Power grid topology identification method and device
The identification of feature codes in the power grid topology through digital detection algorithms and voting methods has solved the problem of inaccurate identification results in the prior art, and achieved high accuracy and low computational volume of grid topology recognition.
Patent Information
- Application Number
- CN202411344769.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-25
- Publication Date
- 2025-02-14
AI Technical Summary
The prior art has interference problems in identifying power grid topology, resulting in inaccurate identification results.
The signal to be measured at the characteristic frequency is detected by a digital detection algorithm, the signal strength and background noise of the signal to be identified are calculated, and the characteristic code is identified by voting method to distinguish the characteristic current signal and the interference signal.
It improves the accuracy of grid topology recognition, reduces the amount of calculation, avoids spectrum leakage problems, and realizes real-time detection.
Smart Images
Figure CN119441798A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of power distribution of electric power systems, and in particular to a method and device for identifying power grid topology. Background Art
[0002] With the rapid development of power grid technology, power companies have higher and higher requirements for power grid technology. Accurate power grid topology is important information that needs to be mastered for power grid operation and management, but the huge number of users has brought great challenges to the management of power grid topology. At present, the topology relationship is mainly identified through characteristic current signals; specifically, the master station sends a characteristic current signal to the user terminal. After receiving the instruction, the user terminal controls the load on and off to generate a characteristic current signal on the power line, and identifies the characteristic code on the characteristic current signal, and then reports the identified characteristic code and identification time to the master station. The master station sorts out the topology relationship in this way.
[0003] However, in actual implementation, in order to prevent the characteristic current signal from affecting the normal metering function of the user, the characteristic current signal is generally set to be very small, and it accounts for a small proportion in the power supply line of hundreds or thousands of amperes. At the same time, various electrical appliances are connected to the power grid, and the types of electricity consumption are complex and changeable. The lines contain rich spectrum signals, which will cause great interference to the identification of characteristic current signals. Generally speaking, there are two major problems:
[0004] First, compared with the industrial frequency current signal and the noise signals generated by various electrical equipment, the characteristic current signal is a weak signal, usually only tens of microvolts to a few microvolts, or even lower, during sampling, which sometimes makes it impossible to detect whether the characteristic current signal exists; second, the noise on the power supply line will change with the increase or decrease of electrical equipment, and the intensity of the noise signal and the industrial frequency signal in different power consumption periods is not the same, which makes it difficult to distinguish whether the detected signal is a characteristic current signal or a noise signal.
[0005] In response to the above problems, in topology recognition technology, the fast Fourier transform (FFT) algorithm is generally used to extract the characteristic code in the power grid. However, this method still has some problems. When the sampling rate remains unchanged, a sufficient number of FFT points are required to participate in the calculation so that the spectrum resolution of the FFT algorithm can meet the requirements, but it will cause too much calculation and lead to delayed response. In addition, the calculation result of the FFT algorithm is the signal strength of a frequency interval, which will also include the signal of non-characteristic current frequency. There are also problems such as spectrum leakage, which will interfere with the recognition of the characteristic code and lead to inaccurate recognition results.
[0006] In the process of implementing the present invention, the inventors found that there are at least the following problems in the prior art:
[0007] The current method of identifying power grid topology will cause a lot of interference in the process of identifying the feature code, resulting in inaccurate identification results. Summary of the invention
[0008] The purpose of the present invention is to provide a method and device for identifying power grid topology, so as to solve the technical problem that there are many interferences in the process of identifying feature codes in the prior art, resulting in inaccurate identification results. The preferred technical solutions among the many technical solutions provided by the present invention can produce many technical effects as described below.
[0009] To achieve the above object, the present invention provides the following technical solutions:
[0010] The present invention provides a method for identifying power grid topology, comprising the following steps: continuously acquiring a measured signal, detecting the measured signal at a characteristic frequency through a digital detection algorithm, and obtaining a signal strength of a signal to be identified; wherein the signal to be identified is the measured signal at the characteristic frequency; calculating the background noise of the signal to be identified within a first set time; identifying a characteristic code of the signal to be identified through a voting method according to the signal strength and background noise of the signal to be identified; and judging whether a characteristic current signal exists in the measured signal according to the characteristic code of the signal to be identified, so as to identify the relationship of the power grid topology.
[0011] Optionally, the method of identifying the characteristic code of the signal to be identified by a voting method based on the signal strength and background noise of the signal to be identified includes: comparing the signal strength of each signal to be identified detected at a second set time with N times the background noise; wherein, there are a signal strengths of the signals to be identified at the second set time, and the signal strength of each signal to be identified corresponds to 1 data block; if the signal strength of the signal to be identified is greater than N times the background noise, the data block is recorded as 1, otherwise, the data block is recorded as 0, until a data sequence consisting of a 0s and 1s is obtained; the data sequence is divided into 16-bit code elements, 1-bit code element includes b data blocks, and the binary value of the 16-bit code element is output according to the b data blocks of each code element, so as to obtain the characteristic code of the signal to be identified; wherein, a=16*b; the 16-bit code element is the characteristic code of the signal to be identified.
[0012] Optionally, the voting and outputting of the 16-bit codewords according to b data blocks includes: if among 1-bit codewords, more than b / 2 of the data blocks are 1, voting the codeword as 1; otherwise, voting as 0; and voting each bit of the codeword in turn to obtain a characteristic sequence of the characteristic code of the signal to be identified.
[0013] Optionally, judging whether a characteristic current signal exists in the measured signal according to a characteristic code of the signal to be identified includes: when it is identified that a characteristic sequence of the characteristic code of the signal to be identified represents 0xAAE9, confirming that a characteristic current signal exists in the measured signal.
[0014] Optionally, after determining whether a characteristic current signal exists in the measured signal according to the characteristic code of the signal to be identified, the method for identifying the power grid topology further includes: if it is identified that no characteristic current signal exists in the measured signal, using a data blocks as a window, sliding to the next data block, and forming a new data sequence for identification.
[0015] Optionally, calculating the background noise of the signal to be identified within the first set time includes: recording the signal strength of all the signals to be identified within the first set time; after removing the abnormal maximum and minimum values of the signal strengths of all the signals to be identified, calculating the average value of the signal strengths of all the signals to be identified to obtain the background noise.
[0016] Optionally, the method of detecting the measured signal at the characteristic frequency by a digital detection algorithm to obtain the signal strength of the signal to be identified includes: performing digital detection on the measured signal at the characteristic frequency to obtain a first DC component and a second DC component of the measured signal; and calculating the signal strength of the signal to be identified based on the first DC component and the second DC component.
[0017] Optionally, the signal to be identified f(t) is assumed to be: Wherein, A is the signal strength of the signal to be identified; f is the frequency of the signal to be identified; t is the time for sampling the signal to be identified; is the phase of the signal to be identified; the measured signal f(t) is processed by sinusoidal correlation to obtain formula (1): The measured signal f(t) is subjected to cosine correlation processing to obtain equation (2): The first DC component P and the second DC component Q are obtained by low-pass filtering equation (1) and equation (2) respectively: The signal strength A of the signal to be identified is calculated based on the first DC component P and the second DC component Q:
[0018] Optionally, the continuously acquiring the measured signal includes: performing recursive bandpass filtering on the power grid signal sampled by the analog-to-digital converter to obtain the measured signal.
[0019] A device for identifying power grid topology, comprising:
[0020] one or more processors;
[0021] A memory for storing one or more computer programs, wherein one or more processors are used to execute the one or more computer programs stored in the memory, so that the one or more processors execute any one of the above-mentioned methods for identifying a power grid topology.
[0022] Implementing one of the above technical solutions of the present invention has the following advantages or beneficial effects:
[0023] The present invention first detects the measured signal through a digital detection algorithm, and can accurately obtain the signal to be identified at the characteristic frequency. The calculation amount is small, real-time detection can be achieved, and spectrum leakage problems can be avoided; then the characteristic code of the signal to be identified is identified through a voting method, and other interference signals are distinguished from the characteristic current signal. It can effectively identify whether there is a characteristic current signal in the signal to be identified, and further improve the accuracy of identification, so as to ensure that an accurate power grid topology relationship is obtained through the characteristic current signal. BRIEF DESCRIPTION OF THE DRAWINGS
[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. It is obvious that the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:
[0025] Figure 1 is a flow chart of a method for identifying a power grid topology according to a first embodiment of the present invention;
[0026] Figure 2 is a flowchart of step S1 of a method for identifying a power grid topology according to a first embodiment of the present invention;
[0027] Figure 3 is a flowchart of step S2 of a method for identifying a power grid topology according to a first embodiment of the present invention;
[0028] Figure 4 This is a flowchart of step S2 of a method for identifying a power grid topology according to an embodiment of the present invention. DETAILED DESCRIPTION
[0029] In order to make the purpose, technical solutions and advantages of the present invention clearer, the various exemplary embodiments to be described below will refer to the corresponding drawings, which constitute a part of the exemplary embodiments, wherein various exemplary embodiments that may be used to implement the present invention are described. Unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation methods described in the following exemplary embodiments do not represent all implementation methods consistent with the present disclosure. It should be understood that they are only examples of processes, methods, devices, etc. that are consistent with some aspects of the present disclosure as detailed in the attached claims, and other embodiments may also be used, or the embodiments listed herein may be modified in structure and function without departing from the scope and essence of the present invention.
[0030] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", etc. indicate the orientation or positional relationship based on the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the elements referred to must have a specific orientation, be constructed and operated in a specific orientation. The terms "first", "second", etc. are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. The term "multiple" means two or more. The terms "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, an integral connection, a mechanical connection, an electrical connection, a communication connection, a direct connection, an indirect connection through an intermediate medium, and can be the internal connection of two elements or the interaction relationship between two elements. The term "and / or" includes any and all combinations of one or more related listed items. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances.
[0031] In order to illustrate the technical solution of the present invention, a specific embodiment is used below for description, and only the parts related to the embodiment of the present invention are shown.
[0032] Embodiment 1:
[0033] like Figure 1 As shown, the present invention provides a method for identifying a power grid topology, comprising the following steps:
[0034] S1. Continuously acquire the measured signal, detect the measured signal at the characteristic frequency through the digital detection algorithm, and obtain the signal strength of the signal to be identified; wherein, the signal to be identified is the measured signal at the characteristic frequency; S2. Calculate the background noise of the signal to be identified within the first set time; S3. According to the signal strength and background noise of the signal to be identified, identify the characteristic code of the signal to be identified by the voting method; wherein, the characteristic code of the signal to be identified includes 16-bit code elements; S4. According to the characteristic code of the signal to be identified, determine whether there is a characteristic current signal in the measured signal to identify the relationship of the power grid topology.
[0035] The grid topology recognition method provided in this embodiment is applied to the field of power distribution of electric power systems. The measured signal is first detected by a digital detection algorithm, and the signal to be identified at the characteristic frequency can be accurately obtained. The calculation amount is small, real-time detection can be achieved, and spectrum leakage problems can be avoided. Then, the characteristic code of the signal to be identified is identified by a voting method, and other interference signals are distinguished from the characteristic current signal. It can effectively identify whether there is a characteristic current signal in the signal to be identified, and further improve the accuracy of recognition, so as to ensure that an accurate grid topology relationship is obtained through the characteristic current signal.
[0036] Next, combine Figure 1-Figure 4 The specific implementation steps of the method for identifying the power grid topology provided in this embodiment are described in detail:
[0037] First, execute step S1, continuously acquire the measured signal, detect the measured signal at the characteristic frequency through the digital detection algorithm, and obtain the signal strength of the signal to be identified; wherein the signal to be identified is the measured signal at the characteristic frequency; the frequency of the characteristic current signal is generally 783hz or 883.33Hz, and the measured signal is detected at the characteristic frequency, that is, the signal strength of the measured signal at 783hz or 883.33Hz is detected to determine whether there is a characteristic current signal at this frequency.
[0038] Further, the measured signal is continuously acquired, including: recursively bandpass filtering the power grid signal sampled by the analog-to-digital converter to obtain the measured signal. Filtering the sampled power grid signal before detection can remove the AC power frequency signal and other noise signals in the power grid signal, thereby filtering out part of the interference in the measured signal; in order to save the computing resources of the MCU, this embodiment preferably uses an IIR digital filter for recursive bandpass filtering. In order to enhance the intensity of high-frequency signals (signals at a characteristic frequency of 883.33 Hz) and reduce the interference of low-frequency signals (50 Hz power frequency signals), the sampling resistor used in the analog-to-digital converter can be replaced with an inductor. The low-pass frequency resistance of the inductor is high, which can make the sampling value of the high-frequency signal larger.
[0039] Specifically, Figure 2As shown, the signal to be detected at the characteristic frequency is detected by a digital detection algorithm to obtain the signal strength of the signal to be identified, including: S11, performing digital detection on the signal to be detected at the characteristic frequency to obtain the first DC component and the second DC component of the signal to be identified; S12, calculating the signal strength of the signal to be identified based on the first DC component and the second DC component. Through digital detection, the signal strength can be accurately calculated at a specific frequency to obtain the signal strength of the signal to be identified with higher credibility.
[0040] Furthermore, the digital detection method is specifically as follows: assuming that the signal to be identified f(t) is: Where A is the signal strength of the signal to be identified; f is the frequency of the signal to be identified; t is the time of sampling the signal to be identified; is the phase of the signal to be identified; the only unknown quantities are signal strength A and phase That is the desired quantity; the measured signal f(t) is processed by sinusoidal correlation to obtain formula (1): That is, multiply both sides of formula (1) by a sinusoidal signal sin(2*π*f*t); perform cosine correlation processing on the measured signal f(t) to obtain formula (2): That is, multiply both sides of formula (2) by a cosine signal cos(2*π*f*t); perform low-pass filtering on formula (1) and formula (2) respectively to obtain the first DC component P and the second DC component Q as follows: The determined values of the first DC component P and the second DC component Q can be obtained by a low-pass filter; in actual applications, there will be many other signals of different frequencies that are unrelated to the characteristic current signal in the signal to be identified f(t). After sine and cosine correlation processing, the two components are low-pass filtered to filter out such signals that are unrelated to the characteristic current signal. The signal strength A of the signal to be identified is calculated based on the first DC component P and the second DC component Q: The phase of the signal to be identified can also be calculated based on the first DC component P and the second DC component Q. for: Thereby, the accurate signal strength of the signal to be identified can be obtained.
[0041] Then, step S2 is executed to calculate the background noise of the signal to be identified within the first set time, so as to vote with the signal strength of the signal to be identified and identify the code of the signal to be identified. Figure 3 As shown, it includes: S21, recording the signal strength of all signals to be identified within the first set time; S22, after removing the abnormal maximum and minimum values of the signal strength of all signals to be identified, calculating the average value of the signal strength of all signals to be identified to obtain background noise.
[0042] The characteristic code of the characteristic current signal is a 16-bit code, the code is 0xAAE9, and the duration of one-bit code is 600ms. Therefore, the data sampled every 100ms is taken as a data block during sampling, that is, in step S1, the signal strength data of the signal to be identified is detected every 100ms; for example, when calculating the background noise of the signal to be identified, the first set time is set to one minute, and a signal strength calculation result can be obtained every 100ms, and 600 calculation results can be obtained in one minute; remove the abnormal maximum and minimum values of these 600 calculation results, and calculate the average value of the remaining values. The calculated average value is the background noise. Whenever the window slides once, the background noise is calculated once to continuously output the background noise.
[0043] Next, step S3 is executed to identify the characteristic code of the signal to be identified by the voting method according to the signal strength and background noise of the signal to be identified; wherein the characteristic code of the signal to be identified includes 16-bit code elements. Since step S1 only solves the problem of signal strength detection at the characteristic frequency, but still cannot distinguish how strong the signal strength can be identified as code 1, the spectrum of the power grid signal is rich and changeable, even if there is no characteristic current signal in the power grid, the signal strength at 883.33Hz may be very strong, and it is difficult to distinguish how strong the signal strength is to be the characteristic current signal. Therefore, this embodiment uses the voting method for identification.
[0044] Specifically, Figure 4 As shown, it includes: S31, comparing the signal strength of each signal to be identified detected at the second set time with N times the background noise; wherein, there are a signal strengths of signals to be identified at the second set time, and the signal strength of each signal to be identified corresponds to 1 data block; the length of the characteristic code of the characteristic current signal is 16 bits, one bit of coding time is 600ms, and one bit of coding includes 6 data blocks. Therefore, this embodiment sets the second set time to 9.6s, and 96 data blocks can be sampled, that is, a=96, which is the length of the characteristic code.
[0045] S32, if the signal strength of the signal to be identified is greater than N times the background noise, the data block corresponding to the signal strength of the signal to be identified is recorded as 1, otherwise, the data block corresponding to the signal strength of the signal to be identified is recorded as 0, until a data sequence consisting of a 0s and 1s is obtained; if the signal strength of the signal to be identified is N times greater than the background noise, it can be considered that the signal strength of this point is stronger at the characteristic frequency, and the data block can be identified as 1. Preferably, in this embodiment, N is set to 2, which can ensure accurate identification of the signal to be identified; the larger the multiple is set, the higher the identification difficulty, but the higher the identification accuracy, which can be set according to actual usage.
[0046] S33, divide the data sequence into 16-bit code elements, 1-bit code element includes b data blocks, and output the binary value of the 16-bit code element according to the b data blocks of each code element, and obtain the characteristic code of the signal to be identified; wherein, a=16*b; the 16-bit code element is the characteristic code of the signal to be identified. After the calculation in step S32, a data sequence of length 96 composed of 0 and 1 can be obtained. Since the length of the characteristic code is 16, b=6. Finally, each code element obtains the final recognition result according to these 6 data blocks.
[0047] Furthermore, voting is performed based on b data blocks to output 16-bit codewords, including: if more than b / 2 data blocks are 1 in a 1-bit codeword, the codeword is voted as 1; otherwise, the codeword is voted as 0; each codeword is voted in turn to obtain a characteristic sequence of the characteristic code of the signal to be identified. For example, b=6, if more than 3 signal strengths are greater than N times the background noise, that is, 4 or more data blocks are 1, the codeword is voted as 1. This voting method can greatly improve the accuracy of identifying characteristic codes.
[0048] Further, judging whether there is a characteristic current signal in the measured signal according to the characteristic code of the signal to be identified includes: when the characteristic sequence of the characteristic code of the signal to be identified indicates 0xAAE9, it is confirmed that there is a characteristic current signal in the measured signal; the characteristic sequence is composed of 16-bit binary code elements, and if the code can be decoded as 0xAAE9, it means that there is a characteristic current in the current to be identified. If it is identified that there is no characteristic current signal in the measured signal, a data block is used as a window, and slides to the next data block to form a new data sequence for identification.
[0049] Finally, step S4 is performed to determine whether there is a characteristic current signal in the measured signal according to the characteristic code of the signal to be identified, so as to identify the relationship of the power grid topology. When the characteristic code is identified in the measured signal, the characteristic code is obtained and decoded to obtain the power grid topology relationship information, so as to accurately and effectively identify the relationship of the power grid topology.
[0050] The grid signal with characteristic current signal is switched to the power frequency current of 2000A, 1600A and 1200A and the power grid with various interferences (such as interference generated by high-power frequency conversion motors in the power grid). The recognition results are shown in Table 1. The power frequency current is reduced by 400 times through a 2000:5 current transformer and output to the ammeter. Regardless of the signal strength at 783hz or 883hz, regardless of the secondary side current of 3A, 4A or 5A, when the signal strength is large, the bit of the code element is recognized as 1, and when the signal strength is small, the bit of the code element is recognized as 0, and the success rate of switching recognition is 100%.
[0051]
[0052] Table 1 Feature code recognition results
[0053] Embodiment 2:
[0054] The present invention also provides an embodiment of a device for identifying power grid topology, comprising one or more processors and a memory; wherein the memory is used to store one or more computer programs, and the one or more processors are used to execute one or more computer programs stored in the memory, so that the processor executes the features / steps of an embodiment of a method for identifying power grid topology described in Embodiment 1.
[0055] The above description is only the preferred embodiment of the present invention. It is known to those skilled in the art that various changes or equivalent substitutions may be made to these features and embodiments without departing from the spirit and scope of the present invention. In addition, under the teachings of the present invention, these features and embodiments may be modified to adapt to specific circumstances and materials without departing from the spirit and scope of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed herein, and all embodiments falling within the scope of the claims of this application belong to the protection scope of the present invention.
Claims
1. A method for identifying power grid topology, characterized in that: The following steps are involved: Continuously acquiring the measured signal, detecting the measured signal at the characteristic frequency through a digital detection algorithm, and obtaining the signal strength of the signal to be identified; wherein the signal to be identified is the measured signal at the characteristic frequency; Calculate the background noise of the signal to be identified within a first set time; Identify the characteristic code of the signal to be identified by a voting method according to the signal strength and background noise of the signal to be identified; It is determined whether a characteristic current signal exists in the measured signal according to the characteristic code of the signal to be identified, so as to identify the relationship of the power grid topology.
2. A method for identifying power grid topology according to claim 1, characterized in that: The step of identifying the characteristic code of the signal to be identified by a voting method according to the signal strength and background noise of the signal to be identified includes: Compare the signal strength of each of the to-be-identified signals detected at the second set time with N times the background noise; wherein there are a signal strengths of the to-be-identified signals at the second set time, and the signal strength of each of the to-be-identified signals corresponds to 1 data block; If the signal strength of the signal to be identified is greater than N times of the background noise, the data block is recorded as 1, otherwise, the data block is recorded as 0, until a data sequence consisting of a 0s and 1s is obtained; The data sequence is divided into 16-bit code elements, 1-bit code element includes b data blocks, and the binary value of the 16-bit code element is output according to the b data blocks of each code element to obtain the characteristic code of the signal to be identified; wherein, a=16*b; the 16-bit code element is the characteristic code of the signal to be identified.
3. A method for identifying power grid topology according to claim 2, characterized in that: The voting and outputting of the 16-bit codewords according to the b data blocks includes: if among the 1-bit codewords, more than b / 2 of the data blocks are 1, then the codeword is voted as 1; otherwise, it is voted as 0; and each bit of the codeword is voted in turn to obtain a characteristic sequence of the characteristic code of the signal to be identified.
4. A method for identifying power grid topology according to claim 3, characterized in that: The determining whether there is a characteristic current signal in the measured signal according to the characteristic code of the signal to be identified includes: when it is identified that the characteristic sequence of the characteristic code of the signal to be identified represents 0xAAE9, confirming that there is a characteristic current signal in the measured signal.
5. A method for identifying power grid topology according to claim 4, characterized in that: After determining whether a characteristic current signal exists in the measured signal according to the characteristic code of the signal to be identified, the method for identifying the power grid topology further includes: If it is identified that there is no characteristic current signal in the measured signal, a data blocks are used as a window and slid to the next data block to form a new data sequence for identification.
6. A method for identifying power grid topology according to claim 1, characterized in that: The calculating the background noise of the signal to be identified within the first set time includes: Record the signal strength of all the signals to be identified within a first set time; After removing the abnormal maximum and minimum values in the signal strengths of all the signals to be identified, the average value of the signal strengths of all the signals to be identified is calculated to obtain the background noise.
7. A method for identifying power grid topology according to claim 1, characterized in that: The step of detecting the measured signal at the characteristic frequency by a digital detection algorithm to obtain the signal strength of the signal to be identified includes: Performing digital detection on the measured signal at a characteristic frequency to obtain a first DC component and a second DC component of the measured signal; The signal strength of the signal to be identified is calculated according to the first DC component and the second DC component.
8. A method for identifying power grid topology according to claim 7, characterized in that: Assume that the signal to be identified f(t) is: Wherein, A is the signal strength of the signal to be identified; f is the frequency of the signal to be identified; t is the time for sampling the signal to be identified; is the phase of the signal to be identified; The measured signal f(t) is subjected to sinusoidal correlation processing to obtain formula (1): The measured signal f(t) is subjected to cosine correlation processing to obtain equation (2): The first DC component P and the second DC component Q are obtained by low-pass filtering equation (1) and equation (2) respectively: The signal strength A of the signal to be identified is calculated based on the first DC component P and the second DC component Q:
9. A method for identifying power grid topology according to claim 1, characterized in that: The continuously acquiring the measured signal includes: performing recursive bandpass filtering on the power grid signal sampled by the analog-to-digital converter to obtain the measured signal.
10. A device for identifying power grid topology, characterized in that: include: one or more processors; A memory for storing one or more computer programs, and one or more processors for executing the one or more computer programs stored in the memory, so that one or more processors execute a method for identifying a power grid topology as described in any one of claims 1 to 9.