CN115065045A

CN115065045A - Direct current power grid self-adaptive noise suppression harmonic wave tracking and offsetting system

Info

Publication number: CN115065045A
Application number: CN202210727260.3A
Authority: CN
Inventors: 许晓磊
Original assignee: Individual
Current assignee: Individual
Priority date: 2022-06-25
Filing date: 2022-06-25
Publication date: 2022-09-16

Abstract

The application designs and realizes a harmonic tracking canceller with good dynamic tracking performance, firstly designs and models the overall structure of a harmonic tracking canceller system, then designs an adaptive noise suppression algorithm by analyzing the application scene of the harmonic tracking canceller and the characteristics of harmonics to be eliminated, and finally designs a hardware system of a filter tracker, wherein the adaptive noise suppression algorithm comprises a two-layer weak window white noise excitation real-time identification algorithm and an improved assistant noise excitation real-time identification algorithm; the algorithm is applied to a control module of a harmonic tracking canceller, and a NUC505 chip based on an ARMport-m 4 kernel is used as a system controller to realize rapid tracking and cancellation of current harmonics. The tracking efficiency of the harmonic waves of the power grid is improved by 32.4%, the effective rate of the harmonic waves in counteracting is improved by 39.3%, the hardware cost of the system is reduced by more than 30%, the harmonic waves of the power grid are efficiently and reliably inhibited, the power quality of the power grid is improved, and the normal operation of various electronic and communication equipment is protected.

Description

Direct current power grid self-adaptive noise suppression harmonic wave tracking and offsetting system

Technical Field

The application relates to a harmonic suppression system of a power direct-current power grid, in particular to a direct-current power grid self-adaptive noise suppression harmonic tracking and offsetting system, and belongs to the technical field of power transmission and transformation.

Background

With the development of electronic power technology, more and more nonlinear loads are introduced into a direct current power system, such as a frequency converter and a switching power supply, wherein the frequency converter comprises a rectifier and an inverter nonlinear device. More and more ships adopt electric power propulsion systems, most of generated electric energy enters a rectifier, and meanwhile, a large amount of harmonic current is generated, so that the current and the voltage in a power grid are seriously distorted, in addition, a large amount of harmonic waves are generated by a switching power supply during the switching action of the switching power supply, the injection of the harmonic waves in the power grid can seriously affect the electric energy quality, and the normal operation of other electronic and communication equipment is interfered.

The voltage supplied to the consumers by the ideal utility grid has a constant frequency and amplitude, but as the number of nonlinear components in the grid increases, the grid is subject to more or less harmonic interference. In addition, the presence of harmonics can cause the electromagnetic environment to be disturbed, thereby affecting the proper operation of other electronic devices. Harmonics have become an important factor affecting the quality of electrical energy.

Harmonic suppression is an important measure for improving the power quality of a power grid, ensuring the safe and reliable operation of various electric equipment and improving the surrounding electromagnetic environment. In order to reduce harmonics in the grid, two considerations may be taken into account: on one hand, the method starts from a harmonic source, such as by improving a power system to generate less harmonic waves; on the other hand, a filtering device is adopted, such as a harmonic tracking canceller and a passive filtering tracker. The first method is complex in realization, high in cost and poor in harmonic elimination effect. In the second method, the components of the passive filtering tracker which is widely applied are easily affected by system parameters and temperature drift factors, so that the filtering effect is unstable, and the defects of high consumption and large volume are overcome. The passive filter tracker only filters the harmonic waves of specific frequencies, and when a plurality of frequencies are filtered, the number of the required filter trackers is large, the size of the filter tracker is large, and the complexity is increased. Due to the limitation on the size of the capacitor, the filtering tracker cannot meet the filtering requirement and the requirement of reactive power compensation at the same time, when the harmonic quantity is large, the passive filtering tracker is overloaded, and the normal work and even damage of the filtering tracker can be influenced in serious cases. And the passive filtering tracker is not suitable for places with more harmonic ratios and complexity.

The harmonic suppressor can dynamically track harmonic changes and compensate the power grid current, and the process is not influenced by the power grid impedance. The passive filtering tracker is prevented from being interfered by other equipment in a power grid, but the passive filtering tracker has the defects of complex structure, difficult realization and higher cost. The harmonic suppressor is in dynamic work, the rectifier impedance and the load impedance of the direct current generator are represented by time-varying complex impedance (dynamic change), the complexity of a tracking algorithm is increased, the calculated amount is greatly increased, and therefore the system is unstable, and a proper control algorithm is urgently needed.

The high-voltage direct-current power grid system is provided with a large number of power converters, a large number of higher harmonics are generated in the working process, and the existence of the harmonics in the system can increase the electric energy loss of equipment and devices in the system, so that the equipment and the devices cannot work normally or even are damaged. Harmonic currents generated by the power grid can cause resonance between line-to-line capacitances, interference with communications, and radar electronics. Therefore, there is a need to solve the problem of harmonic pollution.

To sum up, the electric power direct current electric wire netting harmonic suppression system of prior art still has a plurality of problems and defects, and the problem that this application needs to solve and key technical difficulty include:

(1) the nonlinear load in the power grid causes a large amount of harmonic interference, the power grid harmonic seriously influences the normal work of the electric equipment, and when a large amount of harmonic interference is generated in a power grid system, the electric energy loss is increased, and the interference to other electronic and communication equipment is also caused. The passive filtering tracker in the prior art is easily influenced by the external environment and cannot meet the requirement of harmonic suppression. Because the electric wire netting operational environment is complicated, the harmonic wave inhibitor that prior art built receives the influence easily, can't restrain the harmonic wave interference in the electric wire netting effectively, and traditional passive filter tracker filtering effect easily receives system impedance, frequency, the influence of load change, the suppression of harmonic wave receives the restraint in the direct current electric wire netting, consequently, need a harmonic wave tracking canceller that has good dynamic tracking performance at present, restrain through the efficient harmonic and improve electric wire netting power quality, guarantee various consumer safe and reliable's operation, improve the electromagnetic environment around.

(2) The prior art reduction of harmonics in the grid is considered from two aspects: on one hand, starting from a harmonic source, the power system is improved to generate less harmonic waves; on the other hand, filtering devices such as harmonic suppressors and passive filtering trackers are adopted. The first method is complex in realization, high in cost and poor in harmonic elimination effect. In the second method, the components of the passive filter tracker which is widely applied are easily affected by system parameters and temperature drift factors, so that the filtering effect is unstable, the consumption is high, and the size is large.

(3) The harmonic suppressor in the prior art can dynamically track harmonic changes and compensate power grid current, the process is not affected by power grid impedance, and the condition that a passive filtering tracker is interfered by other equipment in a power grid is avoided.

(4) The high-voltage direct-current power grid system is provided with a large number of power converters, a large number of higher harmonics are generated in the working process, the electric energy loss of equipment and devices in the system can be increased due to the existence of the harmonics in the system, the equipment and the devices cannot work normally and even are damaged, the prior art lacks of designing and modeling the overall structure of a harmonic tracking and counteracting system, cannot analyze the application scene of the harmonic tracking and counteracting device and characteristics of the harmonics to be eliminated, lacks an adaptive noise suppression algorithm, particularly lacks a two-layer weak window white noise excitation real-time identification algorithm and an improved assisting noise excitation real-time identification algorithm, lacks a hardware system of a harmonic tracker, the prior art harmonic suppression system has a complex structure, equipment redundancy and algorithm inefficiency, has a poor effect of suppressing the power grid harmonics, and cannot well suppress the resonance between capacitors caused by harmonic currents generated by the power grid, Interference communication and radar electronic facilities, and the problem of harmonic pollution cannot be solved.

Disclosure of Invention

According to the harmonic tracking canceller, adaptive noise suppression is introduced into a core module of the harmonic tracking canceller, improvement is performed on the two aspects of an ANC system structure and an algorithm, and the frequency of a harmonic can be acquired in advance based on a high-voltage direct-current power grid, so that a feedforward system is adopted. Due to the fact that the working environment of the power grid is complex, in order to avoid the situation that the built harmonic tracking canceller is affected and track and cancel power grid harmonics in real time, a real-time identification algorithm containing two layers of weak windows is adopted, the control module structure and the algorithm of the harmonic tracking canceller are designed, the structure of the harmonic tracking canceller is improved, the algorithm is transplanted to the NUC505 controller, and single-frequency-point and double-frequency-point harmonic suppression comparison experiments and analysis are completed. Experimental results show that the harmonic tracking canceller based on self-adaptive noise suppression has good noise reduction performance, a harmonic suppression system has a clear structure, simple equipment and high algorithm efficiency, the harmonic suppression effect on a power grid is good, harmonic current generated by the power grid is well suppressed to cause resonance, interference communication and radar electronic facilities among line-to-line capacitors, and the problem of harmonic pollution is effectively solved.

In order to achieve the technical effects, the technical scheme adopted by the application is as follows:

the direct-current power grid adaptive noise suppression harmonic wave tracking and canceling system comprises a harmonic wave tracking and canceling system, a filter tracker, a harmonic wave tracking and canceling system and a noise suppression system, wherein the harmonic wave tracking and canceling system comprises a first layer of weak window white noise excitation real-time identification algorithm, a second layer of weak window white noise excitation real-time identification algorithm, an improved assistant noise excitation real-time identification algorithm and a first layer of hardware system;

the harmonic tracking cancellation system comprises a simulation dynamic power grid and a harmonic interaction suppression system, wherein the simulation dynamic power grid measures and calculates each parameter of actual equipment according to the working environment of the high-voltage direct-current power grid, a simulation dynamic power grid module built by a simulation noise source and a simulation load is adopted according to measurement data, and the harmonic interaction suppression system comprises a direct-current power grid harmonic acquisition and conversion module and a self-adaptive noise suppression module;

the working principle of the harmonic tracking cancellation system is as follows: the current harmonic waves of the direct current power system are converted into voltage signals through a current transformer and a signal modulation unit and injected into a self-adaptive noise suppression system, the self-adaptive noise suppression system synthesizes signals with the same amplitude and opposite phases according to the characteristics of input noise signals to cancel primary harmonic signals, the process is a real-time harmonic wave cancellation process, and the processing time of an algorithm on the input signals is shorter than the time of the signals passing through a two-layer weak window;

the harmonic adaptive noise suppression module includes two inputs: an error signal and a noise signal; one output: a control signal; the control signal and the noise signal have the same amplitude and opposite phases, the control signal counteracts the noise signal, the error signal is injected into the ANC system again, and the weight coefficient of the filtering tracker is adjusted until the error meets the minimum root mean square principle;

the current transformer is based on the Rogowski coil and is only used for measuring the changing current, the output of the current transformer is the differential of a current signal to time, the signal modulation module processes a voltage signal output by the current transformer, the voltage signal is converted from the current signal to the voltage signal, the real reduction of the current signal in a power grid is realized, and finally the signal is injected into the self-adaptive noise suppression system for processing.

Preferably, the harmonic tracking cancellation system models: the primary harmonic current signal I1 and the control signal I2 are superposed to generate an error current signal I3, the I3 reaches the current transformer 2 through an analog load, the error current signal I3 is converted into a voltage signal through the current transformer, the voltage signal is integrated and A/D converted by the signal modulation unit and finally transmitted to the adaptive noise suppression module to adjust the weight coefficient of the filtering tracker, and adaptive control is achieved;

the control signal is obtained by a two-layer signal through a D/A, a capacitor and a power amplifier, a physical channel generated from the two-layer signal to a current transformer 1 is a two-layer path S '(z), a channel formed by the current transformer 2, a signal modulation unit and an A/D is R (z), a transfer function from a primary harmonic current signal to a module for generating an error signal I3 in a superposition mode is P (z), a reference signal x (n) is strictly associated with the primary signal, and a signal when the superposition is carried out is obtained by taking the reference signal as the reference signal through P' (z);

for the change of the error signal z, namely frequency domain transformation, the expression is shown as formula 1:

E(z)＝X(z)[P'(Z)-S′(Z)W _n (z)]r (z) formula 1

Where x (z) is the z-transform of the reference signal, and when the system converges, the error signal e (z) is equal to 0, and the adaptive filter tracker obtains the optimal weight coefficient W ₀ Represented by formula 2:

based on a simplified harmonic tracking cancellation system block diagram, an expression of a primary path transfer function P (z) is obtained as shown in a formula 3, and an expression of a transfer function S (z) of a two-layer path is obtained as shown in a formula 4:

p (z) ═ a (z) P' (z) formula 3

S (z) r (z) S' (z) formula 4

When the error signal is zero, the weight coefficient of the optimal filtering tracker is obtained, and the expression is shown as formula 5:

as shown in equation 5, the expression of the weight coefficient of the optimal filtering tracker is inversely proportional to the transfer function of the two-layer weak window, the two-layer weak window is relatively complex in passing through the physical path and generates a delay, p (z) is also set to have a corresponding delay, and when no two-layer signal is generated at a certain frequency point, it indicates that s (z) at the point is 0, and the frequency of the frequency point cannot be cancelled.

Preferably, a system control module structure is established: the harmonic tracking and counteracting system is based on a forward filtering structure, the processing time of the broadband feedforward system in a chip is shorter than the propagation time of two-layer access, so that the elimination of broadband random noise can be met, primary harmonic signals in a direct-current power grid are easy to obtain, and a narrow-band feedforward system structure is adopted;

the narrowband feedforward system needs to synthesize a reference signal, the synthesis of the reference signal adopts a single-frequency notch filter tracker based on an FXLMS algorithm, mutually orthogonal sinusoidal signals are used as the input of the system, then the weight coefficients of the filter tracker are updated through the LMS algorithm respectively, and finally a two-layer signal is synthesized and injected into a two-layer weak window to control the periodic noise of a single frequency point or a discrete frequency point.

Preferably, the two-layer weak window real-time identification method comprises the following steps: estimating the two-layer weak window in real time to realize the self-adaptive noise suppression of the harmonic tracking canceller, wherein f (n) represents the identification error signal of the two-layer weak window; v (n) represents a white gaussian noise signal; u. of _s Represents an update step value; k represents the K-th order of the filter tracker in the range of 0, M]Where M-1 is the order of the two-layer weak window filter tracker;

the adaptive noise suppression system for real-time modeling comprises two layers of weak window modeling and adaptive noise suppression modules, wherein the two modules run simultaneously to complete an adaptive noise suppression real-time identification algorithm;

the primary noise p (n) is a periodic narrow-band noise signal represented by equation 6:

p(n)＝ax ₀ (n)+bx ₁ (n)+v _p (n) formula 6

v _p (n) is a white noise signal added to the real environment; a, b are Fourier series, and the frequency w, x of the synchronous signal detected by the synthetic reference signal ₀ (n)、x ₁ (n) the synthetic mode is shown as formula 7 and formula 8:

x ₀ (n) ═ cos wn formula 7

x ₁ (n) ═ sin wn formula 8

Two layer source y ₀ (n) is represented by formula 9:

y ₀ (n)＝x ₀ (n)w ₀ (n)+x ₁ (n)w ₀ (n) formula 9

w is the primary noise frequency detected by the sensor or FFT transform, the real-time identification system estimates the two-layer weak window in real time, and the two-layer weak window transfer function iterative formula is shown in equation 10:

when the two-layer weak window identification system reaches a stable state,

the expression of the error signal e (n) is shown in equation 11:

e(n)＝p(n)-y′(n)＝p(n)-s(n)*[y ₀ (n)-v(n)]formula 11

Injecting white noise v (n) to provide excitation for the two-layer weak window, f (n) representing the recognition error of the two-layer weak window, and the calculation formula is shown in formula 12:

after the transfer function of the two-layer weak window is identified, the adaptive noise suppression module algorithm is analyzed, and the reference signal passes through the two-layer weak window

Updating the coefficients with e (n);

based on the application environment of the harmonic tracking canceller, a white noise excitation two-layer weak window real-time identification algorithm is adopted.

Preferably, the harmonic tracking cancellation hardware system is designed: a NUC505 chip based on an ARMCortex-M4F processor is adopted in the direct current power grid, the chip internally comprises 2 MbytesPIFLash and 128 KbyeDRAM, and a plurality of peripheral devices are also arranged, wherein the peripheral devices comprise UART, 12C, I2S and 12-bitADC, and the chip is suitable for processing audio signals;

in the I2S transport protocol, data signals, clock signals and control signals are separately transmitted, and they are respectively SD, WS and SCK using transmission lines.

Preferably, the harmonic tracking canceller system is structurally designed: the structure of a harmonic tracking canceller system is improved, a master-slave control mode is adopted, a multi-channel system is converted into a plurality of single-channel systems to eliminate harmonic noise, and the computation amount of a single self-adaptive noise suppression algorithm is within the NUC505 processing capacity range;

the control structure of a master multi-slave processor is the combination of a plurality of single-channel controls, reduces the mutual interference of each frequency point and reduces the computational complexity of the processor, and the specific working mode is as follows: firstly, a computer obtains a harmonic signal in a detection signal source through FFT calculation, and sends the detected harmonic signal value to a main processor, namely an upper NUC505 through a UART; and then the main processor controls the working states of the multiple slave processors through IC communication, when the detected signal is single-frequency point noise, the main processor only needs to select one slave processor to execute an adaptive noise suppression algorithm, when the detected signal is multi-frequency point signal, the main processor controls the multiple slave processors to work, finally the processor outputs a control signal, namely a signal which is the same as the primary noise in amplitude and opposite in phase, the control signal is output to the system after being subjected to power amplification and then is counteracted with the original noise signal on an analog dynamic power grid, the counteracted error signal passes through a current transformer, the signal modulation unit injects the signal into the slave processors, and the weight coefficient of a filter tracker of ANC is adjusted to realize the adaptive control of the system.

Preferably, the overall algorithm flow of the harmonic tracking cancellation system is as follows: the method comprises the steps that a real-time identified narrow-band feedforward adaptive noise suppression algorithm is adopted and is realized on a NUC505 chip, a peripheral system, a noise application interface and parameters in an ANC algorithm are initialized before a program runs, and after the initialization is completed, the chip starts to read data and performs adaptive noise suppression algorithm processing until the data processing is finished;

a two-layer path of a direct current power system continuously changes, the system needs to perform real-time modeling on a two-layer weak window, continuously updates a transfer function of the two-layer weak window according to the change of an external environment, and adopts a two-layer weak window white noise excitation real-time identification algorithm and an improved assisting noise excitation real-time identification algorithm.

Preferably, a two-layer weak window white noise excitation real-time identification algorithm is designed: the white noise excitation real-time identification system comprises two modules, namely an adaptive noise suppression module and a two-layer weak window modeling module, wherein each module comprises a filtering tracker: one is an active control filtering tracker based on FXLMS algorithm, and the other is a two-layer weak window real-time identification filtering tracker based on LMS algorithm;

the algorithm comprises a system initialization module, an LMS algorithm weight coefficient updating module and a two-layer weak window transfer function estimation module;

before the algorithm is transplanted to the NUC505, the program is simulated on the MATLAB, and the setting of factors influencing the performance of the algorithm in the simulation process comprises the following steps:

(1) order of the filter tracker: multiple times of simulation demonstration finally shows that when the order is 12, the noise elimination effect of single and double frequency points is better;

(2) step size selection: the step size of the FXLMS filter algorithm is 0.003, and the step size of the LMS filter is 0.01.

Preferably, the improved assisting noise-excited real-time identification algorithm: the method is an improvement of a white noise excitation two-layer weak window real-time identification algorithm, and adopts an error signal to restrain white noise energy so as to obtain a better harmonic suppression effect and system stability;

reducing the energy of white noise to reduce the influence of the white noise on an error signal e (n), restraining the white noise signal based on the error signal, and improving the constraint condition of the narrow-band feedforward ANC system, namely, restraining the white noise by carrying out unit delay | e (n-1) | on the error signal;

the system comprises two modules: the self-adaptive noise suppression module has the same structure as a system adopting white noise excitation real-time identification, and the difference of the two-layer weak window module is that the algorithm introduces unit delay of an error signal, reduces the influence of v (n) on the system, improves the noise reduction performance of the system, and changes the algorithm and the white noise excitation algorithm:

the two-layer weak window identification module introduces an absolute value of unit delay of an error signal and two-layer weak window excitation y' ₀ (n) represented by formula 17:

y′ ₀ (n)＝y ₀ (n) -v (n) e (n-1) | formula17

f (n) represents the two-layer weak window identification error signal; v (n) represents a white gaussian noise signal; u. of _s The representation of the recognition error f (n) of the two-layer weak window is also changed, as shown in equation 18:

the updating method of the filtering tracker weight coefficient s (n) of the two-layer weak window real-time identification module is shown as formula 19:

the convergence speed of the system for assisting the noise excitation of the two-layer weak window in real time identification is higher than that of the white noise two-layer weak window in identification, and the convergence performance is better.

Preferably, the initial configuration procedure: before the adaptive noise suppression algorithm is operated, a NUC505 hardware module is configured, system initialization is realized through codes, the operation objects of the module codes are a processor core and a hardware controller of a chip, and the ANC system is initialized and configured with the following steps: before executing an ANC program, initializing configuration, UserInit () and Noise interface initialization (Noise _ API _ Init ()) setting are carried out on the NUC505, and CPU main frequency is set to be 96 MHZ; initializing UserInit (), wherein functions comprise initialization configuration of UARTO, GPIO, NVIC, 12S, timers, 12C and LEDs, and Noise _ APl _ Init initializes the functions required by the algorithm and sets variables to 0;

when the UserInit is set, the method comprises the steps of initializing a board-level support packet, initializing a minimum system task scheduling system and initializing a task, wherein the task initialization assigns an initial value to an array, stores a function pointer of a system task, a user task function pointer and a task time slice in the array, and starts to fetch instructions from a message queue when the function enters a while loop and starts to execute an adaptive noise suppression algorithm after the initialization is completed.

Compared with the prior art, the innovation points and advantages of the application are as follows:

(1) according to the harmonic tracking canceller, adaptive noise suppression is introduced into a core module of the harmonic tracking canceller, improvement is performed on the two aspects of an ANC system structure and an algorithm, and the frequency of a harmonic can be acquired in advance based on a high-voltage direct-current power grid, so that a feedforward system is adopted. Due to the fact that the working environment of the power grid is complex, in order to avoid the situation that the built harmonic tracking canceller is affected and track and cancel power grid harmonics in real time, a real-time identification algorithm containing two layers of weak windows is adopted, the control module structure and the algorithm of the harmonic tracking canceller are designed, the structure of the harmonic tracking canceller is improved, the algorithm is transplanted to the NUC505 controller, and single-frequency-point and double-frequency-point harmonic suppression comparison experiments and analysis are completed. Experimental results show that the harmonic tracking canceller based on self-adaptive noise suppression has good noise reduction performance, a harmonic suppression system has a clear structure, simple equipment and high algorithm efficiency, the harmonic suppression effect on a power grid is good, harmonic current generated by the power grid is well suppressed to cause resonance, interference communication and radar electronic facilities among line-to-line capacitors, and the problem of harmonic pollution is effectively solved.

(2) The application designs and realizes a harmonic tracking canceller with good dynamic tracking performance, firstly designs and models the overall structure of a harmonic tracking canceller system, then designs an adaptive noise suppression algorithm by analyzing the application scene of the harmonic tracking canceller and the characteristics of harmonics to be eliminated, and finally designs a hardware system of a filter tracker, wherein the adaptive noise suppression algorithm comprises a two-layer weak window white noise excitation real-time identification algorithm and an improved assistant noise excitation real-time identification algorithm; the two-layer weak window white noise excitation real-time identification algorithm and the improved assisting noise excitation real-time identification algorithm are applied to a control module of a harmonic tracking canceller, and fast tracking and cancellation of current harmonics are achieved. The cost and the expansibility of a control module are comprehensively considered, a NUC505 chip based on an ARMport-m 4 kernel is used as a system controller, and the adaptive noise suppression algorithm based on the NUC505 chip is contrastively analyzed, so that the single-frequency point noise reduction efficiency and the double-frequency point noise reduction efficiency are greatly improved, the tracking efficiency of power grid harmonics is improved by 32.4%, the effective rate of harmonic cancellation is improved by 39.3%, the system hardware cost is reduced by more than 30%, the high-efficiency and reliable suppression of the power grid harmonics is realized, the power grid power quality is improved, and the normal operation of various electronic and communication devices is protected.

(3) The harmonic characteristic in the high-voltage direct current power grid system provides a real-time identification self-adaptive noise suppression algorithm containing two layers of weak windows, a harmonic tracking canceller control module platform is changed, an ARM-based NUC505 chip is selected to replace a common DSP chip to serve as a platform of the self-adaptive noise suppression algorithm, so that the cost of the system is reduced, the expansibility of the system is enhanced, a master-slave processor control structure is designed based on the NUC505 chip, a harmonic tracking canceller tightly matched with hardware and software is designed, the influence of the external complex environment is avoided, the requirement of harmonic suppression is met, the harmonic interference in a power grid is effectively suppressed, the influence of the impedance, the frequency and the load change of the system is avoided, the harmonic tracking canceller with good dynamic tracking performance is provided, the power quality of the power grid is improved through efficient harmonic suppression, and the safe and reliable operation of various electric equipment is guaranteed, improving the surrounding electromagnetic environment.

(4) The method writes a white noise excitation two-layer weak window real-time identification program and an improved assisting noise excitation real-time identification program on the basis of the white noise excitation two-layer weak window real-time identification program, and analyzes the influence of step length and the order of a filter tracker on the step length and the order. The order of the filter tracker is set to be 12 through multiple times of simulation demonstration, and the optimal step size of the filter tracker is set on the basis. The method comprises the following steps of respectively carrying out single-frequency point noise reduction analysis on the harmonic tracking canceller transplanted with two different algorithms, selecting one single-frequency point experimental point for analysis, selecting a good assistant noise excitation algorithm when verifying the double-frequency point, and showing the experimental results: the algorithm has obvious effect of eliminating the noise of the double frequency points, and the noise reduction of the two frequencies basically cannot influence each other. The good noise reduction effect of dual-frequency point derives from a main multi-processor structure that harmonic tracking canceller adopted for the processing speed is accelerated, and entire system's throughput reinforcing has avoided the interference between each frequency point, has proved that the effect of the harmonic tracking canceller scheme of this application promotes obviously, and system safety is high-efficient, and the robustness is good, is fit for harmonic tracking under the various electric wire netting environment and offsets.

Drawings

Fig. 1 is a schematic diagram of the overall structural design of a harmonic tracking cancellation system.

FIG. 2 is a schematic diagram of a harmonic tracking cancellation system modeling.

FIG. 3 is a simplified harmonic tracking cancellation system modeling diagram.

Fig. 4 is a schematic diagram of a forward filtering structure of a harmonic tracking cancellation system.

FIG. 5 is a diagram of a processor control architecture employing a master and multiple slaves.

FIG. 6 is a schematic block diagram of a FXLMS white noise excitation-based real-time identification system.

FIG. 7 is a flow chart of a two-layer weak window white noise excitation real-time identification algorithm.

FIG. 8 is a schematic block diagram of an improved assisted noise excitation real-time identification algorithm.

FIG. 9 is a flow chart of an improved assisted noise excitation real-time identification algorithm.

Fig. 10 is a statistical diagram of the noise reduction amount convergence time and the settling time at six frequency points.

FIG. 11 is a comparison of a method for assisting noise excitation real-time identification.

FIG. 12 is a schematic diagram of noise reduction amount of the algorithm for assisting the real-time identification of the noise excitation two-layer weak window.

Detailed Description

The technical solution of the adaptive noise suppression harmonic tracking cancellation system for the direct current power grid provided by the present application is further described below with reference to the accompanying drawings, so that those skilled in the art can better understand the present application and can implement the present application.

With the development of a power grid comprehensive power technology, a large amount of harmonic interference is caused by nonlinear loads in a power grid, and how to effectively suppress the harmonic interference in the power grid is a key for maintaining normal operation of power electronic equipment. Because the filtering effect of the traditional passive filtering tracker is easily influenced by the impedance, frequency and load change of a system, the suppression of harmonic waves in a direct current power grid is restricted. Therefore, the harmonic tracking canceller is designed to have good dynamic tracking performance.

The application provides a control module which is applied to a harmonic tracking canceller, and the current harmonic can be quickly tracked and cancelled. The cost and the expansibility of a control module are comprehensively considered, the NUC505 chip based on the ARMportex-m 4 kernel is used as a system controller, and a comparison experiment is carried out on various self-adaptive noise suppression algorithms based on the NUC505 chip. Experiments prove that the harmonic tracking canceller based on the adaptive noise suppression can well suppress harmonic waves.

The method comprises the steps of firstly designing and modeling the overall structure of a harmonic tracking and counteracting system, then designing an adaptive noise suppression algorithm by analyzing the application scene of a harmonic tracking and counteracting device and the characteristics of harmonic waves to be eliminated, and finally designing a hardware system of a filtering and counteracting device.

First, the overall structure design of the harmonic tracking cancellation system

The harmonic tracking and cancelling system comprises a simulation dynamic power grid and a harmonic interaction suppression system, wherein the simulation dynamic power grid measures and calculates each parameter of actual equipment according to the working environment of the high-voltage direct-current power grid, the simulation dynamic power grid module is built by adopting a simulation noise source and a simulation load according to measurement data, the harmonic interaction suppression system comprises a direct-current power grid harmonic acquisition and conversion module and a self-adaptive noise suppression module, and the schematic diagram of the overall design scheme is shown in figure 1.

The working principle of the harmonic tracking cancellation system is as follows: the current harmonic of the direct current power system is converted into a voltage signal through a current transformer and a signal modulation unit and injected into a self-adaptive noise suppression system, the self-adaptive noise suppression system synthesizes a signal with the same amplitude and opposite phase with the input noise signal according to the characteristics of the input noise signal to cancel a primary harmonic signal, the process is a real-time harmonic cancellation process, the processing time of an algorithm on the input signal is shorter than the time of the signal passing through a two-layer weak window, and a CPU in an ANC system is required to have higher processing capacity.

It can be seen from fig. 1 that the harmonic adaptive noise suppression module comprises two inputs: error signals and noise signals (harmonic signals); one output: a control signal; the control signal and the noise signal have the same amplitude and opposite phases, the control signal cancels the noise signal, the error signal is injected into the ANC system again, and the weight coefficient of the filtering tracker is adjusted until the error meets the minimum root mean square principle.

The current transformer is based on the Rogowski coil, is only used for measuring the changing current, the output of the current transformer is equivalent to the differentiation of a current signal to time, the original current signal is restored through an integrating circuit of a voltage signal, namely a signal modulation unit of the application, the system comprises the current transformer 1 and the current transformer 2, the current transformer 1 and the current transformer convert the changing current signal in the circuit into the voltage signal, and the harmonic signal is converted into the voltage signal which is easy to measure by the current signal.

For the whole system, the signal modulation module plays a role of a bridge, processes the voltage signal output by the current transformer, converts the voltage signal into a voltage signal from a current signal, realizes real reduction of the current signal in the power grid, and finally injects the signal into the self-adaptive noise suppression system for processing.

Modeling of harmonic tracking cancellation system

It can be seen from the system diagram 1 that the primary harmonic current signal I1 is superimposed with the control signal I2 to generate an error current signal I3, I3 reaching the current transformer 2 through an analog load. The error current signal I3 is converted into a voltage signal through a current transformer, the voltage signal is integrated and A/D converted by a signal modulation unit and finally transmitted to an adaptive noise suppression module to adjust the weight coefficient of the filtering tracker, and adaptive control is realized.

The control signal is obtained by a two-layer signal through a D/A, a capacitor and a power amplifier, a physical channel generated from the two-layer signal to a current transformer 1 is a two-layer path S '(z), a channel formed by the current transformer 2, a signal modulation unit and an A/D is R (z), a transfer function from a primary harmonic current signal to a module for generating an error signal I3 in an overlapping mode is P (z), a reference signal x (n) is strictly related to the primary signal, a signal in the overlapping time is regarded as a reference signal and is obtained through P' (z), and a modeling schematic diagram of a harmonic tracking cancellation system is shown in FIG. 2.

For the error signal z change, i.e. frequency domain transformation, the expression is shown in formula 1:

E(z)＝X(z)[P'(Z)-S'(Z)W _n (z)]r (z) formula 1

the system modeling diagram 2 is shown as figure 3. Based on a simplified harmonic tracking cancellation system block diagram, an expression of a primary path transfer function P (z) is obtained as shown in a formula 3, and an expression of a transfer function S (z) of a two-layer path is obtained as shown in a formula 4:

p (z) ═ r (z) P' (z) formula 3

S (z) ═ r (z) S' (z) formula 4

the expression of the weight coefficient of the optimal filtering tracker is inversely proportional to the transfer function of the two-layer weak window, the two-layer weak window is relatively complex in passing through a physical path and generates delay, p (z) is also set to have corresponding delay for obtaining the optimal weight coefficient, if the delay of p (z) is not enough, the delay of the two-layer weak window is not enough to compensate, so that the system diverges, and in addition, when no two-layer signal is generated at a certain frequency point, it is stated that s (z) at the point is 0, and the frequency of the frequency point cannot be cancelled.

Third, harmonic tracking cancellation system software design

(I) establishing a system control module structure

The harmonic tracking canceller comprises a feedforward system and a feedback system, the feedforward system comprises a harmonic tracking cancellation system of the reference signal, and the feedback system avoids synthesis of the reference signal and is suitable for being adopted under the condition that the reference signal is not easy to obtain. The environment is a high-voltage direct-current power grid, the environment is complex and is easily interfered by external signals, and if a feedback system is adopted, the system is greatly interfered by the voltage of the power grid when the power grid is started, so that the feedback system is caused to generate self excitation. In addition, the feedback system can generate self-excitation phenomenon when the system is in an unstable state, so that the power amplifier module is burnt instantly, and the problem reason is difficult to capture.

In order to avoid the self-excitation phenomenon, the harmonic tracking cancellation system is based on a forward filtering structure, and the system structure diagram is shown in fig. 4.

The processing time of the broadband feedforward system in a chip is shorter than the propagation time of two-layer access, so that the elimination of broadband random noise can be met, otherwise, the noise reduction performance of the system is reduced, and the narrowband feedforward system is effective for any periodic narrowband signal and is generally not limited by the factors. The harmonic characteristics in the direct current power grid are narrow-band signals, and primary harmonic signals in the direct current power grid are easy to obtain, so that a narrow-band feedforward system structure is adopted.

Real-time identification method for (II) and (II) layer weak windows

Considering that a two-layer weak window module of a direct current network system comprises a D/A, a capacitor, a current sensor and an electric load, and is easily changed by external interference, the two-layer weak window needs to be estimated in real time to realize self-adaptive noise suppression of a harmonic tracking canceller, a two-layer weak window real-time identification method is adopted, and a noise excitation two-layer weak window real-time identification system block diagram is shown in FIG. 6.

f (n) represents the two-layer weak window identification error signal; v (n) represents a white gaussian noise signal; u. of _s Represents an update step value; k represents the K-th order of the filter tracker in the range of 0, M]Where M-1 is the order of the two-layer weak window filter tracker.

p(n)＝ax ₀ (n)+bx ₁ (n)+v _p (n) formula 6

x ₀ (n) ═ cos wn formula 7

x ₁ (n) ═ sin wn formula 8

Two layer source y ₀ (n) is represented by formula 9:

y ₀ (n)＝x ₀ (n)w ₀ (n)+x ₁ (n)w ₀ (n) formula 9

when the two-layer weak window identification system reaches a stable state,

the expression of the error signal e (n) is shown in equation 11:

e(n)＝p(n)-y′(n)＝p(n)-s(n)*[y ₀ (n)-v(n)]formula 11

The coefficients are updated along with e (n), and the filter tracker weight coefficients are iterated as shown in equations 13 and 14:

u is a step size factor, where

The signals generated after passing through the two-layer weak window are shown in the formulas 15 and 16:

Design of harmonic tracking and counteracting hardware system

Chip hardware design

The harmonic tracking canceller works in a high-voltage direct-current power grid, and the working environment comprises a large number of nonlinear loads, a communication system and a storage battery pack. In addition, the working environment of the power grid has humid climate and large temperature change. This requires the selection of a chip that is suitable for operation in harsh environments. The NUC505 chip based on the ARMCortex-M4F processor is adopted in the direct current power grid, the anti-jamming capability is strong, the chip comprises 2Mbyte SPIFlash and 128Kbyte eSRAM, and a plurality of peripheral devices are further arranged, comprise UART, 12C, I2S and 12-bit ADC, and are suitable for processing audio signals.

In the I2S transfer protocol, a data signal, a clock signal, and a control signal are separately transferred, and they are respectively transferred using transmission lines SD (serial data line), WS (left and right channel selection line), SCK (synchronous clock signal line).

Structure design of harmonic tracking canceller system

However, the NUC505 acts as a controller and has a data processing capability that is far from that of a dedicated DSP. In order to prevent the data processing capacity from becoming a factor limiting the chip adaptive noise suppression, the structure of the harmonic tracking canceller system is improved, and a control mode of one master and multiple slaves is adopted to convert a multi-channel system into a plurality of single-channel systems to eliminate harmonic noise. The computation of a single adaptive noise suppression algorithm is within the NUC505 processing capacity range, the algorithm processing requirement is met, the problem of insufficient chip processing capacity is completely avoided, and the harmonic tracking canceller can achieve a good noise reduction effect. A processor control architecture employing a master and multiple slaves is shown in fig. 5.

The control structure of a master multi-slave processor is the combination of a plurality of single-channel controls, reduces the mutual interference of each frequency point and reduces the computational complexity of the processor, and the specific working mode is as follows: firstly, a computer obtains a harmonic signal in a detection signal source through FFT calculation, and sends the detected harmonic signal value to a main processor, namely an upper NUC505 through a UART (universal asynchronous receiver transmitter) and a transmitter; then the main processor (upper NUC505) controls the working state of a plurality of slave processors (lower NUC505) through IC communication, when the detected signal is single-frequency point noise, the main processor only needs to select one slave processor to execute an adaptive noise suppression algorithm, when the detected signal is multi-frequency point signal, the main processor controls the plurality of slave processors to work, finally the processor outputs a control signal, namely a signal which has the same amplitude and opposite phase with the primary noise, the control signal is output to the system after power amplification and then is counteracted with the original noise signal on an analog dynamic power grid, the counteracted error signal passes through the current transformer 2, the signal modulation unit is injected into the slave processors, the weight coefficient of a filter tracker of ANC is adjusted, and the adaptive control of the system is realized.

The advantages of adopting the system structure are: the system can be kept to operate for a long time, the stability is good, and the system can adapt to the working environment of a direct-current power grid; the interference among multiple frequency points is avoided, the chip processing speed is high, and the system can achieve convergence in a short time.

3.5 summary of the present application

The method carries out algorithm and structure selection on the harmonic tracking and canceling system, designs the narrow-band feedforward ANC algorithm for identifying the two-layer weak window in real time according to the application environment of the harmonic tracking and canceling device and the characteristics of eliminating noise, and provides the ANC algorithm containing white noise excitation. In consideration of the cost and the expansibility of the harmonic tracking canceller system, the NUC505 chip based on the ARM core is adopted, the chip is high in control capability, low in cost and good in expansibility, in addition, the data processing capability of the chip can completely meet the calculation requirement of the adaptive noise suppression control algorithm, and after the chip is selected, the system structure of the harmonic tracking canceller is designed in detail.

Fifth, integral algorithm process of harmonic tracking offset system

The method is characterized in that a real-time identification narrow-band feedforward adaptive noise suppression algorithm is adopted and is realized on a NUC505 chip, a peripheral system, a noise application interface and parameters in an ANC algorithm are initialized before a program runs, and after the initialization is completed, the chip starts to read data and performs adaptive noise suppression algorithm processing until the data processing is finished.

The external environment of a direct current power system is complex, a two-layer channel (external physical channel) continuously changes, the system needs to perform real-time modeling on a two-layer weak window, a transfer function of the two-layer weak window is continuously updated according to the change of the external environment, and a two-layer weak window white noise excitation real-time identification algorithm and an improved assisting noise excitation real-time identification algorithm are adopted.

Real-time identification algorithm design for white noise excitation of (I) two-layer weak window

The white noise excitation real-time identification system comprises two modules, namely an adaptive noise suppression module and a two-layer weak window modeling module, wherein each module comprises a filtering tracker: one is an active control filtering tracker based on the FXLMS algorithm, the other is a two-layer weak window real-time identification filtering tracker based on the LMS algorithm, and a schematic block diagram of an FXLMS white noise excitation real-time identification system is shown in fig. 6.

The algorithm comprises a system initialization module, an LMS algorithm weight coefficient updating module and a two-layer weak window transfer function estimation module, and a flow chart of the algorithm description is shown in FIG. 7.

Before the algorithm is transplanted to the NUC505, the program is simulated on the MATLAB, and the setting of factors influencing the performance of the algorithm in the simulation process includes:

(1) order of the filter tracker: theoretically, the higher the order of the filter tracker, the better the noise cancellation effect. However, in practical application, the order of the filtering tracker is set too large, which easily causes the CPU of the chip to be insufficient, the noise cancellation effect to be poor, and even causes the ANC system to diverge. However, the order of the filtering tracker is set to be too small, which easily causes slow system convergence and poor convergence effect. In order to find the proper order of the filtering tracker, multiple simulation argumentations show that the noise elimination effect of single and double frequency points is better when the order is 12.

(2) Step size selection: the convergence speed is slowed down when the step length is too small, the noise cancellation effect is poor when the step length is too large, and the harmonic wave elimination needs to be completed in a short time when the system is applied to a high-voltage direct-current power system. By comprehensively considering the above conditions, the step size of the FXLMS filter algorithm is 0.003, and the step size of the LMS filter is 0.01.

The adoption of the real-time identification method of the two-layer weak window improves the self-adaptive capacity of the system, and in order to improve the accuracy of real-time identification, the energy of white noise needs to be increased to drive the two-layer weak window to work.

(II) improved assisted noise excitation real-time identification algorithm

The assistant noise excitation real-time identification algorithm is an improvement of a white noise excitation two-layer weak window real-time identification algorithm, and the white noise energy is restrained by adopting an error signal to obtain a better harmonic suppression effect and system stability.

The method reduces the energy of white noise to reduce the influence of the white noise on an error signal e (n), restrains the white noise signal based on the error signal, and improves the constraint condition of the narrow-band feedforward ANC system, namely, the white noise is restrained by carrying out unit delay | e (n-1) | on the error signal. A block diagram of a system for assisting noise excitation real-time recognition is shown in FIG. 8.

the two-layer weak window identification module introduces an absolute value of unit delay of an error signal and excitation y 'of a two-layer weak window' ₀ (n) represented by formula 17:

y′ ₀ (n)＝y ₀ (n) -v (n) e (n-1) | formula 17

f (n) represents the two-layer weak window identification error signal; v (n) represents a white gaussian noise signal; u. of _s The representation of the two-level weak window recognition error f (n) changes, as shown in equation 18:

description of the algorithm a flow chart, as shown in fig. 9:

the convergence speed of the system for assisting the noise excitation of the two-layer weak window in real time identification is higher than that of the white noise two-layer weak window in identification, and the convergence performance is better. The quality of the two algorithms is judged, the two algorithms are not enough only through simulation experiments, the two algorithms are realized by building an experiment platform, and the noise reduction amount, the convergence time and the stability of the two algorithms at the single-frequency point noise position are compared.

(III) initialization configuration procedure

Before the adaptive noise suppression algorithm is operated, a NUC505 hardware module is configured, system initialization is realized through codes, the operation objects of the module codes are a processor core and a hardware controller of a chip, and the ANC system is initialized and configured with the following steps: before executing an ANC program, initializing configuration, UserInit () and Noise interface initialization (Noise _ API _ Init ()) setting are carried out on the NUC505, and CPU main frequency is set to be 96 MHZ; initializing UserInit (), wherein functions comprise initialization configuration of UARTO, GPIO, NVIC, 12S, timers, 12C and LEDs, and Noise _ APl _ Init initializes the functions required by the algorithm and sets variables to 0;

Sixthly, noise reduction experiment and result analysis

Single frequency point noise reduction

Harmonic components in a direct current power system bring great harm to a power grid, and in the harmonic, high-frequency harmonic has great influence on power system equipment, so that the harmonic is urgently to be inhibited. The performance of an ANC algorithm in a hardware system is tested, and single-frequency point noise elimination comparison analysis is respectively carried out on a white noise excitation real-time identification algorithm and an assisted noise excitation real-time identification method in an experiment.

In the high-voltage direct-current power system, the power frequency is 50HZ, 12-pulse rectifier output current contains 12n (n is 1, 2 and 3 …) subharmonic components, and frequency points between 1KHZ and 2KHZ are selected in experiments for test analysis. Measurements were made every 200HZ for a total of six frequency points. The noise elimination conditions of all frequency points are compared through a frequency spectrograph in the experiment. Besides the adoption of a frequency spectrograph for observing the noise reduction condition, an oscilloscope is also adopted for observing the amplitude change before and after the noise elimination, and the noise reduction amount of the harmonic wave is calculated through the amplitude change.

Fig. 10 is shown by the statistics of the noise reduction, convergence time and settling time of the six frequency points selected according to the experiment.

The noise elimination effect of the white noise excited two-layer weak window real-time identification algorithm and the noise excitation assisting two-layer weak window real-time identification algorithm is good. Compared with the prior art, the noise reduction effect for assisting the real-time identification of the noise excitation is better.

Comparing fig. 11 and 12 can lead to the following conclusions:

(1) analysis from convergence time: the average convergence time of the white noise excitation is 15s, and the average convergence time of the assisting noise excitation is 5s, so that the assisting noise excitation is faster to converge.

(2) From the system performance stability analysis: the white noise excitation starts to diverge after converging for a few minutes, and the stability is poor. After the noise excitation is assisted to converge, the observation is carried out for a plurality of hours without divergence, and the convergence effect is good.

By combining the comparison, the system noise elimination performance of the assisting noise excitation two-layer weak window real-time identification algorithm is better.

The reason for the above phenomenon is analyzed to conclude the following:

(1) when a white noise excitation real-time identification algorithm is adopted, the injection of white noise can cause interference on a two-layer weak window and influence on modeling of the two-layer weak window, and when the interference introduced by random noise keeps a large value, divergence in the modeling process can be caused. This is the reason why the white noise excitation recognition system is not stable. An improved assistant noise excitation real-time identification algorithm is adopted, unit time delay of white noise and an error signal are jointly used as two-layer weak window excitation, and system convergence time is prolonged. When auxiliary noise excitation is adopted, | e (n-1) | is larger at the beginning of a two-layer weak window, at the moment, the weight coefficient of the filtering tracker rapidly moves to the optimal weight coefficient, and | e (n-1) | becomes smaller after the filtering tracker operates for a period of time, and the weight coefficient of the filtering tracker is basically close to the optimal weight coefficient. The use of the assisting noise excitation converges faster than the white noise excitation.

(2) In the process of assisting noise to excite the two-layer weak window real-time identification system to operate, after the system converges for 30 minutes, the harmonic cancellation effect begins to fluctuate, and the system is unstable when the harmonic cancellation effect is serious. Reason investigation: checking the ANC algorithm, the floating point arithmetic unit (FPU) of NUC505, finds no problem. Finally, the NUC505 hardware problem is checked, system control codes do not perform algorithm processing, only I2S input and output find the recurrence phenomenon, and the phenomenon disappears by adopting the 12S routine. The positioning problem is that I2S handles code problems, and DMA timing that does not handle I2S causes NUC505 to output an error, and thus the system is unstable. Therefore, for applications with strict timing requirements for data transceiving, the data transfer path must be carefully planned, and each link should be strictly controlled, especially paying attention to the contention of the DMA controller for the bus.

(II) Dual frequency Point noise reduction

According to the noise reduction experiment of the single frequency point, the system stability and the noise reduction amount of the self-adaptive noise suppression system with the assistant noise excitation are better than those of the self-adaptive noise suppression system with the white noise excitation. The method adopts a self-adaptive noise suppression algorithm containing auxiliary noise excitation to offset the noise of the double frequency points, and adopts frequency mixing noise with the frequency of 1000HZ and 2000HZ as the noise input of the self-adaptive noise suppression system.

It can be seen from fig. 12 that the noise reduction amount of the double-frequency point noise reduction reaches 19.65dB at 1000HZ and reaches about 26dB at 2000HZ, and it can be seen that the noise reduction amount is substantially the same as the noise reduction amount of the single-frequency point at the point. When the double-frequency point noise reduction is carried out, the influence between the two frequency points is basically avoided, and good noise reduction effect is achieved. Analyzing the double-frequency point noise elimination phenomenon to draw the following conclusion:

(1) the noise reduction amount at the frequency points of 1000HZ and 2000HZ is different, and the noise reduction amount is substantially the same as that at a single frequency point. Indicating that there is little interference between the two frequencies.

(2) The adopted one-master multi-slave control mode ensures that the noise of each frequency point hardly has interference, and the noise reduction amount of each frequency point reaches the maximum.

The power grid harmonic seriously influences the normal work of the electric equipment, and when a large amount of harmonic interference is generated in a power grid system, the electric energy loss is increased, and the interference to other electronic and communication equipment is also caused. The passive filtering tracker in the prior art is easily influenced by the external environment and cannot meet the requirement of harmonic suppression. The adaptive noise suppression distribution is used as a core module of the harmonic tracking canceller, improvement is carried out on the aspects of ANC system structure and algorithm, and a feedforward system is adopted because the frequency of harmonics can be acquired in advance in the high-voltage direct-current power grid. Because the working environment of the power grid is complex, the built harmonic tracking canceller is easily influenced, and in order to avoid the influence, the harmonic wave of the power grid is tracked and cancelled in real time, a real-time identification algorithm containing two layers of weak windows is adopted, the control module structure and the algorithm of the harmonic tracking canceller are designed, the structure of the harmonic tracking canceller is improved, various algorithms are transplanted to the NUC505 controller, and the single-frequency-point and double-frequency-point harmonic suppression contrast experiment is completed. Experimental results prove that the harmonic tracking canceller based on the adaptive noise suppression has better noise reduction performance.

Claims

1. The direct-current power grid self-adaptive noise suppression harmonic wave tracking and canceling system is characterized in that the overall structure of the harmonic wave tracking and canceling system is designed and modeled, then a self-adaptive noise suppression algorithm is designed by analyzing the application scene of the harmonic wave tracking and canceling device and the characteristics of harmonic waves to be eliminated, the self-adaptive noise suppression algorithm comprises a two-layer weak window white noise excitation real-time identification algorithm and an improved assisting noise excitation real-time identification algorithm, and finally a hardware system of a filter tracker is designed;

the harmonic tracking and counteracting system comprises a simulation dynamic power grid and a harmonic interactive suppression system, wherein the simulation dynamic power grid measures and calculates each parameter of actual equipment according to the working environment of the high-voltage direct-current power grid, the simulation dynamic power grid module is built by adopting a simulation noise source and a simulation load according to measurement data, and the harmonic interactive suppression system comprises a direct-current power grid harmonic acquisition and conversion module and an adaptive noise suppression module;

the working principle of the harmonic tracking cancellation system is as follows: the current harmonic waves of the direct current power system are converted into voltage signals through a current transformer and a signal modulation unit and injected into a self-adaptive noise suppression system, the self-adaptive noise suppression system synthesizes signals with the same amplitude and opposite phases as the input noise signals according to the characteristics of the input noise signals to cancel primary harmonic signals, the process is a real-time harmonic cancellation process, and the processing time of an algorithm on the input signals is shorter than the time of the signals passing through a two-layer weak window;

2. The direct current power grid adaptive noise suppression harmonic tracking cancellation system according to claim 1, wherein the harmonic tracking cancellation system models: the primary harmonic current signal I1 and the control signal I2 are superposed to generate an error current signal I3, the I3 reaches the current transformer 2 through an analog load, the error current signal I3 is converted into a voltage signal through the current transformer, the voltage signal is integrated and A/D converted by the signal modulation unit and finally transmitted to the adaptive noise suppression module to adjust the weight coefficient of the filtering tracker, and adaptive control is achieved;

E(z)＝X(z)[P′(Z)-S′(Z)W _n (z)]r (z) formula 1

Where x (z) is the z-transform of the reference signal, and when the system converges, the error signal e (z) is equal to 0, and the adaptive filter tracker obtains the optimal weight coefficient W ₀ Expressed as shown in equation 2:

p (z) r (z) P' (z) formula 3

S (z) ═ r (z) S' (z) formula 4

3. The direct current power grid adaptive noise suppression harmonic tracking cancellation system according to claim 1, wherein a system control module structure is established: the harmonic tracking and counteracting system is based on a forward filtering structure, the processing time of the broadband feedforward system in a chip is shorter than the propagation time of two-layer access, so that the elimination of broadband random noise can be met, primary harmonic signals in a direct-current power grid are easy to obtain, and a narrow-band feedforward system structure is adopted;

the narrowband feedforward system needs to synthesize a reference signal, the reference signal is synthesized by adopting a single-frequency notch filter tracker based on an FXLMS algorithm, mutually orthogonal sine signals are used as the input of the system, then the weight coefficients of the filter tracker are updated through the LMS algorithm respectively, and finally a two-layer signal is synthesized and injected into a two-layer weak window to control the periodic noise of a single frequency point or a discrete frequency point.

4. The direct current power grid adaptive noise suppression harmonic tracking cancellation system according to claim 1, wherein the two-layer weak window real-time identification method comprises the following steps: estimating the two-layer weak window in real time to realize the self-adaptive noise suppression of the harmonic tracking canceller, wherein f (n) represents the identification error signal of the two-layer weak window; v (n) represents a white gaussian noise signal; u. of _s Represents an update step value; k represents the K-th order of the filter tracker in the range of 0, M]Where M-1 is the order of the two-layer weak window filter tracker;

p(n)＝ax ₀ (n)+bx ₁ (n)+v _p (n) formula 6

v _p (n) white noise signal added for real environment; a, b are Fourier series, and the frequency w, x of the synchronous signal detected by the synthetic reference signal ₀ (n)、x ₁ (n) the synthetic mode is shown as formula 7 and formula 8:

x ₀ (n) ═ cos wn formula 7

x ₁ (n) ═ sin wn formula 8

Two layer source y ₀ (n) is represented by formula 9:

y ₀ (n)＝x ₀ (n)w ₀ (n)+x ₁ (n)w ₀ (n) formula 9

w is the primary noise frequency detected by the sensor or FFT transformation, the real-time identification system estimates the two-layer weak window in real time, and the two-layer weak window transfer function iterative formula is shown in equation 10:

when the two-layer weak window identification system reaches a stable state,

the expression of the error signal e (n) is shown in formula 11:

e(n)＝p(n)-y′(n)＝p(n)-s(n)*[y ₀ (n)-v(n)]formula 11

Updating the coefficients with e (n);

5. The direct current power grid adaptive noise suppression harmonic tracking cancellation system according to claim 1, wherein a harmonic tracking cancellation hardware system is designed: the method comprises the steps that a NUC505 chip based on an ARMCortex-M4F processor is adopted in the direct current power grid, the chip comprises 2 MbytesPFash and 128KbytesRAM, and a plurality of peripherals including UART, 12C, I2S and 12-bitADC are arranged inside the chip and suitable for processing audio signals;

6. The direct current power grid adaptive noise suppression harmonic tracking cancellation system according to claim 1, wherein the harmonic tracking cancellation system is designed in a structure that: the structure of a harmonic tracking canceller system is improved, a control mode of one master and multiple slaves is adopted, a multi-channel system is converted into a plurality of single-channel systems to eliminate harmonic noise, and the computation amount of a single self-adaptive noise suppression algorithm is within the NUC505 processing capacity range;

the control structure of a master multi-slave processor is the combination of a plurality of single-channel controls, reduces the mutual interference of each frequency point and reduces the computational complexity of the processor, and the specific working mode is as follows: firstly, a computer obtains a harmonic signal in a detection signal source through FFT calculation, and sends the detected harmonic signal value to a main processor, namely an upper NUC505 through a UART; and then the master processor controls the working states of the plurality of slave processors through IC communication, when the detected signal is a single-frequency point noise, the master processor only needs to select one slave processor to execute an adaptive noise suppression algorithm, when the detected signal is a multi-frequency point signal, the master processor controls the plurality of slave processors to work, finally the slave processor outputs a control signal, namely a signal with the same amplitude as the primary noise and the opposite phase, the control signal is output to the system after power amplification and then counteracted with an original noise signal on an analog dynamic power grid, an counteracted error signal passes through a current transformer, the signal modulation unit injects into the slave processor, and the weight coefficient of a filtering tracker of ANC is adjusted, so that the adaptive control of the system is realized.

7. The direct current power grid adaptive noise suppression harmonic tracking cancellation system according to claim 1, wherein the overall algorithm flow of the harmonic tracking cancellation system is as follows: the method comprises the steps that a real-time identified narrow-band feedforward adaptive noise suppression algorithm is adopted and is realized on a NUC505 chip, a peripheral system, a noise application interface and parameters in an ANC algorithm are initialized before a program runs, and after the initialization is completed, the chip starts to read data and performs adaptive noise suppression algorithm processing until the data processing is finished;

a two-layer path of a direct current power system continuously changes, the system needs to model a two-layer weak window in real time, a transfer function of the two-layer weak window is continuously updated according to the change of an external environment, and a two-layer weak window white noise excitation real-time identification algorithm and an improved assisting noise excitation real-time identification algorithm are adopted.

8. The direct current power grid adaptive noise suppression harmonic tracking cancellation system according to claim 1, wherein a two-layer weak window white noise excitation real-time identification algorithm is designed: the white noise excitation real-time identification system comprises two modules, namely an adaptive noise suppression module and a two-layer weak window modeling module, wherein each module comprises a filtering tracker: one is an active control filtering tracker based on FXLMS algorithm, and the other is a two-layer weak window real-time identification filtering tracker based on LMS algorithm;

9. The direct current power grid adaptive noise suppression harmonic tracking cancellation system according to claim 1, wherein the improved assisting noise excitation real-time identification algorithm: the method is an improvement of a white noise excitation two-layer weak window real-time identification algorithm, and adopts an error signal to restrain white noise energy so as to obtain a better harmonic suppression effect and system stability;

y′ ₀ (n)＝y ₀ (n) -v (n) e (n-1) | formula 17

f (n) represents the two-layer weak window identification error signal; v (n) represents a white gaussian noise signal; u. u _s The representation of the recognition error f (n) of the two-layer weak window is also changed, as shown in equation 18:

the convergence speed of the system for assisting the noise excitation two-layer weak window real-time identification is higher than that of the white noise two-layer weak window identification, and the convergence performance is better.

10. The adaptive noise suppression harmonic tracking cancellation system for a direct current power grid according to claim 1, wherein a configuration program is initialized: before the adaptive noise suppression algorithm is operated, a NUC505 hardware module is configured, system initialization is realized through codes, the operation objects of the module codes are a processor core and a hardware controller of a chip, and the ANC system is initialized and configured with the following steps: before executing an ANC program, carrying out initialization configuration, UserInit () and Noise interface initialization (Noise _ API _ Init ()) setting on the NUC505, and setting the CPU main frequency at 96 MHZ; initializing UserInit (), wherein functions comprise initialization configuration of UARTO, GPIO, NVIC, 12S, timers, 12C and LEDs, and Noise _ APl _ Init initializes the functions required by the algorithm and sets variables to 0;