Methods and Systems for Improving Circuit Accuracy Based on Intelligent Converged Terminals

Abstract

This application relates to the field of electrical variable measurement, specifically to a method and system for improving circuit accuracy based on an intelligent fusion terminal. The method includes: obtaining a current error-temperature fitting polynomial and a frequency domain amplitude error-temperature fitting polynomial based on historical electricity consumption data, measured current sequence, temperature sequence, and actual current sequence; correcting the measured current of the current electricity consumption process based on the fitting polynomials to obtain a corrected current sequence; calculating an adaptive calculation frequency for the effective current value by sliding division of the corrected current sequence; obtaining an effective corrected current sequence and an effective measured current sequence based on the adaptive calculation frequency; obtaining a weighting factor based on the effective corrected current sequence and the effective measured current sequence; and obtaining the effective current value based on the weighting factor and the effective current sequence. This application has the effect of accurately calculating the effective current value and improving the measurement accuracy of user branch circuits by the intelligent fusion terminal.

Description

Technical Field

[0001] This application relates to the field of electrical variable measurement, and in particular to a method and system for improving circuit accuracy based on an intelligent fusion terminal. Background Technology

[0002] As the core of the low-voltage distribution Internet of Things (IoT), the intelligent fusion terminal is the most numerous edge device in the power IoT technology architecture. It can be networked locally with low-voltage smart devices, smart meters, etc. to complete the intelligent transformation of the distribution area. The traditional intelligent fusion terminal error calibration method requires disassembling the device and connecting it to the distribution and procurement base plate using a serial cable. The calibration parameters are written into the data storage EEPROM through the State Grid standard 645 protocol frame.

[0003] Existing technologies perform single-time-domain correction of current based on temperature, ignoring the different thermal drift errors caused by temperature affecting currents of different frequency components in the circuit, resulting in large errors in the results. In addition, existing technologies calculate the correction current based on a fixed effective value sequence length, which is prone to spectral leakage, leading to low accuracy of the effective value of the circuit current. Summary of the Invention

[0004] In order to obtain the effective value of the circuit current more accurately and improve the measurement accuracy of the user branch circuit by the intelligent fusion terminal, this application provides a method and system for improving circuit accuracy based on the intelligent fusion terminal.

[0005] Firstly, this application provides a method for improving circuit accuracy based on an intelligent fusion terminal, employing the following technical solution:

[0006] Calculate the effective value of the current; input the effective value of the current at each corresponding time point to the intelligent fusion terminal to obtain the power of the user branch circuit at the current time, so as to improve the accuracy of the intelligent fusion terminal in measuring the user branch circuit.

[0007] The method for calculating the effective value of the current is as follows:

[0008] Based on historical electricity consumption data, a current error-temperature fitting polynomial is constructed as the first polynomial for time-domain dimension correction; based on historical electricity consumption data, a fitting error is constructed, and then the frequency domain amplitude error-temperature fitting polynomial for each frequency is obtained as the second polynomial for frequency-domain dimension correction.

[0009] Obtain the time-domain corrected current sequence and time-domain corrected confidence level based on the first polynomial and the current power consumption data; obtain the frequency-domain corrected current sequence and frequency-domain corrected confidence level based on the second polynomial and the current power consumption data;

[0010] The corrected current sequence is obtained based on the time-domain corrected current sequence, the time-domain corrected confidence level, the frequency-domain corrected current sequence, and the frequency-domain corrected confidence level.

[0011] The adaptive calculation frequency for calculating the effective value of the current is calculated by sliding division of the correction current sequence. The current effective correction current sequence is obtained based on the adaptive calculation frequency and the correction current sequence of the target phase. Similarly, the current effective measurement current sequence is obtained.

[0012] Calculate the product of the average values ​​of the frequency domain amplitude difference and the time domain amplitude difference between the IMF components of the effective corrected current sequence and the effective measured current sequence. Obtain a weighting factor based on the product of the average values ​​and the average of all the products of the average values. Obtain the effective current value based on the weighting factor and the average current amplitude of the IMF components of the effective current sequence.

[0013] The beneficial effects are as follows: This application utilizes an intelligent fusion terminal to acquire the actual current sequence, reducing the error caused by the data and making the subsequent acquisition of electrical energy more accurate. By selecting different window lengths, a second polynomial is obtained, and multi-frequency adaptive fitting is performed to accurately acquire the thermal drift error in the frequency domain. Combined with the first polynomial, time-domain correction is performed to achieve correction in both the time and frequency domains, avoiding spectral leakage and improving the measurement accuracy of the effective value of the circuit current.

[0014] Optionally, the calculation method of the first polynomial is as follows: collect the historical measured current sequence and historical temperature sequence of each phase of the energy meter in the historical time, and obtain the actual current sequence using the intelligent fusion terminal; collect the current measured current sequence and current temperature sequence of each phase of the energy meter in the current time;

[0015] The historical error sequence is obtained by calculating the difference between the actual current sequence and the historical measured current sequence at the same time. The first polynomial is obtained by fitting the historical temperature sequence and the historical error sequence using the least squares method.

[0016] The beneficial effect is that the first polynomial is obtained to determine the error of the current based on the temperature, so that subsequent time-domain correction can be performed.

[0017] Optionally, the second polynomial can be calculated as follows:

[0018] Select any phase as the target phase, divide the historical temperature sequence of the target phase into multiple temperature subsequences by any sequence length, calculate the average value of each temperature subsequence, and obtain the first average temperature sequence.

[0019] The historical measured current sequence is divided into multiple measurement subsequences by the same sequence length. The Fourier transform of the measurement subsequences is performed to obtain multiple spectrum diagrams. Any frequency is selected as the target frequency, and the measurement amplitude sequence of the target frequency is obtained based on any spectrum diagram. Similarly, the actual amplitude sequence is obtained.

[0020] The error amplitude sequence is obtained by calculating the difference between the actual amplitude sequence and the measured amplitude sequence at the same time. The error amplitude sequence and the first average temperature sequence are fitted to obtain the error fitting polynomial. The fitting error of the target phase is obtained by the difference between the fitted error amplitude sequence obtained by the error fitting polynomial and the corresponding error amplitude sequence. The average of the fitting errors of all phases is accumulated as the first average. The first average of the sequence length is accumulated as the first polynomial fitting error function value. The error fitting polynomial containing the smallest first polynomial fitting error function value is selected as the second polynomial.

[0021] The beneficial effect is that the fitting effect of the error fitting polynomial can be evaluated under different fine-grained conditions based on different window lengths, avoiding the situation where the fitting ability under multiple loads is locally optimal.

[0022] Optionally, the calculation method for the time-domain correction confidence is as follows: calculate the current current error sequence based on the current temperature sequence in the current electricity consumption data of the first polynomial; accumulate the current current error sequence with the data at the same time in the measured current sequence in the current electricity consumption data to obtain the time-domain corrected current sequence; and take the average value of the ratio of the time-domain corrected current sequence to the data at each time in the measured current sequence in the current electricity consumption data as the time-domain correction confidence.

[0023] The beneficial effect is that it provides the confidence level of the time-domain correction for subsequent calculation of the correction current sequence.

[0024] Optionally, the frequency domain correction confidence level is calculated as follows: Fourier transform the current measurement current sequence to obtain spectrum one; obtain the frequency amplitude error based on the second polynomial and the current temperature sequence; add the amplitude error of the same frequency to the amplitude of spectrum one and perform inverse Fourier transform to obtain the frequency domain correction current sequence; calculate the ratio of the current measurement current sequence and the frequency domain correction current sequence at the same time and take the average value to obtain the frequency domain correction confidence level.

[0025] The beneficial effect is that it provides the confidence level of the frequency domain correction so that the correction current sequence can be calculated subsequently.

[0026] Optionally, the method for calculating the correction current sequence is as follows:

[0027] Choose any time as the target time, add the time-domain correction confidence and the frequency-domain correction confidence as the first sum, take the ratio of the time-domain correction confidence to the first sum as the first ratio, and multiply the target time current value in the time-domain corrected current sequence by the first ratio as the first product; take the ratio of the frequency-domain correction confidence to the first sum as the second ratio, and multiply the target time current value in the frequency-domain corrected current sequence by the second ratio as the second product, and obtain the corrected current value at the target time based on the sum of the first product and the second product, and calculate the corrected current value at each time to obtain the corrected current sequence.

[0028] The beneficial effect is that a corrected current sequence is obtained so that the effective value of the current can be calculated subsequently.

[0029] Optionally, the reciprocal of the fundamental frequency of the current is used as the length of the sliding division of the correction current sequence to divide the correction current sequence into multiple correction sub-sequences. The sequence containing the correction current at the current moment is taken as the first sequence, and the sequence preceding the first sequence is taken as the second sequence. Fourier transform is performed on the first sequence to obtain the second spectrum. The first fundamental phase, the first fundamental energy, and the total energy of the first harmonic are obtained from the second spectrum. Similarly, the second fundamental phase, the second fundamental energy, and the total energy of the second harmonic are obtained from the second sequence.

[0030] Optionally, the adaptive calculation frequency is calculated as follows: the ratio of the total energy of the second harmonic to the energy of the second fundamental wave is used as the third ratio, the ratio of the total energy of the first harmonic to the energy of the first fundamental wave is used as the fourth ratio, the difference between the third ratio and the fourth ratio is normalized as the first processing, the sum of the frequencies of the first sequence and the second sequence and the fundamental frequency is used as the second sum, and the target phase adaptive calculation frequency is obtained by multiplying the second sum and the first processing; the average value of the adaptive calculation frequencies of all phases is calculated to obtain the adaptive calculation frequency.

[0031] The beneficial effect is that the calculation frequency is adaptively adjusted by combining adjacent windows.

[0032] Optionally, the method for calculating the effective current value based on the weighting factor and the average current amplitude of the effective current sequence IMF components is as follows: the reciprocal of the adaptive calculation frequency is taken as the effective sequence length; the weighting factor is multiplied by the average current amplitude of the effective current sequence IMF components, and the product of all IMF components is accumulated and the square root is taken to obtain the effective current value.

[0033] Secondly, this application provides a system for improving circuit accuracy based on an intelligent fusion terminal, which adopts the following technical solution:

[0034] A system that improves circuit accuracy based on intelligent fusion terminals, including processors and memory.

[0035] The beneficial effect is that the above-mentioned method for improving circuit accuracy based on intelligent fusion terminals is used to generate a computer program and stored in a memory so that it can be loaded and executed by a processor. Thus, a system can be made based on the memory and processor, which is convenient to use.

[0036] This application has the following technical effects:

[0037] This application collects data from each phase to avoid significant errors caused by phase imbalances due to different loads or by ignoring harmonic components in different phases. Furthermore, a fixed effective value calculation window can lead to spectral leakage. This application can analyze the temperature-dependent effects on current components of different frequencies in the circuit, performing dual-dimensional correction of the current in both the time and frequency domains. It also adaptively adjusts and weights the effective current value calculation based on the length of the effective value calculation window before and after correction, improving the accuracy of the effective current value in the circuit and making the acquisition of user branch circuit power more precise. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the method for improving circuit accuracy based on an intelligent fusion terminal, as described in this application. Detailed Implementation

[0039] This application discloses a method for improving circuit accuracy based on an intelligent fusion terminal, including: calculating the effective value of current; inputting the effective value of current at each corresponding previous time moment to the intelligent fusion terminal to obtain the power of the user branch circuit at the current time, so as to improve the measurement circuit accuracy of the user branch circuit by the intelligent fusion terminal; refer to Figure 1 The calculation method for the effective value of the current includes steps S1-S9, as detailed below:

[0040] S1: Construct a current error-temperature fitting polynomial based on historical electricity consumption data as the first polynomial for time-domain dimension correction.

[0041] The historical and current measured current sequences of each phase of the three-phase energy meter are collected using current transformers; the actual current sequence is obtained using a smart fusion terminal; and the historical and current temperature sequences of each phase of the three-phase energy meter are collected using temperature sensors. One user branch circuit corresponds to one three-phase energy meter, and an example sampling frequency of 5kHz is used.

[0042] The difference between the actual current sequence and the historical measured current sequence at the same time is calculated to obtain the historical error sequence. The historical temperature sequence and the historical error sequence are fitted using the least squares method to obtain the first polynomial.

[0043] Single-time-domain correction cannot identify the differences in harmonic components on each phase. Using a fixed effective value sequence length for the current value after single-time-domain correction will result in spectral leakage, leading to low measurement accuracy of the effective value of the circuit current.

[0044] In electricity metering, the voltage, current, and energy data on the circuit are usually a comprehensive signal of a three-phase system. The accuracy of this data depends on the accuracy of each phase. Different phases have different error magnitudes due to load imbalance or load harmonic differences. Processing the comprehensive signal can easily mask single-phase errors and reduce the ability to identify faults.

[0045] For historical electricity consumption processes, the difference between the actual current sequence and the historical measured current sequence is calculated to obtain the current error sequence. The least squares method is used to perform polynomial fitting on the historical temperature sequence and the current error sequence to obtain the first polynomial. The role of the first polynomial is to obtain the current error based on the temperature.

[0046] S2: Construct a fitting error based on historical electricity consumption data.

[0047] Select any phase as the target phase, divide the historical temperature sequence of the target phase into multiple temperature subsequences of arbitrary length, with each subsequence having a length of 1; calculate the average value of the data in each temperature subsequence to obtain the first average temperature sequence;

[0048] The historical measured current sequence is divided into multiple measurement subsequences by the same sequence length. The Fourier transform of the measurement subsequences yields multiple spectrograms. Any frequency is selected as the target frequency, and the measurement amplitude sequence of the target frequency is obtained based on any spectrogram. Similarly, the actual measured current sequence is divided into multiple actual subsequences by the same sequence length. The Fourier transform of the actual subsequences yields multiple spectrograms of the actual subsequences. Any frequency is selected as the target frequency, and the measurement amplitude sequence of the target frequency is obtained based on any actual subsequence spectrogram.

[0049] The error amplitude sequence is obtained by calculating the difference between the actual amplitude sequence and the measured amplitude sequence at the same time. The error fitting polynomial is obtained by fitting the error amplitude sequence and the first average temperature sequence. The fitting error of the target phase is obtained by the difference between the fitted error amplitude sequence obtained by the error fitting polynomial and the corresponding error amplitude sequence.

[0050] Repeat this process to obtain the fitting error of the target frequency in any phase for different sequence lengths.

[0051] In user branch circuits, current or voltage signals mainly consist of the fundamental frequency and various harmonics. Since different harmonics are affected differently by temperature, directly fitting the original signal in the time domain cannot identify the harmonic differences, resulting in significant limitations and applicability only to local moments. Therefore, this application analyzes the differences in the influence of temperature changes on the amplitude of different harmonics at different fine-grained levels, and obtains the frequency domain fitting error through multi-fine-grained dynamic fitting based on these differences.

[0052] S3: Then obtain the frequency domain amplitude error-temperature fitting polynomial for each frequency as the second polynomial for frequency domain dimension correction.

[0053] The average of all phase fitting errors is accumulated as the first average. The first average of the sequence length number of times is accumulated as the first polynomial fitting error function value. The error fitting polynomial containing the smallest first polynomial fitting error function value is selected as the second polynomial.

[0054] In one embodiment, the formula for calculating the frequency domain polynomial fitting error function can be:

[0055]

[0056] in, The frequency domain polynomial fitting error function represents the target frequency. Indicates the number of selected sequence lengths. Indicates the number of phases, Indicates the first The target frequency under the sequence length is the first The average value of the polynomial fitting error of the phase. The error fitting polynomial corresponding to the minimum frequency domain polynomial fitting error function value is selected as the second polynomial. The function of this polynomial is to obtain the amplitude error of the target frequency based on the temperature.

[0057] Since the user branch circuit is connected to a three-phase energy meter, the effective current value of the circuit is affected by the current on the three phases. Therefore, the average value of the polynomial fitting error on the three phases is used to evaluate the fitting effect of the polynomial. Using different sequence lengths can evaluate the fitting effect of the polynomial at different fine-grained levels. By using multiple fine-grained levels and three phases, the fitting ability of the polynomial under multiple load conditions can be comprehensively evaluated, avoiding the occurrence of local load optima.

[0058] Existing technologies directly fit the time-domain current, neglecting the influence of three-phase currents on the circuit current and the differences in harmonic components of the current in each phase. This results in the fitted polynomial being only suitable for historical power consumption processes and unable to obtain real-time errors. In contrast to existing technologies, this application analyzes the thermal drift error of the current fundamental and harmonics at different fine-grained levels by selecting different sequence lengths, and accurately obtains the thermal drift error in the frequency domain through multi-frequency adaptive fitting.

[0059] S4: Obtain the time-domain corrected current sequence and time-domain corrected confidence level based on the first polynomial and the current power consumption data; obtain the frequency-domain corrected current sequence and frequency-domain corrected confidence level based on the second polynomial and the current power consumption data.

[0060] The error current sequence of the current power consumption process is obtained based on the first polynomial and the current temperature sequence. The current current error sequence is accumulated with the data of the measured current sequence at the same time in the current power consumption data to obtain the time-domain corrected current sequence. The average value of the ratio of the time-domain corrected current sequence to the data of the measured current sequence at each time in the current power consumption data is used as the time-domain correction confidence level.

[0061] The frequency amplitude error is obtained by performing a Fourier transform on the current measurement current sequence. The amplitude error at the same frequency is obtained based on the second polynomial and the current temperature sequence. The amplitude error at the same frequency is added to the amplitude of the frequency spectrum one and then an inverse Fourier transform is performed to obtain the frequency domain corrected current sequence. The frequency domain corrected confidence level is obtained by calculating the ratio of the same time data of the current measurement current sequence and the frequency domain corrected current sequence and taking the average value.

[0062] Because the thermal drift error variation characteristics and temperature-dependent effects of current signals differ in the time and frequency domains, the thermal drift errors obtained in the time and frequency domains are different, and using only the time or frequency domain to obtain the thermal drift error has limitations. Therefore, this application obtains the thermal drift error in both the time and frequency domains to achieve a two-dimensional correction current, and then uses a weighted fusion based on the relative deviation between the corrected current and the measured current to achieve the two-dimensional correction current.

[0063] S5: Obtain the corrected current sequence based on the time-domain corrected current sequence, the time-domain corrected confidence level, the frequency-domain corrected current sequence, and the frequency-domain corrected confidence level.

[0064] Choose any time as the target time, add the time-domain correction confidence and the frequency-domain correction confidence as the first sum, take the ratio of the time-domain correction confidence to the first sum as the first ratio, and multiply the target time current value in the time-domain corrected current sequence by the first ratio as the first product; take the ratio of the frequency-domain correction confidence to the first sum as the second ratio, and multiply the target time current value in the frequency-domain corrected current sequence by the second ratio as the second product, and obtain the corrected current value at the target time based on the sum of the first product and the second product, and calculate the corrected current value at each time to obtain the corrected current sequence.

[0065] In one embodiment, the formula for calculating the correction current value can be:

[0066]

[0067] in, Indicates the target phase time during the current power consumption process. The correction current value, Indicates the confidence level of time-domain correction. Represents the time in the time-domain corrected current sequence The current value, Indicates the confidence level of frequency domain correction. Represents the time in the frequency domain corrected current sequence The current value is obtained. This process is repeated to obtain the corrected current value at each time step.

[0068] The larger the ratio of the measured current to the corrected current, the smaller the thermal drift error in a single frequency domain or time domain, and the higher the confidence level of the correction should be.

[0069] Compared with single time-domain correction, this patent can analyze the thermal drift error differences at different frequencies in the frequency domain and perform time-frequency domain dual-dimensional fusion correction.

[0070] Thus, the corrected current sequence for each phase of the current power consumption process is obtained.

[0071] S6: Adaptive calculation frequency for calculating the effective value of the current by sliding partitioning the corrected current sequence.

[0072] The reciprocal of the fundamental frequency of the current is used as the length of the sliding division of the correction current sequence. The correction current sequence is divided to obtain multiple correction sub-sequences. The sequence containing the correction current at the current moment is taken as the first sequence, and the sequence preceding the first sequence is taken as the second sequence. Fourier transform is performed on the first sequence to obtain the second spectrum. The first fundamental phase, the first fundamental energy, and the total energy of the first harmonic are obtained from the second spectrum. Similarly, the second fundamental phase, the second fundamental energy, and the total energy of the second harmonic are obtained from the second sequence.

[0073] A Fourier transform is performed on the second sequence to obtain its spectrum. Based on the spectrum, the second fundamental phase, the second fundamental energy, and the total energy of the second harmonic are obtained. The calculation of the fundamental phase, fundamental energy, and total harmonic energy is existing technology and will not be elaborated here.

[0074] Because users' electricity consumption patterns are complex and diverse, and the harmonic variations and thermal drift errors caused by nonlinear loads are highly volatile, fixed sequences are only suitable for calculating the effective current value of circuits under ideal conditions. They cannot be adjusted in real time and may lead to excessive residual harmonic component measurement errors due to spectral leakage. Therefore, this application analyzes the differences in harmonic component variations based on the length of a continuous sliding window sequence, synchronizes the sliding drift through the phase difference between adjacent sequences, and adaptively adjusts the calculation frequency by combining the changes in the ratio of harmonic and fundamental energy between adjacent sequences.

[0075] The ratio of the total energy of the second harmonic to the energy of the second fundamental wave is used as the third ratio, and the ratio of the total energy of the first harmonic to the energy of the first fundamental wave is used as the fourth ratio. The difference between the third and fourth ratios is normalized and used as the first processing. The sum of the frequencies of the first and second sequences and the fundamental frequency is used as the second sum. The target phase adaptive calculation frequency is obtained by multiplying the second sum and the first processing. The average value of the adaptive calculation frequencies of all phases is calculated to obtain the adaptive calculation frequency.

[0076] In one embodiment, the formula for calculating the adaptive calculation frequency can be:

[0077]

[0078] in, The adaptive calculation frequency represents the effective value of the target phase current. The initial calculation frequency (equal to the fundamental frequency) represents the effective value of the target phase current. This represents the difference between the phase of the first fundamental frequency and the phase of the second fundamental frequency. This represents the total energy of the second harmonic. Indicates the energy of the second fundamental wave. This represents the total energy of the first harmonic. This represents the energy of the first fundamental wave. Similarly, the adaptive calculation frequencies of the three phases are obtained, and the average is rounded down to obtain the adaptive calculation frequency of the effective current value.

[0079] Regarding the ratio of total harmonic energy to fundamental energy, when the ratio of the first sequence is greater than that of the second sequence, the calculation frequency should be appropriately reduced and the sequence length increased to smooth harmonic and noise fluctuations and improve the accuracy of RMS calculation; conversely, the calculation frequency should be appropriately increased and the sequence length decreased to reduce the cumulative effect of small harmonic and noise fluctuations and avoid excessive fluctuation response.

[0080] Thus, the adaptive calculation frequency of the effective current value is obtained.

[0081] S7: Determine the effective window length based on the adaptive calculation frequency, and obtain the current effective correction current sequence based on the effective window length and the correction current sequence of the target phase; similarly, obtain the current effective measurement current sequence.

[0082] In one embodiment, the reciprocal of the adaptive calculation frequency is used as the effective window length. The current effective corrected current sequence is obtained by truncating the target phase correction current sequence of the same length according to the effective window length. The current effective measured current sequence is obtained by truncating the target phase measurement current sequence of the same length according to the effective window length.

[0083] S8: Calculate the product of the average value of the frequency domain amplitude difference and the average value of the time domain amplitude difference between the effective corrected current sequence and the effective measured current sequence IMF components. Obtain the weighting factor based on the average value product and the average value of all average value products. Obtain the effective current value based on the weighting factor and the average current amplitude of the effective current sequence IMF components.

[0084] EMD (Empirical Mode Decomposition) is performed on the effective calibration current sequence to obtain multiple IMF (Intrinsic Mode Function) components of the effective calibration current sequence. Fourier transform is performed on the IMF components to obtain the first spectrum of each component. EMD is also performed on the effective measurement current sequence to obtain multiple IMF components of the effective measurement current sequence. Fourier transform is performed on the IMF components to obtain the second spectrum of each component.

[0085] For the effective correction current sequence and the effective measurement current sequence of the target phase, the average difference of the data at the same time is calculated to obtain the average value of the time domain amplitude difference; the average difference of the amplitude of the first spectrum and the second spectrum of the corresponding IMF component is calculated to obtain the average value of the frequency domain amplitude difference.

[0086] The effective current value is obtained by multiplying the weighting factor by the average current amplitude of the IMF component of the effective current sequence, and then taking the square root of the product of all IMF components.

[0087] In one embodiment, the formula for calculating the effective value of the current can be:

[0088]

[0089] in, This represents the effective current value of the user branch circuit target at the previous moment. Indicates the number of IMF components. The first part represents the effective corrected current sequence and the effective measured current sequence. The product of the average frequency domain amplitude difference and the average time domain amplitude difference between the IMF components. This represents the average of the products of all IMF components. Indicates the length of the effective correction current sequence. The first effective correction current sequence The first IMF component Each element.

[0090] A value greater than 0 indicates that the error of the corresponding IMF component correction is relatively small. The smaller the relative deviation of the effective current value it provides, the higher the accuracy and the greater the average current weight of its components.

[0091] Because nonlinear loads can introduce specific harmonic components into user branch circuits, existing technologies that calculate the RMS current value using the original signal ignore the impact of harmonic components on the accuracy of the RMS value, resulting in low accuracy in the RMS current calculation. Therefore, this application analyzes the time-domain and frequency-domain amplitude differences between different IMF components and the effective measured current sequence before correction to obtain the relative weight of each IMF component, thereby improving the accuracy of the RMS current calculation through relative weighting.

[0092] Compared with existing technologies that calculate the effective value of current based on the original signal and a fixed window length, this application obtains an accurate effective value of current by capturing the correction differences on different components through signal decomposition and weighted fusion.

[0093] Repeat this process to obtain the effective current value at each corresponding previous time step.

[0094] Thus, the measured current value is corrected in both time and frequency domains, and combined with the adaptive effective sequence length to obtain a high-precision effective current value.

[0095] S9: Input the current effective value of each phase at the current moment to the intelligent fusion terminal, and obtain the power of the user branch circuit at the current moment based on the high-precision current effective value.

[0096] This application also discloses a system for improving circuit accuracy based on a smart fusion terminal, including a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, the method for improving circuit accuracy based on a smart fusion terminal according to this application is implemented.

[0097] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

[0098] In this application, the aforementioned memory can be any tangible medium containing or storing a program that can be used or combined with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium can be any suitable magnetic or magneto-optical storage medium, such as resistive random access memory (DRAM), dynamic random access memory (DRAM), static random access memory (SRAM), etc., or any other medium that can be used to store desired information and can be accessed by an application program, module, or both. Any such computer storage medium can be part of a device or accessible to or connected to a device.

[0099] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A method for improving the accuracy of a circuit based on an intelligent converged terminal, characterized by, The method comprises the steps of: The current effective value is calculated; the current effective value of each phase at the current time is input into the intelligent fusion terminal to obtain the electric energy of the user branch circuit at the current time, so as to improve the measurement accuracy of the intelligent fusion terminal to the user branch circuit; The current effective value is calculated by the following method: A current error-temperature fitting polynomial is constructed according to historical power consumption data as a first polynomial for time domain correction; a fitting error is constructed according to historical power consumption data, and then a frequency domain amplitude error-temperature fitting polynomial of each frequency is obtained as a second polynomial for frequency domain correction; The time domain correction current sequence and the time domain correction confidence are obtained according to the first polynomial and the current power consumption data; the frequency domain correction current sequence and the frequency domain correction confidence are obtained according to the second polynomial and the current power consumption data; The corrected current sequence is obtained according to the time domain correction current sequence, the time domain correction confidence, the frequency domain correction current sequence and the frequency domain correction confidence. The adaptive calculation frequency of the corrected current sequence is calculated by sliding division; the current effective corrected current sequence is obtained according to the adaptive calculation frequency and the corrected current sequence of the target phase; the current effective measurement current sequence is obtained in the same way. The average value product of the frequency domain amplitude difference and the time domain amplitude difference between the IMF components of the effective corrected current sequence and the effective measurement current sequence is calculated; the weight factor is obtained according to the average value product and the average value of all the average value products; the current effective value is obtained according to the weight factor and the average current amplitude of the IMF components of the effective current sequence. The reciprocal of the fundamental frequency of the current is taken as the length of the sliding division of the corrected current sequence; the corrected current sequence is divided to obtain a plurality of corrected subsequences; the sequence containing the corrected current at the current time is taken as a first sequence, and the sequence located in front of the first sequence is taken as a second sequence; the Fourier transform of the first sequence is performed to obtain the first fundamental phase, the first fundamental energy and the first total harmonic energy of the first sequence; the second fundamental phase, the second fundamental energy and the second total harmonic energy of the second sequence are obtained in the same way. The adaptive calculation frequency is calculated by the following method: the ratio of the second total harmonic energy to the second fundamental energy is taken as a third ratio, the ratio of the first total harmonic energy to the first fundamental energy is taken as a fourth ratio, the difference between the third ratio and the fourth ratio is normalized as a first processing, the sum of the frequencies of the first sequence and the second sequence and the fundamental frequency is taken as a second sum, and the target phase adaptive calculation frequency is obtained according to the product of the second sum and the first processing. The average value of all phase adaptive calculation frequencies is calculated to obtain the adaptive calculation frequency.

2. The method for improving the accuracy of the circuit based on the intelligent fusion terminal according to claim 1, characterized in that, The first polynomial is calculated by the following method: the historical measurement current sequence and the historical temperature sequence of each phase of the historical time electric energy meter are collected, and the actual current sequence is obtained by the intelligent fusion terminal; the current measurement current sequence and the current temperature sequence of each phase of the current time electric energy meter are collected; The difference between the actual current sequence and the historical measurement current sequence at the same time is calculated to obtain the historical error sequence, and the first polynomial is obtained by fitting the historical temperature sequence and the historical error sequence by using the least square method.

3. The method for improving the accuracy of the circuit based on the intelligent fusion terminal according to claim 2, characterized in that, The second polynomial is calculated by the following method: Select any phase as the target phase, and divide the historical temperature sequence of the target phase into multiple temperature subsequences with any sequence length, calculate the average value of each temperature subsequence to obtain a first average temperature sequence; The historical measured current sequence is divided into multiple measurement subsequences with the same sequence length, and the measurement subsequences are subjected to Fourier transform to obtain multiple frequency spectra; any frequency is selected as a target frequency, and a measured amplitude sequence of the target frequency is obtained from any frequency spectrum; Similarly, an actual amplitude sequence is obtained; The difference between the actual amplitude sequence and the measured amplitude sequence of the target phase is calculated to obtain an error amplitude sequence; the error amplitude sequence and the first average temperature sequence are fitted to obtain an error fitting polynomial, and the difference between the fitting error amplitude sequence obtained from the error fitting polynomial and the corresponding error amplitude sequence is obtained to obtain a fitting error of the target phase; the average value of all phase fitting errors is accumulated as a first average value, and the first average value of the sequence length is accumulated as a first polynomial fitting error function value; the error fitting polynomial with the smallest first polynomial fitting error function value is selected as a second polynomial.

4. The method for improving the accuracy of the circuit based on the intelligent fusion terminal according to claim 1, characterized in that, The calculation method of the time domain correction confidence is as follows: the current temperature sequence in the current power consumption data of the first polynomial is used to calculate a current current error sequence, and the current current error sequence and the data at the same time of the measured current sequence in the current power consumption data are accumulated to obtain a time domain correction current sequence; the average value of the ratio of the time domain correction current sequence to the data at each time of the measured current sequence in the current power consumption data is taken as the time domain correction confidence.

5. The method for improving the accuracy of the circuit based on the intelligent fusion terminal according to claim 2, characterized in that, The calculation method of the frequency domain correction confidence is as follows: the current measured current sequence is subjected to Fourier transform to obtain a frequency spectrum one, the amplitude error of the frequency is obtained according to the second polynomial and the current temperature sequence, the amplitude error of the same frequency is added to the amplitude of the frequency spectrum one, and then inverse Fourier transform is performed to obtain a frequency domain correction current sequence; the ratio of the current measured current sequence to the frequency domain correction current sequence at the same time is calculated, and the average value is taken to obtain the frequency domain correction confidence.

6. The method for improving the accuracy of the circuit based on the intelligent fusion terminal according to claim 1, characterized in that, The calculation method of the correction current sequence is as follows: An arbitrary time is selected as a target time, the time domain correction confidence and the frequency domain correction confidence are added to obtain a first sum, the ratio of the time domain correction confidence to the first sum is taken as a first ratio, the current value at the target time in the time domain correction current sequence is multiplied by the first ratio to obtain a first product; the ratio of the frequency domain correction confidence to the first sum is taken as a second ratio, and the product of the current value at the target time in the frequency domain correction current sequence and the second ratio is taken as a second product; the correction current value at the target time is obtained according to the sum of the first product and the second product, and the correction current value at each time is calculated to obtain a correction current sequence.

7. The method for improving the precision of the circuit based on the intelligent fusion terminal according to claim 1, characterized in that, The calculation method of the current effective value according to the weight factor and the average current amplitude of the effective current sequence IMF component is as follows: the reciprocal of the adaptive calculation frequency is taken as an effective sequence length; The weight factor and the average current amplitude of the effective current sequence IMF component are multiplied to obtain a first product, and the square root of the sum of all IMF component products is taken to obtain the current effective value.

8. A system for improving the accuracy of a circuit based on an intelligent converged terminal, characterized by, The method comprises the following steps: A processor and a memory, the memory storing computer program instructions which, when executed by the processor, implement the method for improving circuit accuracy based on a smart converged terminal according to any one of claims 1-7.

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