發(fā)布時間：2018-04-24 09:50

  本文選題：虛假數(shù)據(jù)攻擊 + 信息物理融合系統(tǒng)��； 參考：《電力系統(tǒng)自動化》2017年11期

【摘要】：虛假數(shù)據(jù)攻擊面臨掌握的電氣參數(shù)存在誤差,甚至不完整及量測數(shù)據(jù)中存在不良數(shù)據(jù)的問題,提出一種基于拉格朗日乘子法的虛假數(shù)據(jù)攻擊策略。首先通過拉格朗日乘子法和增廣狀態(tài)估計法辨識不良數(shù)據(jù)和估計未知支路電抗,然后在凸松弛技術(shù)框架內(nèi),將傳統(tǒng)的攻擊單個量測點的次優(yōu)虛假數(shù)據(jù)攻擊向量模型轉(zhuǎn)化為基追蹤(BP)模型,最后采用交替方向乘子法(ADMM)快速求解次優(yōu)攻擊向量。以典型的IEEE節(jié)點測試系統(tǒng)為例進(jìn)行仿真測試,仿真結(jié)果表明:與傳統(tǒng)的線性規(guī)劃算法相比,將攻擊單個量測點的次優(yōu)攻擊向量模型轉(zhuǎn)化為BP模型后,采用ADMM求解次優(yōu)攻擊向量具有更高的計算效率;電抗未知支路數(shù)量較少時,攻擊成功率較高,但是狀態(tài)變量的誤差向量的標(biāo)準(zhǔn)差較小時,電抗未知支路數(shù)量對攻擊成功率影響減弱;該方法不會顯著增加攻擊成本。
[Abstract]:The false data attack is faced with the error of the electrical parameters in control, even incomplete and the bad data in the measurement data. A false data attack strategy based on Lagrange multiplier method is proposed. At first, the Lagrange multiplier method and augmented state estimation method are used to identify bad data and estimate unknown branch reactance, and then within the framework of convex relaxation technique, The traditional suboptimal false data attack vector model which attacks a single measurement point is transformed into the base tracking BP- model, and the suboptimal attack vector is solved quickly by alternating direction multiplier method (ADMMM). A typical IEEE node test system is taken as an example. The simulation results show that compared with the traditional linear programming algorithm, the sub-optimal attack vector model which attacks a single measurement point is transformed into BP model. When the number of reactance unknown branches is small, the success rate of attack is higher, but the standard deviation of error vector of state variable is smaller. The effect of the number of reactance unknown branches on the attack success rate is weakened, and the attack cost is not significantly increased by this method.
【作者單位】： 武漢大學(xué)電子信息學(xué)院;武漢大學(xué)動力與機(jī)械學(xué)院;
【基金】：國家自然科學(xué)基金資助項目(50677047) 湖北省自然科學(xué)基金資助項目(2015CFB563) 中央高�；究蒲袠I(yè)務(wù)費專項資金資助項目(2042017kf0037)~~
【分類號】：TM76;TP309

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本文編號：1796149