A Method for Solving the State Estimation Problem with the Target of Maximizing the Normal Rate of Measuring Points

Abstract

The invention discloses a method for solving a state estimation problem taking a maximum normal rate of a measurement point as a target. The method comprises the following steps of performing approximate optimization, namely serializing an evaluation function of the normal rate of the measurement point to build a non-linear continuous variable optimization model of the problem and perform solving, thus obtaining an approximately optimal estimation state of the measurement point normal rate; checking the compatibility of an abnormal measurement point, namely analyzing an uncertainty region of the current abnormal measurement point according to a system state corresponding to the approximately optimal result, judging whether a state that enables the abnormal measurement point to be compatible with the current normal measurement point exists, if the state exists, determining that the measurement point is a normal measurement point in the state and the normal rate of the measurement point corresponding to the state is higher, repeating the execution to obtain a system state with higher normal rate of the measurement point; and performing filtration on the normal measurement point, namely performing least square estimation on the system state under the condition that an existing normal measurement point set is not changed. The method has the advantages of high tolerance resistance performance, high precision and small calculation gain.

Description

technical field [0001] The invention belongs to the field of power system analysis and control, and in particular relates to a method for solving a state estimation problem whose goal is to maximize the normal rate of measuring points. Background technique [0002] Power system state estimation provides real-time and credible state information for power system analysis and control, and is an important part of energy management systems. At present, the most widely used state estimation method is weighted least squares (WLS) estimation, which has the disadvantage of poor robustness, and the estimation results are easily affected by bad measurement points. To solve this problem, many scholars have proposed a series of robust estimation methods, such as weighted least absolute value (WLAV) estimation, quadratic linear (QL) estimation, quadratic constant (QC) estimation, etc. These methods all start from the concept of residuals and have certain limitations. [0003] In recent ...

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Problems solved by technology

To solve this problem directly, on the one hand, the global optimal solution cannot be obtained, that is, the estimated result of the maximum normal rate of the measuring point cannot be obtained, but only the approximate result of the larger normal rate of the measuring point can be obtained; on the other hand, the calculation efficiency is low, and it cannot satisfy the large Requirements for Online Applications of Scale Power Systems

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