Universal self-adaptive wave trapper

Abstract

The invention relates to a universal self-adaptive wave trapper, and belongs to the technical of the electrical variable measurement. The defect that the detection performance is affected by input signal frequency and amplitude can be overcome at the same time by modifying and improving the existing self-adaptive wave trapper, and the self-adaptive wave trapper has relatively simple structure andis used for the extraction of electric signal information in an electric system, the frequency, the amplitude, the phase angle and like information can be accurately monitored in real time, thereby mastering the operational status of the system; and meanwhile, the extracted information can be used for electric energy quality detection, relay protection and like aspects, thereby improving the intelligent, the comprehensive and digital level of a transformer substation; compared with the traditional ANF, the universal ANF has more extensive application range, and can be used as an electric signal detection unit to be applied to the electric system besides the conventional electric system.

Description

technical field

[0001] The invention belongs to the technical field of electric variable measurement, and in particular relates to a general self-adaptive wave notch filter. Background technique

[0002] In the ground power system, the substation is an important node in the power system. In order to understand the operation status of the substation more comprehensively and accurately, it is necessary to closely monitor the information of the equipment in the substation. The frequency, amplitude and phase angle of voltage and current are important information for power system operation and control. Only when the above information is accurately detected, can the power quality be analyzed, harmonic control be carried out, and the reliability of relay protection be improved. Accurate acquisition of these information will have a significant impact on the stability of the system. At present, the information extraction in the substation is basically in a fragmented and distributed...

Examples

specific Embodiment 1

[0056] Specific embodiment 1, it is assumed that the frequency of the input signal is 50 Hz, the initial phase angle is 0, ε=500, and ζ=0.6. First set the input signal amplitude as 1.0pu, when t=0.3s, the input signal frequency increases to 51Hz, and when t=0.8s, the frequency returns to 50Hz. The frequency tracking results obtained by using general ANF and traditional ANF are as follows figure 2 As shown, the black line in the figure is the detection waveform of general ANF, and the gray line is the detection waveform of traditional ANF. It can be seen that both methods can quickly and accurately detect frequency changes when the input signal amplitude is 1.0pu.

[0057] Set the amplitude of the input signal to 0.5pu and 1.5pu respectively, and the frequency still changes as described above, the result obtained is as follows image 3 and 4 shown. The results show that the detection performance of the general-purpose ANF designed in this paper is always consistent when the...

specific Embodiment 2

[0058] In the specific embodiment 2, it is assumed that the frequency of the input signal is 400 Hz, the initial phase angle is 0, ε=500, and ζ=0.6. First set the input signal amplitude to 1.0pu, when t=1.0s, the input signal frequency increases to 800Hz, and when t=1.6s, the frequency returns to 400Hz. The frequency tracking results obtained by using general ANF and traditional ANF are as follows Figure 5 As shown, the black line in the figure is the detection waveform of the general ANF, and the gray line is the detection waveform of the traditional ANF. It can be seen that the general ANF can track the frequency change in one cycle, while the traditional ANF takes a long time to detect the frequency There is a large difference in speed between the two.

[0059] Set the input signal amplitudes to 0.5pu and 1.5pu respectively. When t=2.0s, the input signal frequency increases to 800Hz. When t=4.0s, the frequency returns to 400Hz. The waveform is as follows Figure 6 and 7...

specific Embodiment 3

[0061] In the specific embodiment 3, it is assumed that the frequency of the input signal is 50 Hz, the initial phase angle is 0, ε=500, and ζ=0.6. First set the amplitude of the input signal to be 1.0pu. When t=0.3s, the amplitude is increased by 0.2pu, and when t=0.8s, the amplitude is restored to 1.0pu. The amplitude tracking results obtained by using general ANF and traditional ANF are as follows: Figure 8 As shown, the black line in the figure is the detection waveform of the general ANF, and the gray line is the detection waveform of the traditional ANF. It can be seen that both methods can quickly and accurately detect the amplitude change when the input signal amplitude is 1.0pu.

[0062] Set the input signal amplitudes as 0.5pu and 1.5pu respectively, when t=0.3s, the amplitudes increase to 0.6pu and 1.8pu respectively, the obtained results are as follows Figure 9 and 10 shown. The results show that the amplitude detection performance of the general-purpose ANF ...

technical field

[0001] The invention belongs to the technical field of electric variable measurement, and in particular relates to a general self-adaptive wave notch filter. Background technique

[0002] In the ground power system, the substation is an important node in the power system. In order to understand the operation status of the substation more comprehensively and accurately, it is necessary to closely monitor the information of the equipment in the substation. The frequency, amplitude and phase angle of voltage and current are important information for power system operation and control. Only when the above information is accurately detected, can the power quality be analyzed, harmonic control be carried out, and the reliability of relay protection be improved. Accurate acquisition of these information will have a significant impact on the stability of the system. At present, the information extraction in the substation is basically in a fragmented and distributed...

Examples

specific Embodiment 1

[0056] Specific embodiment 1, it is assumed that the frequency of the input signal is 50 Hz, the initial phase angle is 0, ε=500, and ζ=0.6. First set the input signal amplitude as 1.0pu, when t=0.3s, the input signal frequency increases to 51Hz, and when t=0.8s, the frequency returns to 50Hz. The frequency tracking results obtained by using general ANF and traditional ANF are as follows figure 2 As shown, the black line in the figure is the detection waveform of general ANF, and the gray line is the detection waveform of traditional ANF. It can be seen that both methods can quickly and accurately detect frequency changes when the input signal amplitude is 1.0pu.

[0057] Set the amplitude of the input signal to 0.5pu and 1.5pu respectively, and the frequency still changes as described above, the result obtained is as follows image 3 and 4 shown. The results show that the detection performance of the general-purpose ANF designed in this paper is always consistent when the...

specific Embodiment 2

[0058] In the specific embodiment 2, it is assumed that the frequency of the input signal is 400 Hz, the initial phase angle is 0, ε=500, and ζ=0.6. First set the input signal amplitude to 1.0pu, when t=1.0s, the input signal frequency increases to 800Hz, and when t=1.6s, the frequency returns to 400Hz. The frequency tracking results obtained by using general ANF and traditional ANF are as follows Figure 5 As shown, the black line in the figure is the detection waveform of the general ANF, and the gray line is the detection waveform of the traditional ANF. It can be seen that the general ANF can track the frequency change in one cycle, while the traditional ANF takes a long time to detect the frequency There is a large difference in speed between the two.

[0059] Set the input signal amplitudes to 0.5pu and 1.5pu respectively. When t=2.0s, the input signal frequency increases to 800Hz. When t=4.0s, the frequency returns to 400Hz. The waveform is as follows Figure 6 and 7...

specific Embodiment 3

[0061] In the specific embodiment 3, it is assumed that the frequency of the input signal is 50 Hz, the initial phase angle is 0, ε=500, and ζ=0.6. First set the amplitude of the input signal to be 1.0pu. When t=0.3s, the amplitude is increased by 0.2pu, and when t=0.8s, the amplitude is restored to 1.0pu. The amplitude tracking results obtained by using general ANF and traditional ANF are as follows: Figure 8 As shown, the black line in the figure is the detection waveform of the general ANF, and the gray line is the detection waveform of the traditional ANF. It can be seen that both methods can quickly and accurately detect the amplitude change when the input signal amplitude is 1.0pu.

[0062] Set the input signal amplitudes as 0.5pu and 1.5pu respectively, when t=0.3s, the amplitudes increase to 0.6pu and 1.8pu respectively, the obtained results are as follows Figure 9 and 10 shown. The results show that the amplitude detection performance of the general-purpose ANF ...

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