A method, device, terminal and medium for synchronous control of power system signals

Abstract

This application discloses a method, device, terminal, and medium for controlling power system signal synchronization, relating to the field of power system control technology. The technical solution provided by this application calculates the phase difference and frequency difference between the output signal and the reference signal based on their phase and frequency data, respectively. The phase difference and frequency difference are then input into a signal synchronization optimization model based on an adaptive neural network algorithm, which then outputs a synchronization signal through the operation of the signal synchronization optimization model. The signal synchronization optimization model, constructed using the adaptive neural network algorithm, can continuously update parameters based on the characteristics of the input data, perform self-training, and flexibly adjust to accommodate different frequency and phase drifts, thereby improving the stability and accuracy of power system signal synchronization.

Description

Technical Field

[0001] The present application relates to the field of power system control technology, and in particular to a power system signal synchronization control method, device, terminal and medium. Background Art

[0002] As power systems operate, signal synchronization is increasingly required in many situations. For example, in energy storage systems, the synchronization of the control angle with the reference angle determines whether the inverter system can smoothly commutate and whether the output AC signal phase and frequency are consistent with the grid. For example, when connecting circuit cores, it is also necessary to determine whether the phase and frequency of the connected circuits are synchronized, otherwise it will damage the stability of the grid. For example, signal synchronization technology may also be used when testing and analyzing the full current and resistive current phase of lightning arresters. For example, in partial discharge measurements, remote signal synchronization technology is also used because the signal acquisition and synchronization signals are generated in different locations.

[0003] However, since the signal synchronization process may involve multiple complex power electronic devices, noise interference, system nonlinearity and other factors, the clock frequency and phase used for signal synchronization may drift as the system runs over time, affecting the stability and accuracy of signal synchronization. Summary of the Invention

[0004] The present application provides a method, device, terminal and medium for controlling signal synchronization of an electric power system, which are used to solve the technical problems of low stability and accuracy of signal synchronization in existing electric power systems.

[0005] To solve the above technical problems, the present application provides a first aspect of a power system signal synchronization control method, comprising:

[0006] Acquire an output signal and a reference signal, wherein the output signal is a signal output by the host, and the reference signal is a signal transmitted from the slave to the host;

[0007] Calculating a phase difference and a frequency difference between the output signal and the reference signal according to the phase data and the frequency data of the output signal and the reference signal;

[0008] The phase difference and the frequency difference are input into a preset signal synchronization optimization model to output a synchronization signal through the operation of the signal synchronization optimization model, wherein the signal synchronization optimization model includes: a relationship function for reflecting the input and output relationship of the signal synchronization optimization model and an error weight optimization function for optimizing the weight coefficient of the signal synchronization optimization model, and the synchronization signal is the signal after the output signal and the reference signal are synchronized.

[0009] Preferably, the relationship function is specifically:

[0010]

[0011] Where, is the phase difference between the output signal and the reference signal at time t, is the frequency difference between the output signal and the reference signal at time t, is the synchronization signal at time t, W1 and W2 are network weights, b1 and b2 are bias terms, and f is the activation function.

[0012] Preferably, it also includes:

[0013] Based on the error factor data of power system signal synchronization and the corresponding weighting coefficients of each error factor, a comprehensive error relationship is determined to determine the bias term b2 in the relationship function based on the comprehensive error relationship. The error factors include: noise error, hardware nonlinear error and temperature change error.

[0014] Preferably, the error weight optimization function is specifically:

[0015]

[0016]

[0017]

[0018] Where, is the phase difference between the output signal and the reference signal at time t, is the frequency difference between the output signal and the reference signal at time t, η is the learning rate, and is the network weight at time t+1, and is the network weight at time t.

[0019] Preferably, it also includes:

[0020] According to the synchronization signal, the gain coefficient and the filter coefficient of the signal synchronization optimization model are updated according to a preset parameter update function.

[0021] Preferably, the parameter update function is specifically:

[0022]

[0023] Where, is the gain coefficient at time t+1, is the filter coefficient at time t+1, is the gain coefficient at time t, is the filter coefficient at time t, η is the learning rate, is the phase difference between the output signal and the reference signal at time t, is the frequency difference between the output signal and the reference signal at time t, is the synchronization signal at time t.

[0024] At the same time, the second aspect of the present application provides a power system signal synchronization control device, including:

[0025] a signal acquisition unit, configured to acquire an output signal and a reference signal, wherein the output signal is a signal output by the host, and the reference signal is a signal transmitted from the slave to the host;

[0026] a phase-frequency difference calculation unit, configured to calculate a phase difference and a frequency difference between the output signal and the reference signal, respectively, based on the phase data and the frequency data of the output signal and the reference signal;

[0027] A signal synchronization optimization unit is used to input the phase difference and the frequency difference into a preset signal synchronization optimization model to output a synchronization signal through the operation of the signal synchronization optimization model, wherein the signal synchronization optimization model includes: a relationship function for reflecting the input and output relationship of the signal synchronization optimization model and an error weight optimization function for optimizing the weight coefficient of the signal synchronization optimization model.

[0028] Preferably, it also includes:

[0029] A feedback optimization unit is used to update the gain coefficient and filter coefficient of the signal synchronization optimization model according to the synchronization signal and a preset parameter update function.

[0030] A third aspect of the present application provides a power system signal synchronization control terminal, comprising: a memory and a processor;

[0031] The memory is used to store program code, and the program code is used to implement the power system signal synchronization control method provided by the first aspect of the present application;

[0032] The processor is configured to read and execute the program code.

[0033] The fourth aspect of the present application provides a computer-readable storage medium, in which program code is stored. The program code is used to be read and executed by a processor to implement the power system signal synchronization control method provided in the first aspect of the present application.

[0034] It can be seen from the above technical solutions that this application has the following advantages:

[0035] The technical solution provided in this application calculates the phase and frequency differences between the output signal and the reference signal based on their phase and frequency data, respectively. This phase and frequency differences are then input into a signal synchronization optimization model based on an adaptive neural network algorithm. The signal synchronization optimization model, constructed using an adaptive neural network algorithm, can continuously update parameters based on the characteristics of the input data, perform self-training, and flexibly adjust to accommodate varying frequency and phase drifts, thereby improving the stability and accuracy of power system signal synchronization. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0037] Figure 1 Schematic diagram of the power system architecture.

[0038] Figure 2 This is a flow chart of an embodiment of a method for synchronous control of power system signals provided in this application.

[0039] Figure 3 This is a structural diagram of a power system signal synchronization control device provided in this application.

[0040] Figure 4 This is a flow chart of an embodiment of a power system signal synchronization control terminal provided in this application. DETAILED DESCRIPTION

[0041] The embodiments of the present application provide a method, device, terminal and medium for controlling power system signal synchronization, which are used to solve the technical problems of low stability and accuracy of existing power system signal synchronization.

[0042] In order to make the purpose, features, and advantages of the invention of this application more obvious and easy to understand, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the embodiments described below are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0043] See also Figure 1 and Figure 2 , the present application provides a power system signal synchronization control method, comprising:

[0044] Step 101: Obtain an output signal and a reference signal;

[0045] The output signal is the signal output by the host, and the reference signal is the signal transmitted from the slave to the host.

[0046] Step 102: Calculate the phase difference and frequency difference between the output signal and the reference signal based on the phase data and frequency data of the output signal and the reference signal.

[0047] Step 103: input the phase difference and the frequency difference into a preset signal synchronization optimization model to output a synchronization signal through calculation of the signal synchronization optimization model;

[0048] The signal synchronization optimization model includes: a relationship function for reflecting the relationship between the input and output of the signal synchronization optimization model and an error weight optimization function for optimizing the weight coefficient of the signal synchronization optimization model.

[0049] It should be noted that if Figure 1 As shown in the figure, the upper circuit can be called a slave, and the lower circuit can be called a master. In the slave, the reference signal is consistent with the phase-locked loop reference signal. Among them, the reference signal refers to the reference signal that is synchronized when the phase and frequency are synchronized, such as the standard voltage of the large power grid of the energy storage system; the voltage of one of the circuits during circuit phase verification; the operating voltage of the lightning arrester during the full current and resistive current phase tests of the lightning arrester; the operating voltage during partial discharge measurement may come from the voltage and current signals (analog quantities) of the power grid system, or it can be a self-set digital reference signal. If it is an analog signal, it needs to pass through an LPF (Low Pass Filter) to filter out the high-frequency noise components and then be converted into a digital signal through an ADC (analog to digital converter). The reference phase and frequency in the slave are sent to the master via wireless communication, and the master obtains the phase and frequency information therein through the wireless signal; at the same time, the master obtains the phase frequency of the signal from the signal output system that needs to be synchronized. The output system is then synchronized with the reference signal to obtain the signal after the output signal and the reference signal are synchronized, that is, the synchronization signal. Among them, synchronization and anti-drift processing are both Figure 1 It is implemented in the signal synchronization module.

[0050] According to the method provided in this embodiment, first, an output signal generated by the signal output system on the host side and a reference signal transmitted to the host by the reference signal of the slave through the wireless module are respectively obtained. Then, the phase characteristics and frequency characteristics of the obtained output signal and reference signal are extracted. Then, based on the phase data and frequency data of the output signal and the reference signal, the phase difference and frequency difference between the output signal and the reference signal are respectively calculated.

[0051] The calculation formulas for phase difference and frequency difference are as follows:

[0052]

[0053] in, is the phase difference signal, are the phases of the acquired reference signal and output signal respectively;

[0054]

[0055] in, is the frequency error signal, are the frequencies of the acquired reference signal and output signal, respectively.

[0056] Inputting the phase difference and the frequency difference into a preset signal synchronization optimization model to output a synchronization signal through calculation of the signal synchronization optimization model;

[0057] More specifically, the signal synchronization optimization model provided in this embodiment has a neural network structure that is a feedforward network, the input layer includes phase error and frequency error, and the output layer generates a control signal for adjusting the system gain and filter coefficient.

[0058] Input: Phase error and frequency error δ(t);

[0059] Hidden layer: nonlinear activation function (such as Sigmoid or ReLU) processes the input signal;

[0060] Output: control signal , used to update the system gain and filter coefficients;

[0061] The input-output relationship of the neural network is:

[0062]

[0063] Among them, W1 and W2 are network weights, b1 and b2 are bias terms, and f is the activation function.

[0064] The error weight optimization function includes: error sub-function and weight optimization sub-function. The error sub-function is defined as the sum of the squares of the phase error and the frequency error. The training goal of the network is to minimize the error function. The back propagation algorithm is used to update the weight of the network. The specific expression of the error weight optimization function is:

[0065]

[0066]

[0067]

[0068] Where, is the phase difference between the output signal and the reference signal at time t, is the frequency difference between the output signal and the reference signal at time t, η is the learning rate, and is the network weight at time t+1, and is the network weight at time t.

[0069] Furthermore, after the signal synchronization optimization model is operated and the synchronization signal is output, the following steps may be further included:

[0070] Step 104: Based on the synchronization signal and according to a preset parameter update function, the gain coefficient and the filter coefficient of the signal synchronization optimization model are updated.

[0071] More specifically, the parameter update function provided in this embodiment is:

[0072]

[0073] Where, is the gain coefficient at time t+1, is the filter coefficient at time t+1, is the gain coefficient at time t, is the filter coefficient at time t, η is the learning rate, is the phase difference between the output signal and the reference signal at time t, is the frequency difference between the output signal and the reference signal at time t, is the synchronization signal at time t.

[0074] By adaptively adjusting these parameters, phase error and frequency error can be reduced to ensure stable synchronization of the system.

[0075] Furthermore, to further improve the stability and accuracy of power system signal synchronization in this solution, this embodiment further introduces the influence of factors such as noise interference, hardware nonlinearity, and temperature changes on clock drift. The method provided by this embodiment may also include:

[0076] According to the error element data of power system signal synchronization, combined with the corresponding weighting coefficients of each error element, a comprehensive error relationship is determined, so as to determine the bias term b2 in the relationship function according to the comprehensive error relationship.

[0077] It should be noted that the influence of noise interference, hardware nonlinearity and temperature change on clock drift is different, including: the error caused by noise interference , Errors caused by hardware nonlinearity Errors caused by temperature changes , these error data can be obtained through fitting simulation.

[0078] Correspondingly, this embodiment sets different weighting coefficients for each factor, including: the weighting coefficient of noise interference error , the weighting coefficient of the system nonlinear error , weighted coefficient of temperature variation error .

[0079] Based on the above error data and weighting coefficients, the comprehensive error relationship is determined as follows:

[0080]

[0081] The output of the neural network can be adjusted according to these weighting coefficients:

[0082]

[0083] In order to further demonstrate the effect of the technical solution of the present application, this embodiment also provides an implementation example. Assume that a signal synchronization system is tested and the input signal frequency f in =100 MHzf, reference signal frequency f ref =100.001 MHzf, and there are factors such as noise, hardware nonlinearity and temperature changes. Assuming the initial phase error =0.05 rad, frequency error δ(t)=0.002 MHz. Initial gain KPLL=1, initial filter coefficient Learning rate η=0.1, noise weighting coefficient w noise =0.5, hardware nonlinear weighting coefficient w nonlinear =0.3, temperature change weighting coefficient w temp =0.2.

[0084] The effects of noise interference, hardware nonlinearity, and temperature changes are: =0.05 rad, =0.002 MHz, =0.01 rad.

[0085]

[0086] The neural network outputs the control signal: The control signal calculated by the neural network after training is:

[0087]

[0088] Update the gains and filter coefficients:

[0089]

[0090] By repeatedly updating the gain and filter coefficients, the system gradually reduces phase and frequency errors, eliminates the impact of clock drift, and ultimately achieves precise synchronization.

[0091] The above is a detailed description of an embodiment of a power system signal synchronization control method provided by the present application. The following is a detailed description of an embodiment of a power system signal synchronization control device provided by the present application.

[0092] See also Figure 3 , an embodiment of the present application provides a power system signal synchronization control device, comprising:

[0093] The signal acquisition unit 201 is used to acquire an output signal and a reference signal, wherein the output signal is a signal output by the host and the reference signal is a signal transmitted from the slave to the host;

[0094] A phase-frequency difference calculation unit 202 is configured to calculate a phase difference and a frequency difference between the output signal and the reference signal based on the phase data and the frequency data of the output signal and the reference signal, respectively;

[0095] The signal synchronization optimization unit 203 is used to input the phase difference and frequency difference into a preset signal synchronization optimization model to output a synchronization signal through the operation of the signal synchronization optimization model, wherein the signal synchronization optimization model includes: a relationship function for reflecting the input and output relationship of the signal synchronization optimization model and an error weight optimization function for optimizing the weight coefficient of the signal synchronization optimization model.

[0096] Furthermore, it also includes:

[0097] The feedback optimization unit 204 is configured to update the gain coefficient and the filter coefficient of the signal synchronization optimization model according to the synchronization signal and a preset parameter update function.

[0098] In addition, if Figure 4 As shown, the embodiment of the present application provides a power system signal synchronization control terminal, the implementation types of the terminal include but are not limited to: personal computers, industrial computers, servers and embedded intelligent devices, the main components of the terminal include: memory 33 and processor 31, the memory 33 and processor 31 can be connected via a communication bus 34;

[0099] The memory is used to store program codes, and the program codes are used to implement the power system signal synchronization control method provided by the above embodiment;

[0100] The processor is used to read and execute program code.

[0101] An embodiment of the present application provides a computer-readable storage medium, in which program code is stored. The program code is used to be read and executed by a processor to implement the power system signal synchronization control method provided in the above embodiment.

[0102] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the terminals, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0103] In the several embodiments provided in this application, it should be understood that the disclosed terminals, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0104] The terms "first," "second," "third," "fourth," and the like (if any) in the specification of the present application and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of the present application described herein, for example, can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such process, method, product, or apparatus.

[0105] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0106] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0107] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0108] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0109] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for synchronous control of power system signals, characterized in that: include: Acquire an output signal and a reference signal, wherein the output signal is a signal output by the host, and the reference signal is a signal transmitted from the slave to the host; Calculating a phase difference and a frequency difference between the output signal and the reference signal according to the phase data and the frequency data of the output signal and the reference signal; Inputting the phase difference and the frequency difference into a preset signal synchronization optimization model to output a synchronization signal through the operation of the signal synchronization optimization model, wherein the signal synchronization optimization model includes: a relationship function for reflecting the input and output relationship of the signal synchronization optimization model and an error weight optimization function for optimizing the weight coefficient of the signal synchronization optimization model, and the synchronization signal is a signal obtained by synchronizing the output signal with the reference signal; The relationship function is specifically: ； Where, is the phase difference between the output signal and the reference signal at time t, is the frequency difference between the output signal and the reference signal at time t, is the synchronization signal at time t, W1 and W2 are network weights, b1 and b2 are bias terms, and f is the activation function; The error weight optimization function is specifically: ； ； ； Where, is the phase difference between the output signal and the reference signal at time t, is the frequency difference between the output signal and the reference signal at time t, η is the learning rate, and is the network weight at time t+1, and is the network weight at time t.

2. The power system signal synchronization control method according to claim 1, characterized in that: Also includes: According to the error element data of the power system signal synchronization, combined with the weighting coefficients corresponding to the various error elements, a comprehensive error relationship formula is determined, so as to determine the bias term b2 in the relationship function according to the comprehensive error relationship formula.

3. The power system signal synchronization control method according to claim 1, characterized in that: Also includes: According to the synchronization signal, the gain coefficient and the filter coefficient of the signal synchronization optimization model are updated according to a preset parameter update function.

4. The power system signal synchronization control method according to claim 3, characterized in that: The parameter update function is specifically: ； Where, is the gain coefficient at time t+1, is the filter coefficient at time t+1, is the gain coefficient at time t, is the filter coefficient at time t, η is the learning rate, is the phase difference between the output signal and the reference signal at time t, is the frequency difference between the output signal and the reference signal at time t, is the synchronization signal at time t.

5. A power system signal synchronization control device, characterized in that: include: a signal acquisition unit, configured to acquire an output signal and a reference signal, wherein the output signal is a signal output by the host, and the reference signal is a signal transmitted from the slave to the host; a phase-frequency difference calculation unit, configured to calculate a phase difference and a frequency difference between the output signal and the reference signal, respectively, based on the phase data and the frequency data of the output signal and the reference signal; a signal synchronization optimization unit, configured to input the phase difference and the frequency difference into a preset signal synchronization optimization model, so as to output a synchronization signal through operation of the signal synchronization optimization model, wherein the signal synchronization optimization model includes: a relationship function for reflecting the input-output relationship of the signal synchronization optimization model and an error weight optimization function for optimizing the weight coefficient of the signal synchronization optimization model, and the synchronization signal is a signal obtained by synchronizing the output signal with the reference signal; The relationship function is specifically: ； Where, is the phase difference between the output signal and the reference signal at time t, is the frequency difference between the output signal and the reference signal at time t, is the synchronization signal at time t, W1 and W2 are network weights, b1 and b2 are bias terms, and f is the activation function; The error weight optimization function is specifically: ； ； ； Where, is the phase difference between the output signal and the reference signal at time t, is the frequency difference between the output signal and the reference signal at time t, η is the learning rate, and is the network weight at time t+1, and is the network weight at time t.

6. The power system signal synchronization control device according to claim 5, characterized in that: Also includes: A feedback optimization unit is used to update the gain coefficient and filter coefficient of the signal synchronization optimization model according to the synchronization signal and a preset parameter update function.

7. A power system signal synchronization control terminal, characterized in that: include: memory and processor; The memory is used to store program codes, and the program codes are used to implement the power system signal synchronization control method according to any one of claims 1 to 4; The processor is configured to read and execute the program code.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores program code, and the program code is used to be read and executed by a processor to implement the power system signal synchronization control method according to any one of claims 1 to 4.

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