Method and system for measuring broadband dynamic harmonic pure real number of power distribution network

Abstract

The invention provides a power distribution network broadband dynamic harmonic pure real number measurement method and system. The method comprises the steps of obtaining a measurement electrical quantity discrete sampling sequence in a power grid; constructing a discrete signal measurement model based on the obtained measurement electrical quantity discrete sampling sequence in the power grid, and calculating a filter bank based on the discrete signal measurement model; further calculating a measurement initial value; starting iterative calculation, judging whether an iteration upper limit is reached or not, if so, directly outputting a measurement result, and if not, calculating frequency response, and updating filter bank pass band and stop band frequency response according to the frequency measurement result; estimating a measurement error based on the updated frequency response; performing error compensation on each order derivative of the composite modulation component based on the estimated measurement error to obtain each order derivative of the composite modulation component of the mth component; and based on each order derivative of the composite modulation component of the mth component, identifying each order derivative of the amplitude and the phase, and obtaining output results of the amplitude, the phase and the frequency of the broadband dynamic harmonic wave of the power distribution network.

Description

Technical Field

[0001] The invention belongs to the technical field of broadband synchronous measurement of power systems, and in particular relates to a broadband dynamic harmonic pure real number measurement method and system for a distribution network. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Large-scale wind and solar power sources, energy storage, DC transmission and distribution projects, and electric vehicle charging piles are connected to the new power system through power electronic equipment. Safety and stability issues such as sub / super synchronous power oscillations, high-frequency oscillations, and commutation failures, as well as power quality issues such as harmonic distortion are becoming increasingly serious. In order to enhance the broadband safety and stability monitoring capabilities of the power grid, a new broadband dynamic measurement device is added. The broadband dynamic measurement structure includes a sampling module, a communication module, a broadband identification module, and a synchronous clock module; ② Broadband signals refer to signals with multiple oscillation modes in a wider bandwidth, as well as the need to upgrade the broadband dynamic measurement function of existing measurement terminals and enhance the broadband dynamic observation performance of the built-in control module of the grid-connected converter. These requirements have gradually penetrated into all aspects of the source, grid, and load.

[0004] Wideband dynamic measurement is to identify the frequency, amplitude, phase and other characteristics of frequency components such as fundamental wave, harmonics and interharmonics in a wider frequency band. It requires that the frequency resolution of the measurement algorithm is sufficient to extract all frequency components, and it can still maintain high-precision identification capability when the amplitude and frequency of the components change dynamically over time, such as ramp and oscillation, after the power grid disturbance. At present, the most commonly used wideband dynamic measurement algorithm for measurement devices is the Fourier transform algorithm, but it is difficult to adapt to the time-varying amplitude and frequency of power grid disturbance. Parameter algorithms and phasor series expansion algorithms can achieve wideband high-precision measurement in the time-varying amplitude and frequency of power grid disturbance, but they need to perform a large number of complex matrix operations, with high computational complexity, and the temporary complex matrix storage required in the execution process occupies a large amount of memory space. In order to ensure the reliability of the operation of the power grid equipment controller, an upper limit is usually set for the calculation load rate of the microcontroller unit (MCU) to prevent the MCU from crashing. However, the initial selection of MCUs for existing measurement terminals in the power grid did not take into account the needs of broadband dynamic measurement. The MCUs are low-cost and relatively backward in performance. New broadband dynamic measurement devices generally also choose low-cost MCUs with low computing frequency. Broadband dynamic measurement easily leads to a high MCU computing load rate. In addition, the MCU's on-chip random access memory (RAM) space is only tens or hundreds of kB, and a large number of temporary complex matrices need to be stored in the external extended RAM. Frequent access to the external extended RAM during the algorithm execution process consumes more main frequency clocks than accessing the on-chip RAM, further increasing the MCU computing load rate. In addition, low-cost MCUs usually do not support direct complex operations, and the complex algorithm needs to be processed into real numbers according to the specific type of MCU, and the generalization application capability is poor.

[0005] Therefore, there is an urgent need to study a low-complexity, low-storage method for fast measurement of wide-band dynamic signals in real numbers. Summary of the invention

[0006] In order to overcome the deficiencies of the above-mentioned prior art, the present invention provides a pure real number measurement method for broadband dynamic harmonics in distribution networks, which avoids complex matrix operations and real number conversion processes while achieving high-precision measurement, reduces computational complexity and memory overhead, and improves the versatility of the algorithm.

[0007] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0008] In a first aspect, a pure real number measurement method for broadband dynamic harmonics in a distribution network is disclosed, comprising:

[0009] Obtaining a discrete sampling sequence of measured electrical quantities in the power grid;

[0010] Based on obtaining the discrete sampling sequence of measured electrical quantities in the power grid, a discrete signal measurement model is constructed, and a filter bank is calculated based on the discrete signal measurement model;

[0011] Based on the calculated filter bank and the discrete sampling sequence of the measured electrical quantity in the power grid, the optimal solution vector of the column vector of each order derivative of the complex modulation component to be calculated is calculated, and the initial value of the measurement is further calculated;

[0012] Start iterative calculation to determine whether the iteration upper limit is reached. If so, directly output the measurement result. If not, calculate the frequency response and update the passband and stopband frequency response of the filter bank according to the frequency measurement result.

[0013] estimating a measurement error based on the updated frequency response;

[0014] Performing error compensation on derivatives of each order of the composite modulation component based on the estimated measurement error to obtain derivatives of each order of the composite modulation component of the mth component;

[0015] Based on the derivatives of the composite modulation components of the mth component, the amplitude and phase derivatives are identified to obtain the pure real output result of the broadband dynamic harmonics of the distribution network.

[0016] As a further technical solution, a discrete sampling sequence of measured electrical quantities in the power grid is obtained, which contains information on the number of sampling points, sampling intervals and window lengths.

[0017] As a further technical solution, the discrete signal measurement model is constructed as follows:

[0018] S=DA

[0019] Where S is the discrete sampling sequence of the measured electrical quantity in the power grid, is the Taylor expansion basis matrix of the complex modulation component, is the column vector of derivatives of each order of the complex modulation component to be determined, M is the number of components, K is the Taylor expansion order, and N is the window length.

[0020] As a further technical solution, the optimal solution vector of the column vector of each order derivative of the complex modulation component to be determined is calculated, and then the initial value in the optimal solution vector is calculated, and the measurement initial value is calculated based on the initial value in the optimal solution vector.

[0021] As a further technical solution, the measurement error is estimated based on the updated frequency response, including: the measurement error estimate of the measured component considering its own frequency response distortion, and the measurement error estimate of the measured component caused by interference from other components.

[0022] As a further technical solution, the pure real number output result of the broadband dynamic harmonics of the distribution network includes amplitude, phase and frequency.

[0023] In the second aspect, a pure real number measurement system for broadband dynamic harmonics in a distribution network is disclosed, comprising:

[0024] The data acquisition module is configured to: acquire a discrete sampling sequence of measured electrical quantities in the power grid;

[0025] The filter bank calculation module is configured to: construct a discrete signal measurement model based on a discrete sampling sequence of measured electrical quantities in the power grid, and calculate the filter bank based on the discrete signal measurement model;

[0026] The measurement initial value calculation module is configured to: calculate the optimal solution vector of the column vector of each order derivative of the complex modulation component to be calculated based on the calculated filter group and the discrete sampling sequence of the measured electrical quantity in the power grid, and further calculate the measurement initial value;

[0027] The judgment module is configured to: start iterative calculation, judge whether the iteration upper limit is reached, if so, directly output the measurement result, if not, calculate the frequency response;

[0028] An updating module is configured to: update the passband and stopband frequency responses of the filter bank according to the frequency measurement result;

[0029] An estimation module is configured to: estimate a measurement error based on the updated frequency response;

[0030] The compensation module is configured to: perform error compensation on each order derivative of the composite modulation component based on the estimated measurement error to obtain each order derivative of the composite modulation component of the mth component;

[0031] The output module is configured to: identify the amplitude and phase derivatives based on the derivatives of the composite modulation component of the mth component, and obtain the pure real output result of the broadband dynamic harmonic of the distribution network.

[0032] One or more of the above technical solutions have the following beneficial effects:

[0033] In the technical solution of the present invention, a discrete signal measurement model is constructed, and a filter group is calculated based on the discrete signal measurement model; based on the calculated filter group and the discrete sampling sequence of the measured electrical quantity in the power grid, the optimal solution vector of the column vector of each order derivative of the complex modulation component to be calculated is calculated, and the initial measurement value is further calculated; in the process of calculating the initial measurement value, it is judged whether the iteration upper limit is reached, if so, the measurement result is directly output, if not, the frequency response is calculated, and the passband and stopband frequency responses of the filter group are updated according to the frequency measurement result; the measurement error is estimated based on the updated frequency response; based on the estimated measurement error, the error of each order derivative of the complex modulation component is compensated to obtain the each order derivative of the complex modulation component of the mth component; based on the each order derivative of the complex modulation component of the mth component, the amplitude and phase derivatives are identified to obtain the output result of the pure real number of the broadband dynamic harmonic of the distribution network.

[0034] In the above way, a pure real discrete measurement model of wide-band dynamic phasor based on Taylor expansion of time-varying amplitude and time-varying phase was established. By initializing the measurement filter group parameters by the least squares method, high-precision measurement of time-varying characteristics can be achieved. Moreover, the model only contains real numbers but no complex numbers, and is suitable for embedded measurement device applications.

[0035] Among them, the broadband multi-component dynamic signal is written into the form of trigonometric function, and the dynamic amplitude-frequency A is further converted into m (t) and φ m (t) Taylor expansion is performed to establish a pure real number discrete measurement model for wide-band dynamic phasor, which does not contain any complex numbers and realizes pure real number measurement.

[0036] In addition, the technical solution of the present invention provides a quantitative index of theoretical measurement error from the perspective of the frequency response of the proposed measurement model, thereby realizing rapid iterative compensation (correction) of the measurement error.

[0037] The parameters of the filter group calculated based on the discrete signal measurement model of the present invention can be used continuously after being obtained, without the need for real-time calculation, with low calculation complexity and low memory occupation.

[0038] The technical solution of the present invention avoids complex matrix operations and real number conversion processes while achieving high-precision measurement, reduces computational complexity and memory overhead, and improves algorithm versatility.

[0039] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0041] Figure 1 The figure is a measurement flow chart of a specific method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0042] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0043] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0044] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0045] Embodiment 1

[0046] This embodiment discloses a pure real number measurement method for broadband dynamic harmonics in a distribution network, establishes a broadband dynamic signal real number measurement model, and provides quantitative indicators from the perspective of frequency response, including: the measurement result of the measured component considering its own frequency response distortion, the measurement error of the measured component considering its own frequency response distortion, and the measurement error caused by the interference of other components on the measured component. Then, a pure real number broadband dynamic signal fast measurement method based on measurement error compensation is established, in order to support the broadband dynamic harmonic pure real number measurement method with low computational complexity, low memory overhead and high versatility for safe and stable monitoring of power grids. See the attached Figure 1 As shown, the specific steps include:

[0047] Step 1: Obtain a discrete sampling sequence of measured electrical quantities in the power grid where t n =nT s , N is the number of sampling points, and the sampling interval is T s , the window length is N = 2N h +1 and n=-N h ,…,N h ,in T is the window length, the window center t0 is the Taylor expansion point, n represents the sampling point, s(t n ) represents t n The sampling time, h is the abbreviation of half.

[0048] Step 2: Based on the obtained discrete sampling sequence of measured electrical quantities in the power grid, a discrete signal measurement model is constructed and a filter bank is calculated.

[0049] S=DA

[0050] In the formula, is the Taylor expansion basis matrix of the complex modulation component, is the column vector of the derivatives of each order of the complex modulation component to be determined, M is the number of components, K is the Taylor expansion order, and N is the number of sampling points.

[0051]

[0052] A=[x1,y1,…,x m ,y m ,…,x M ,y M ] T

[0053] and T stands for matrix transpose.

[0054] As shown below:

[0055]

[0056] and is the derivative of each order of the complex modulation component of the mth component, expressed as:

[0057]

[0058] In the formula, and x m (t) and y m (t) The k-th derivative with t=0 as the expansion point.

[0059] and is the complex modulation component of the mth component with ω Cm is the Taylor expansion basis vector of the center frequency, where is the k-th order expanded time coefficient diagonal matrix, and Expand basis vectors for trigonometric functions.

[0060]

[0061] The above method is to obtain Then calculate the filter bank

[0062]

[0063] Expressed as

[0064]

[0065] in, ω Cm The center frequency filter, For The center frequency filter.

[0066] Step 3: Perform initial measurements of derivatives of each order of the composite modulation component to obtain initial values ​​for subsequent iterative processes;

[0067] Calculate the optimal solution vector of A As shown below, the initial value is calculated

[0068]

[0069] Where S is the discrete sampling sequence of the measured electrical quantity obtained in step 1, Expressed as

[0070] Further calculation of the initial measurement value As shown below, the number of iterations j is set to zero.

[0071]

[0072] Step 4: The j-th iteration result Substitute into the j+1th iteration. Calculate the frequency response, which is used to estimate the measurement error later;

[0073] According to the frequency measurement results Update the filter bank passband and stopband frequency responses as follows Where h=1 to M.

[0074]

[0075] in, and Represents ω Cm The center frequency filter The response at any frequency ω is similarly: and Represents ω Cm The center frequency filter The response at any frequency ω.

[0076] Step 5: Estimation of derivative errors of each order of the complex modulation component;

[0077] The updated frequency response is compared with Substituting them into the following formula, we can estimate in and The measurement error of the measured component taking into account its own frequency response distortion, and It is the measurement error caused by the interference of other components on the measured component. The estimated value of the measurement error of the measured component taking into account its own frequency response distortion; It is an estimated value of the measurement error caused by the interference of other components on the measured component, and is used for subsequent compensation based on the estimated value of the measurement error;

[0078]

[0079] Step 6: Error compensation of each order derivative of the composite modulation component to obtain each order derivative of the composite modulation component of the mth component and This step gradually improves the accuracy, which is then used to calculate the amplitude and phase derivatives of various orders.

[0080] and Measurement results and It is indicated that compensation is performed by the following formula:

[0081]

[0082] Step 7: Identification of amplitude and phase derivatives of various orders;

[0083] Then use the following formula to calculate and Represent the mth harmonic amplitude and phase kth derivative respectively, and update the mth harmonic frequency estimate at the same time The number of iterations j increases by 1.

[0084]

[0085] Step 8: Iteration condition judgment:

[0086] Determine whether the upper limit of the number of iterations has been reached. If the upper limit of the number of iterations has not been reached, return to step 4; if the upper limit of the number of iterations has been reached, stop the iteration and go to step 9.

[0087] Step 9: Output the measurement results of broadband dynamic harmonics of the distribution network;

[0088] Output measurement results: amplitude, phase, frequency: and Embodiment 2

[0089] The purpose of this embodiment is to provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the program.

[0090] Embodiment 3

[0091] The purpose of this embodiment is to provide a computer-readable storage medium.

[0092] A computer-readable storage medium stores a computer program, which executes the steps of the above method when executed by a processor.

[0093] Embodiment 4

[0094] The purpose of this embodiment is to provide a pure real number measurement system for broadband dynamic harmonics in a power distribution network, including:

[0095] The data acquisition module is configured to: acquire a discrete sampling sequence of measured electrical quantities in the power grid;

[0096] The filter bank calculation module is configured to: construct a discrete signal measurement model based on a discrete sampling sequence of measured electrical quantities in the power grid, and calculate the filter bank based on the discrete signal measurement model;

[0097] The measurement initial value calculation module is configured to: calculate the optimal solution vector of the column vector of each order derivative of the complex modulation component to be calculated based on the calculated filter group and the discrete sampling sequence of the measured electrical quantity in the power grid, and further calculate the measurement initial value;

[0098] The judgment module is configured to: start iterative calculation, judge whether the iteration upper limit is reached, if so, directly output the measurement result, if not, calculate the frequency response;

[0099] An updating module is configured to: update the passband and stopband frequency responses of the filter bank according to the frequency measurement result;

[0100] An estimation module is configured to: estimate a measurement error based on the updated frequency response;

[0101] The compensation module is configured to: perform error compensation on each order derivative of the composite modulation component based on the estimated measurement error to obtain each order derivative of the composite modulation component of the mth component;

[0102] The output module is configured to: identify the amplitude and phase derivatives based on the derivatives of the composite modulation component of the mth component, and obtain the pure real output result of the broadband dynamic harmonic of the distribution network.

[0103] Embodiment 5

[0104] The purpose of this embodiment is to provide a computer program product containing instructions, which, when running on a computer, enables the computer to execute the methods and functions involved in any of the above embodiments.

[0105] The steps involved in the apparatus of the above embodiment correspond to the method embodiment 1, and the specific implementation method can refer to the relevant description part of embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood to include any medium that can store, encode or carry an instruction set for execution by a processor and enable the processor to execute any method in the present invention.

[0106] Those skilled in the art should understand that the modules or steps of the present invention described above can be implemented by a general-purpose computer device, or alternatively, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0107] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A pure real number measurement method for broadband dynamic harmonics in a distribution network, characterized in that: include: Obtaining a discrete sampling sequence of measured electrical quantities in the power grid; Based on obtaining the discrete sampling sequence of measured electrical quantities in the power grid, a discrete signal measurement model is constructed, and a filter bank is calculated based on the discrete signal measurement model; Based on the calculated filter bank and the discrete sampling sequence of the measured electrical quantity in the power grid, the optimal solution vector of the column vector of each order derivative of the complex modulation component to be calculated is calculated, and the initial value of the measurement is further calculated; Start iterative calculation to determine whether the iteration upper limit is reached. If so, directly output the measurement result. If not, calculate the frequency response and update the passband and stopband frequency response of the filter bank according to the frequency measurement result. estimating a measurement error based on the updated frequency response; Performing error compensation on derivatives of each order of the composite modulation component based on the estimated measurement error to obtain derivatives of each order of the composite modulation component of the mth component; Based on the derivatives of the composite modulation components of the mth component, the amplitude and phase derivatives are identified to obtain the pure real output result of the broadband dynamic harmonics of the distribution network.

2. The method for measuring pure real numbers of broadband dynamic harmonics in a distribution network as claimed in claim 1, characterized in that: The discrete sampling sequence of the measured electrical quantity in the power grid contains the number of sampling points, sampling interval and window length information.

3. The method for measuring pure real numbers of broadband dynamic harmonics in a distribution network as claimed in claim 1, characterized in that: The discrete signal measurement model is constructed as follows: S=DA Where S is the discrete sampling sequence of the measured electrical quantity in the power grid, is the Taylor expansion basis matrix of the complex modulation component, is the column vector of derivatives of each order of the complex modulation component to be determined, M is the number of components, K is the Taylor expansion order, and N is the window length.

4. The method for measuring pure real numbers of broadband dynamic harmonics in a distribution network as claimed in claim 1, characterized in that: The optimal solution vector of the derivative column vectors of each order of the complex modulation component to be calculated is calculated, and then the initial value in the optimal solution vector is calculated, and the measurement initial value is calculated based on the initial value in the optimal solution vector.

5. The method for measuring pure real numbers of broadband dynamic harmonics in a distribution network as claimed in claim 1, characterized in that: The measurement error is estimated based on the updated frequency response, including: an estimated value of the measurement error of the measured component taking into account its own frequency response distortion, and an estimated value of the measurement error caused by the measured component being interfered by other components.

6. The method for measuring pure real numbers of broadband dynamic harmonics in a power distribution network as claimed in claim 1, characterized in that: The pure real number output result of the broadband dynamic harmonic of the power distribution network includes amplitude, phase and frequency.

7. A pure real number measurement system for broadband dynamic harmonics in distribution networks, characterized by: include: The data acquisition module is configured to: acquire a discrete sampling sequence of measured electrical quantities in the power grid; The filter bank calculation module is configured to: construct a discrete signal measurement model based on a discrete sampling sequence of measured electrical quantities in the power grid, and calculate the filter bank based on the discrete signal measurement model; The measurement initial value calculation module is configured to: calculate the optimal solution vector of the column vector of each order derivative of the complex modulation component to be calculated based on the calculated filter group and the discrete sampling sequence of the measured electrical quantity in the power grid, and further calculate the measurement initial value; The judgment module is configured to: start iterative calculation, judge whether the iteration upper limit is reached, if so, directly output the measurement result, if not, calculate the frequency response; An updating module is configured to: update the passband and stopband frequency responses of the filter bank according to the frequency measurement result; An estimation module is configured to: estimate a measurement error based on the updated frequency response; A compensation module is configured to: perform error compensation on each order derivative of the composite modulation component based on the estimated measurement error to obtain each order derivative of the composite modulation component of the mth component; The output module is configured to: identify the amplitude and phase derivatives based on the derivatives of the composite modulation component of the mth component, and obtain the pure real output result of the broadband dynamic harmonic of the distribution network.

8. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method described in any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method described in any one of claims 1 to 6 are performed.

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