【摘要】：電力系統(tǒng)狀態(tài)估計(jì)欺詐性數(shù)據(jù)是黑客在量測(cè)數(shù)據(jù)中惡意注入的以篡改狀態(tài)估計(jì)輸出結(jié)果為目的的隱蔽性不良數(shù)據(jù)。鑒于欺詐性數(shù)據(jù)能夠有效躲避傳統(tǒng)不良數(shù)據(jù)檢測(cè)和辨識(shí),通過(guò)構(gòu)建特定的欺詐性數(shù)據(jù),黑客能夠蓄意操縱狀態(tài)估計(jì)輸出結(jié)果,進(jìn)而導(dǎo)致錯(cuò)誤調(diào)度指令的產(chǎn)生,威脅電力系統(tǒng)的安全可靠運(yùn)行。因此,在確保未來(lái)智能電網(wǎng)更好服務(wù)于國(guó)民經(jīng)濟(jì)發(fā)展的層面上,研究實(shí)際電力系統(tǒng)中存在的數(shù)據(jù)安全漏洞,并制定相應(yīng)的防御措施具備迫切的現(xiàn)實(shí)意義。根據(jù)已有文獻(xiàn)所提防御方法的防御效果,將欺詐性數(shù)據(jù)防御方法分為檢測(cè)、辨識(shí)和遏制3類。檢測(cè)法僅能夠判定欺詐性數(shù)據(jù)是否存在,但無(wú)法鎖定欺詐性數(shù)據(jù)的具體位置;辨識(shí)法進(jìn)一步實(shí)現(xiàn)了對(duì)欺詐性數(shù)據(jù)所在位置的鎖定。由于遏制法著眼于從根本上瓦解黑客構(gòu)建欺詐性數(shù)據(jù)的可能性,因此,研究中將遏制法視為保障電力系統(tǒng)狀態(tài)估計(jì)結(jié)果可靠性最具成效的防御途徑。量測(cè)信息物理保護(hù)法、網(wǎng)絡(luò)參數(shù)動(dòng)態(tài)調(diào)節(jié)法、拓?fù)浣Y(jié)構(gòu)動(dòng)態(tài)調(diào)節(jié)法以及電力信息融合防御法是現(xiàn)階段提出的4種欺詐性數(shù)據(jù)遏制法,但在應(yīng)用過(guò)程中難免面臨設(shè)備投資較高、全局輸電能力受限、計(jì)算復(fù)雜度較高等因素的制約。為克服上述防御算法的不足,本文提出以完善不良數(shù)據(jù)檢測(cè)和辨識(shí)算法固有數(shù)據(jù)安全漏洞為核心的欺詐性數(shù)據(jù)遏制法,論文工作及主要研究成果如下:1、系統(tǒng)性綜述了電力系統(tǒng)狀態(tài)估計(jì)欺詐性數(shù)據(jù)防御法的研究成果。在總結(jié)現(xiàn)有欺詐性數(shù)據(jù)防御法不足的基礎(chǔ)上,指出完善不良數(shù)據(jù)檢測(cè)和辨識(shí)算法固有的數(shù)據(jù)安全漏洞是防御欺詐性數(shù)據(jù)的核心。2、提出基于狀態(tài)向量挖掘的欺詐性數(shù)據(jù)防御法。采用隱馬爾科夫模型建模歷史運(yùn)行狀態(tài)數(shù)據(jù)庫(kù),將黑客難以操縱的發(fā)電機(jī)輸出功率視為觀察狀態(tài)序列,并通過(guò)維特比算法解碼系統(tǒng)狀態(tài)序列。3、提出基于狀態(tài)變量修正的欺詐性數(shù)據(jù)防御法。提出狀態(tài)一致性檢驗(yàn)用以鎖定疑似受到欺詐性數(shù)據(jù)影響的狀態(tài)變量,并通過(guò)所構(gòu)建的狀態(tài)變量修正向量打破欺詐性數(shù)據(jù)的隱蔽性,使其無(wú)法躲避不良數(shù)據(jù)檢測(cè)和辨識(shí)算法,從而實(shí)現(xiàn)對(duì)欺詐性數(shù)據(jù)的辨識(shí)和剔除。4、采用IEEE-14節(jié)點(diǎn)和IEEE-118節(jié)點(diǎn)標(biāo)準(zhǔn)測(cè)試系統(tǒng)仿真實(shí)驗(yàn)驗(yàn)證所提出欺詐性數(shù)據(jù)防御法遏制欺詐性數(shù)據(jù)的有效性。
[Abstract]:Power system state estimation fraud data is the hidden bad data that hackers inject maliciously into the measurement data to tamper with the output of state estimation. Since fraudulent data can effectively avoid traditional bad data detection and identification, by constructing specific fraudulent data, hackers can deliberately manipulate the output of state estimation, which leads to the generation of false scheduling instructions. It threatens the safe and reliable operation of power system. Therefore, in order to ensure the future smart grid to better serve the development of the national economy, it is of urgent practical significance to study the data security vulnerabilities in the actual power system and to formulate corresponding defense measures. According to the defensive effect of the methods mentioned in the literature, the methods of fraudulent data defense are divided into three categories: detection, identification and containment. The detection method can only determine whether the fraudulent data exists, but it can not lock the location of the fraudulent data. Because containment method focuses on the possibility of disintegrating hackers to construct fraudulent data, containment method is regarded as the most effective defense way to ensure the reliability of power system state estimation results. Physical protection of measurement information, dynamic adjustment of network parameters, dynamic adjustment of topological structure and protection of power information fusion are four kinds of fraudulent data containment methods proposed at present, but it is inevitable to face high investment in equipment in the process of application. The global transmission capacity is limited and the computational complexity is high. In order to overcome the shortcomings of the above defense algorithms, this paper proposes a method of fraudulent data containment based on the improvement of bad data detection and identification of inherent data security vulnerabilities. The main results of this paper are as follows: 1. The research results of power system state estimation fraudulent data defense method are systematically reviewed. On the basis of summing up the deficiency of the existing fraudulent data defense methods, it is pointed out that improving the data security holes inherent in the bad data detection and identification algorithm is the core of the defense against fraudulent data. A state vector mining based data defense method is proposed. Using hidden Markov model to model the historical running state database, the generator output power which is difficult to manipulate by hackers is regarded as the observation state sequence, and the system state sequence is decoded by Viterbi algorithm. In this paper, a method of data fraud defense based on state variable correction is proposed. A state consistency test is proposed to lock the state variables that are suspected to be affected by fraudulent data, and to break the concealment of the fraudulent data by modifying the vector of the state variables, which makes it unable to avoid the bad data detection and identification algorithm. Finally, the identification and elimination of fraudulent data are realized. 4. The effectiveness of the proposed method is verified by using IEEE-14 node and IEEE-118 node standard test system.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM732

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