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Active power filter control method based on fuzzy neural network PID

A technology of fuzzy neural network and power filter, applied in active power filter, AC network to reduce harmonics/ripple, harmonic reduction device, etc., can solve the problem of not taking into account system robustness tracking waveform dynamic response and steady-state response

Inactive Publication Date: 2014-09-17
STATE GRID CORP OF CHINA +3
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  • Abstract
  • Description
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Problems solved by technology

And because the PWM inverter is inherently nonlinear and uncertain, the current waveform control technology proposed does not take into account the robustness of the system and the dynamic response and steady-state response of the tracking waveform.

Method used

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  • Active power filter control method based on fuzzy neural network PID
  • Active power filter control method based on fuzzy neural network PID
  • Active power filter control method based on fuzzy neural network PID

Examples

Experimental program
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Effect test

Embodiment

[0092] Embodiment: Select the number of membership function , ; Taking the APF as the object, it is simulated and verified in the Matlab / Simulink environment. The simulation platform uses controllable thyristors, and the sampling frequency is , the maximum switching frequency is , the circuit parameters are: , ;System parameters are: power supply phase voltage , the given value of the capacitor voltage ; Figure 4 It is the waveform diagram of the three-phase voltage on the grid side; Figure 5 is the grid-side current waveform before filtering under the nonlinear load; Figure 6 For adopting the grid side current waveform after the inventive method APF filter; By Figure 5-6 It can be seen that under the proposed method, the output current of the APF can better suppress the harmonic current and achieve a better compensation effect.

[0093] To sum up, the present invention enables the inverter current control loop to have good control performance, strong robu...

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Abstract

The invention discloses an active power filter (APF) control method based on fuzzy neural network PID. The method comprises the steps that a non-linear dynamic model of an APF inverter is established according to power electronics; a PIC controller of a current control loop is designed according to the established non-linear dynamic model; a fuzzy neural network compensating controller is designed and used for improving the dynamic response of the current control loop of the inverter; a PI controller of a voltage control loop of the inverter is designed, and a reference current value which needs to be tracked by the output current of the inverter is solved. According to the method, PID control and fuzzy neural network control are combined, the design process is simple, engineering realization is easy, and the response performance of the output current of the inverter is further improved.

Description

technical field [0001] The invention relates to an active power filter control method based on fuzzy neural network PID, which belongs to the field of power system control. Background technique [0002] With the increase of diversity of power grid topology and circuit load, the impact of harmonic pollution on power grid system is becoming more and more serious and has aroused widespread concern. Harmonic pollution is not only an obstacle to the development of power electronics technology, harmonics may also cause local series resonance or parallel harmonics in the power system, thereby amplifying the harmonic content and causing equipment burnout, and harmonics will also cause damage to communication systems and electronic equipment cause serious interference. It can be seen that harmonic pollution makes the power system deviate from the ideal and normal electrical process and behavior, and the decline of power quality not only affects the safe and reliable power supply of ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/01
CPCY02E40/22Y02E40/40Y02E40/20
Inventor 杨飞汪超秦华孙波李海涛査森森王尉
Owner STATE GRID CORP OF CHINA
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