Fading-Kalman-filter-based on-line voltage stability monitoring method

A Kalman filter, voltage stabilization technology, applied in the direction of AC network voltage adjustment, circuit devices, AC network circuits, etc., can solve the problems of erroneous monitoring results, drift, etc., to improve practicability, avoid load blackouts and economic losses.

Inactive Publication Date: 2018-05-29
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AI-Extracted Technical Summary

Problems solved by technology

However, when the power system is running, the data obtained by WAMS often contain measurement noise and disturbance noise. In addition, when the continuous excitation is insufficient, the online monitoring results w...
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The invention discloses a fading-Kalman-filter-based on-line voltage stability monitoring method. The method comprises: a parameter of a simplified Thevenin equivalent model of a power system is identified by using local information of a power grid; with consideration of a measurement error and a noise of real-time data, parameter calculation results of adjacent two times as input data of on-lineequivalent model parameters are processed and parameters of an uncertain model are estimated by using a fading Kalman filter algorithm; and with the parameters of the uncertain model, an impedance modulus margin index is calculated, accurate and stable on-line margin monitoring is carried out on the system by monitoring a stability index of a local voltage in real time, and the monitored margin value is compared with a safety margin threshold to determine a weak point and a safety and stability level of the system. According to the method provided by the invention, the method has the high capability for suppressing the local measurement information error and noises and has the excellent robust and tracking performances; the interference on the filtering by the accumulated error is reduced;accurate on-line voltage stable level monitoring is realized; and the support is provided for the safe operation of the power system.

Application Domain

Ac network voltage adjustment

Technology Topic

Power gridVoltage +14


  • Fading-Kalman-filter-based on-line voltage stability monitoring method
  • Fading-Kalman-filter-based on-line voltage stability monitoring method
  • Fading-Kalman-filter-based on-line voltage stability monitoring method


  • Effect test(1)

Test Example

[0080] Application examples of the voltage stability on-line monitoring method provided by the present invention are as follows:
[0081] like image 3 As shown, the IEEE 14 node system is used as the test system for example testing. The system contains 5 generators with 14 nodes, the reference power capacity is 100MVA, and the reference voltage is 23kV. In this example, 14 nodes are selected as the leading node, that is, the monitoring point. The frequency is ΔT=0.02s, the acquisition time is T=100s, and the parameters required for the index calculation are selected. The load is a three-phase RLC load, set to PQ type, and the rated active power and reactive power of each load are set according to Table 1. Among them, 6 #, 8# generator has zero active power, and 3# generator is set as a balanced motor. In this example, 14 nodes are used as monitoring nodes, n=1 is selected, and set A is determined. j (n). collection A j (n) The voltage, current and power information of each node in the set. When filtering in this example, the parameter values ​​are set as follows: M(k)=h ei (k)×10- 8 [1 1 0 0] T , P i (0|0)=10 -6 ·I, X i (0|0)=[U e (k),0,1,0] T.
[0082] In order to check the test result of the present invention when single-phase is grounded, a direct grounding fault of A-phase is simulated at node 14, the fault occurs in 30s, and the fault is eliminated in 33.5s. The acquisition volume within 100s is imported into the algorithm program for calculation, and the fading robust Kalman filtering algorithm is used to estimate the parameters.
[0083] Table 1 IEEE14 node system bus load data
[0085] like Figure 4 As shown, the set reference value is the measured real-time phase voltage amplitude, and the estimated value is the equivalent parameter voltage amplitude calculated by the fading Kalman filter algorithm. from Figure 4 It can be seen that since the initial value of the filter is artificially set, the estimated value fluctuates slightly at the beginning of the filtering process. After an adjustment process, the estimated value becomes stable and slightly higher than the reference value. After the fault is removed, the voltage of node 14 is restored to stability, and the estimated equivalent voltage is gradually restored to the value before the fault occurs, and no tracking oscillation occurs. After that, the node voltage and current will only fluctuate slightly, and the algorithm can also track accurately in this case. The results show that the online monitoring method based on the fading Kalman filter algorithm is adaptive to various system states and has high monitoring accuracy.
[0086] Figure 5As shown, when the system is stable, the equivalent parameters fluctuate slightly, and the impedance modulus margin index value does not fluctuate significantly. The index has good stability and has a good effect on drift phenomenon and noise suppression; In the case of large fluctuations in the monitoring volume, some interference and sampling errors can be effectively filtered, which improves the monitoring accuracy to a certain extent.


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Description & Claims & Application Information

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