【摘要】：隨著電力信息物理系統(tǒng)的快速發(fā)展,對電力系統(tǒng)的精確預測、精當決策和精準控制成為必然要求,而這依賴于精確的數(shù)據(jù)。作為數(shù)據(jù)濾波器的狀態(tài)估計模塊是能量管理系統(tǒng)中的基礎和核心,傳統(tǒng)的加權(quán)最小二乘狀態(tài)估計方法及基于殘差的不良數(shù)據(jù)辨識方法對強相關的多不良數(shù)據(jù)的辨識能力有限,已不能完全滿足日益增長的生產(chǎn)應用和安全的要求,電力系統(tǒng)狀態(tài)估計的抗差性能和計算效率急需提高。為此,本文在不確定理論體系下對狀態(tài)估計進行了深入研究,論文的主要工作如下:(1)基于不確定測度重新定義了正常測點、異常測點、測點正常率,進而提出兼顧測點正常率和量測量偏離真值程度的新的狀態(tài)估計結(jié)果評價新指標,可以應用在真值已知或未知的情況。(2)基于兼顧測點正常率和偏離度的評價指標定義正常測點參與度函數(shù)及狀態(tài)估計準則函數(shù),在此基礎上提出了最大正常率最小偏離度估計方法(MNLD)。此法是以測點正常率最大和正常測點偏離度最小為目標的多目標規(guī)劃模型,從理論上保證了其估計結(jié)果具有較高的合理性。(3)為使MNLD模型適用于實際求解,作了3點等效轉(zhuǎn)化。1)通過目標規(guī)劃法將SE的多目標規(guī)劃轉(zhuǎn)化為單目標規(guī)劃問題;2)采用雙曲正切型矩形脈沖(RPF)替代正常測點參與度函數(shù);3)采用改進凝聚函數(shù)逼近max(7)(8)型函數(shù)(無窮范數(shù)型函數(shù));并采用內(nèi)點法進行求解。(4)通過對MNLD方法與已有的狀態(tài)估計方法進行收斂性試驗、抗差性能、計算效率等方面的仿真實驗。大量算例表明,MNLD方法在抗差性能和計算效率方面具有良好表現(xiàn)。
[Abstract]:With the rapid development of power information physical system, accurate prediction of power system, precise decision-making and accurate control become necessary requirements, which depends on accurate data. As a data filter, the state estimation module is the foundation and core of the energy management system. The traditional weighted least square state estimation method and the residual based bad data identification method have limited ability to identify the strong correlation multi-bad data. It can not fully meet the requirements of increasing production application and safety. The robust performance and computational efficiency of power system state estimation need to be improved urgently. The main work of this paper is as follows: (1) based on the uncertainty measure, the normal point, the abnormal point, the normal rate of measurement point are redefined. Furthermore, a new evaluation index of state estimation results, which takes into account the normal rate of measurement points and the degree of deviation from the true value, is proposed. It can be applied to the situation where the true value is known or unknown. (2) based on the evaluation index which takes into account the normal rate and deviation of the measured point, the participation function and the state estimation criterion function of the normal measuring point are defined. On this basis, a method for estimating the maximum normal rate and minimum deviation degree, (MNLD)., is proposed. This method is a multiobjective programming model with the maximum normal rate and minimum deviation of normal measuring points as the objective, which theoretically ensures the high rationality of the estimated results. (3) in order to make the MNLD model suitable for practical solution, In this paper, the equivalent transformation of 3 points is made. 1) the multiobjective programming of SE is transformed into a single objective programming problem by the goal programming method. 2) the hyperbolic tangent rectangular pulse (RPF) is used to replace the participation function of normal measuring points. 3) the improved condensate function is used to approximate max (7) (8). The inner point method is used to solve the problem. (4) the convergence test of MNLD method and the existing state estimation method is carried out. Simulation experiments on robust performance, computational efficiency and so on. A large number of examples show that the MNLD method has good performance in robustness and computational efficiency.
【學位授予單位】：華北電力大學(北京)
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM732;TM711

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