Power system signal synchronization control method and device, terminal and medium

Abstract

The invention discloses a power system signal synchronization control method and device, a terminal and a medium, and relates to the technical field of power system control. According to the technical scheme provided by the invention, the phase difference and the frequency difference of an output signal and a reference signal are respectively calculated according to phase data and frequency data of the output signal and the reference signal; and inputting the phase difference and the frequency difference into a signal synchronization optimization model based on an adaptive neural network algorithm so as to output a synchronization signal through operation of the signal synchronization optimization model. The signal synchronization optimization model constructed by using the adaptive neural network algorithm can continuously update parameters, perform self-training and flexibly adjust according to the characteristics of input data so as to adapt to drifts of different frequencies and phases, and the signal synchronization stability and precision of the power system are improved.

Description

Technical Field

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

[0002] As the power system gradually operates, there is a need for signal synchronization in many occasions. For example, in the energy storage system, whether the control angle is synchronized with the reference angle determines whether the inverter system can smoothly switch phases and whether the output AC signal phase and frequency can be consistent with the power grid; for example, when the circuit core is connected, it is also necessary to determine whether the phase and frequency of the connected circuit are synchronized, otherwise it will damage the stability of the power grid; for example, when testing and analyzing the full current and resistive current phase of the lightning arrester, signal synchronization technology may also be used for measurement; for example, in partial discharge measurement, since the signal acquisition and synchronization signal are not generated in the same place, signal remote synchronization technology will also be used.

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

[0005] In order to solve the above technical problems, the first aspect of the present application provides a method for synchronous control of power system signals, 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 respectively;

[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] In the formula, 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] 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 to determine the bias term b2 in the relationship function according to the comprehensive error relationship, and the error elements include: noise error, hardware nonlinear error and temperature change error.

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

[0015]

[0016]

[0017]

[0018] In the formula, 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 updating function is specifically:

[0022]

[0023] In the formula, 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, 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;

[0026] A phase-frequency difference calculation unit, used to calculate the phase difference and frequency difference between the output signal and the reference signal according to the phase data and frequency data of the output signal and the reference signal respectively;

[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, including: a memory and a processor;

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

[0032] The processor is used for reading and executing the program code.

[0033] The fourth aspect of the present application provides a computer-readable storage medium, in which a 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 by the present application calculates the phase difference and frequency difference between the output signal and the reference signal according to the phase data and frequency data of the output signal and the reference signal, respectively, and inputs the phase difference and frequency difference into the signal synchronization optimization model based on the adaptive neural network algorithm, so as to output the synchronization signal through the operation of the signal synchronization optimization model. The signal synchronization optimization model constructed by using the adaptive neural network algorithm can continuously update parameters according to the characteristics of the input data, perform self-training, and flexibly adjust to adapt to the drift of different frequencies and phases, 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 drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 creative labor.

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

[0038] Figure 2 A schematic flow chart of an embodiment of a method for synchronous control of power system signals provided in the present application.

[0039] Figure 3 A schematic diagram of the structure of a power system signal synchronization control device provided in this application.

[0040] Figure 4 A schematic diagram of a flow chart of an embodiment of a power system signal synchronization control terminal provided in the present application. DETAILED DESCRIPTION

[0041] The embodiments of the present application provide 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 of an existing electric power system.

[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 them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0043] See also Figure 1 and Figure 2 , the present application provides a method for synchronous control of power system signals, comprising:

[0044] Step 101, obtaining an output signal and a reference signal;

[0045] The output signal is a signal output by the host, and the reference signal is a 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 according to 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, so as 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 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.

[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 host. 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 the circuit phase core; 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 the LPF (Low Pass Filter) to filter out the high-frequency noise components and then be converted into a digital signal through the ADC (analog to digital converter). The reference phase and frequency in the slave are sent to the host through wireless communication, and the host obtains the phase and frequency information therein through the wireless signal; at the same time, the host obtains the phase frequency of the signal from the signal output system that needs to be synchronized. Then the output system is synchronized with the reference signal to obtain the signal after the output signal and the reference signal are synchronized, that is, the synchronization signal, in which the 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, the output signal generated by the signal output system of the host side and the reference signal transmitted from the reference signal of the slave to the host through the wireless module are respectively obtained, and then the phase characteristics and frequency characteristics of the obtained output signal and reference signal are extracted, and then, according to the phase data and frequency data of the output signal and the reference signal, the phase difference and frequency difference of the output signal and the reference signal are respectively calculated;

[0051] Among them, the calculation formulas of 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, so as to output a synchronization signal through the operation 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 a phase error and a frequency error, and the output layer generates a control signal for adjusting the gain and filter coefficient of the system.

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

[0059] Hidden layer: non-linear 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] In the formula, 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 method may further include:

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

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

[0072]

[0073] In the formula, 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, in order to further improve the signal synchronization stability and accuracy of the power system of this solution, this embodiment further introduces the influence of factors such as noise interference, hardware nonlinearity and temperature change 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 various error elements, 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: 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 , weighting 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 then be adjusted based on these weighting coefficients:

[0082]

[0083] 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 noise, hardware nonlinearity, and temperature variations. 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 the 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] A 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, used to calculate the phase difference and frequency difference between the output signal and the reference signal according to the phase data and 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 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.

[0096] Furthermore, it also includes:

[0097] The feedback optimization unit 204 is used to update the gain coefficient and the filter coefficient of the signal synchronization optimization model according to the synchronization signal and the 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: a memory 33 and a processor 31, the memory 33 and the 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 in 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 a 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 can 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 the present 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 only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, 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 interfaces, devices or units, which can be electrical, mechanical or other forms.

[0104] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described herein can, for example, be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0105] It should be understood that in the present 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 objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single 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 separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0107] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0108] If the integrated unit is implemented in the form of 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, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[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 aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned 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 respectively; 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.

2. The method for synchronous control of power system signals according to claim 1, characterized in that: The relationship function is specifically: In the formula, 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.

3. The method for synchronous control of power system signals according to claim 2, characterized in that: Also includes: According to the error element data of the power system signal synchronization, combined with the weighting coefficients corresponding to 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.

4. The method for synchronous control of power system signals according to claim 1, characterized in that: The error weight optimization function is specifically: In the formula, 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.

5. The method for synchronous control of power system signals 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.

6. The method for synchronous control of power system signals according to claim 5, characterized in that: The parameter update function is specifically: In the formula, 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.

7. A power system signal synchronization control device, characterized in that: include: A signal acquisition unit, 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; A phase-frequency difference calculation unit, used to calculate the phase difference and frequency difference between the output signal and the reference signal according to the phase data and frequency data of the output signal and the reference signal respectively; 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.

8. The power system signal synchronization control device according to claim 7, 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.

9. 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 6; The processor is used for reading and executing the program code.

10. 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 6.

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