法具有較高的檢測率,能夠有效檢測FDIAs。
[Abstract]:False Data Injection attack (false Data Injection AttacksFDIAs) is a new attack against power system state estimation in smart grid. It is a typical data integrity attack. FDIAs tamper with power grid state estimation. By successfully bypassing the traditional bad data detection mechanism, the control center makes the wrong decision and causes the serious physical power grid failure. The study of efficient and feasible FDIAs detection method is of great significance to the construction of a safe and stable intelligent grid information physical system. For FDI Ass, this paper focuses on its detection methods. By analyzing the principle of FDIAs and the current research situation at home and abroad, the existing detection methods are compared and analyzed from two aspects: centralized detection and distributed detection. Most of the existing detection methods ignore the influence of FDIAs on the physical characteristics of the power network and the relationship between the two. When the FDIAs is detected, few detection methods propose to restore the measurement of the system so that the system can return to normal operation in a relatively short time. The existing distributed detection methods are usually based on different geographical regions to divide the power network into different subnet systems, which cost a lot of money. In order to solve the above problems, this paper presents two detection methods based on node voltage stability index and zero-space mapping method based on matrix partitioning from the view of centralization and distribution, respectively. In the detection method based on node voltage stability index, the node voltage stability index (Node Voltage Stability Index) is introduced to analyze the influence of FDIAs on NVSI value. According to the NVSI value of the nodes in the system, the improved clustering algorithm is used to cluster the nodes to identify the vulnerability level of the nodes. For the nodes with high vulnerability level, a state prediction detection method is proposed to realize the FDIAs detection. If FDIAs exists, the measurement is updated by using the predictive value of the measurement to restore the normal operation state of the system. In the zero-space mapping two-level detection method based on matrix segmentation, the linear correlation between lines of Jacobian matrix H is analyzed, and a matrix segmentation algorithm based on matrix similarity is designed to divide the detection grid system. The null space mapping detection method is proposed to realize FDIAs detection, and when FDIAs exists, the null space inverse mapping method is used to recover the measurements. Aiming at the two detection methods mentioned above, this paper uses Matpower electric power simulation package to carry out simulation experiments in IEEE 14-bus IEEE30-bus and IEEE 118-bus standard test system, and verifies the feasibility and validity of the method. The experimental results show that the detection method based on the nodal voltage stability index takes less time and less overhead to calculate the NVSI value in a small system, and it can quickly detect the FDI As.When the system scale is large, The null space mapping detection method based on matrix segmentation has high detection rate and can effectively detect FDIAs.
【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM76

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本文編號：1961289