A Dynamic State Estimation Method of Generator Based on Unscented Transform Strong Tracking

A generator dynamic and state estimation technology, applied in the field of analysis and control, power system monitoring, can solve the problem of high dependence on prior knowledge of noise, and achieve the effect of high estimation accuracy
CN104777426BActive Publication Date: 2017-11-24HOHAI UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
HOHAI UNIV
Publication Date
2017-11-24

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Abstract

The invention discloses a generator dynamic state estimation method based on unscented transformation and strong tracking filtering. The method is divided into two steps for generator dynamic state estimation, namely a prediction step and a filtering step. The mean and filter covariance matrix adopts a symmetric sampling strategy for sigma point sampling, calculates the measurement prediction calculation value, obtains the residual equation, and introduces the fading factor to modify the prediction covariance matrix; the filter step adjusts the gain matrix online, and after the correction, the electromechanical transient is obtained. The estimated value of the generator power angle and electrical angular velocity during the state process. Compared with the unscented Kalman filter and the strong tracking filter, the method for estimating the dynamic state of the generator based on the unscented transform and strong tracking filter of the present invention is improved in terms of tracking speed, accuracy and robustness to noise.
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Description

Technical field

[0001] The invention relates to a generator dynamic state estimation method based on strong tracking without trace conversion, which belongs to the technical field of power system monitoring, analysis and control. Background technique

[0002] Power system state estimation is mainly divided into static state estimation and dynamic state estimation. In recent years, a phasor measurement unit (PMU) based on a wide-area measurement system has made it possible to accurately track the electromechanical transient state of the power system. However, due to the existence of measurement errors, direct electromechanical transient analysis using the raw data measured by the PMU cannot obtain accurate results, which will ultimately affect the effective and real-time monitoring of the system and the formulation of corresponding stable control strategies. Dynamic state estimation can not only filter out errors and noise in the measurement data, but its predictive ability can a...

Claims

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