Power grid state identification method and system

Abstract

This invention discloses a method and system for identifying power grid status, belonging to the fields of power quality analysis and signal analysis. The method includes sampling single-phase current at a common coupling point, decomposing the grid-connected current harmonics using wavelet packets, calculating the energy proportion in a specific frequency band, setting a threshold, and identifying the grid status. This method does not require injecting disturbances into the grid; instead, it determines the grid status by performing a recursive discrete Fourier transform on the AC grid-connected current and analyzing the distribution of its harmonic frequencies.

Description

Technical Field

[0001] The present invention relates to the fields of power quality analysis and signal analysis, and to a power grid state identification method and system. Background Art

[0002] With the increasing application of new energy, the strength of the power grid has weakened. At the same time, the addition of series compensation equipment has also changed the impedance state of the power grid. The impedance state of a weak power grid is reflected in the large impedance, while the impedance state of a series-compensated power grid is reflected in the series connection of capacitors and inductors. When the power grid exists in these two states, it will affect the stability of the power grid. At the same time, the harmonic frequency bands they generate are different. Wavelet packet decomposition can decompose the signal into different frequency bands in the frequency domain. Therefore, the state of a weak power grid and a series-compensated power grid can be identified based on the harmonic frequency bands.

[0003] Currently, there is not much research on pure grid state identification, but more on grid impedance measurement, such as:

[0004] Reference 1, entitled “D.K. Alves, R.L. A. Ribeiro, F.B. Costa and T.O.A. Rocha, ″Real-Time Wavelet-Based Grid Impedance Estimation Method″, in IEEE Transactions on Industrial Electronics, vol. 66, no. 10, pp. 8263-8265, Oct. 2019.” (IEEE Transactions on Industrial Electronics, 2019, published online), proposes a method using a steady-state technique to estimate grid impedance by injecting interharmonic currents into the grid and measuring the voltage response at the point of common coupling. The proposed method is compared with impedance estimation methods based on discrete Fourier transform and continuous wavelet transform to demonstrate its performance. The article only measures and calculates the grid impedance and does not estimate the grid state parameters.

[0005] Reference 2, entitled "FBCosta, "Fault-Induced Transient Detection Based on Real-Time Analysis of the Wavelet Coefficient Energy," in IEEE Transactions on Power Delivery, vol. 29, no. 1, pp. 140-153, Feb. 2014." (IEEE Transactions on Power Delivery, 2014, published online), states that wavelet-based methods are considered a promising alternative for real-time fault detection. This paper proposes a wavelet-based method for real-time detection of transmission line fault transients, where the wavelet coefficient energy takes into account the boundary effects of the sliding window. The paper uses wavelet energy coefficients to detect grid fault characteristics, which, in a sense, also constitute grid characteristics of weak grids and series-compensated grids.

[0006] Reference 3, entitled "Chen Qiaodi, Zhang Xing, Li Ming, Guo Zixuan, Liu Xiaoxi, Zhao Wei. Island detection method for droop-controlled grid-connected inverter based on impedance identification [J]. Automation of Power Systems, 2020, 44(07): 123-129." The paper extracts the harmonics of a specific frequency band through recursive Fourier transform and estimates the impedance. However, the Fourier transform calculation can only obtain the harmonic information of one frequency point at a time. To obtain the information of a certain frequency band, multiple calculations are required, which is very time-consuming.

[0007] Based on the above literature, the existing technology has the following deficiencies:

[0008] 1. Most existing methods measure the impedance of the line and then calculate the short-circuit capacity ratio, but there is little research on the impedance state identification of the power grid;

[0009] 2. The existing method of identifying the state of the power grid through impedance usually involves first calculating the specific value of the impedance and then judging the power grid state based on the value. This method is relatively complicated.

[0010] 3. Existing state identification methods usually inject disturbances of a specific frequency and then analyze them through Fourier transform, which increases time cost. Summary of the Invention

[0011] The present invention proposes a grid status identification method, which identifies weak grids and series compensation grids by measuring the characteristics of the common coupling point (PCC)'s own current harmonics, and then performs the next step of inverter adaptive control to improve the stability of the grid-connected system.

[0012] The object of the present invention is achieved in this way. The present invention provides a method for identifying the state of a power grid, the steps of which are as follows:

[0013] S1, with a given sampling frequency f s Get the A-phase current sampling value I of the common coupling point PCC A , the common coupling point PCC is the connection point between the power generation system and the power grid;

[0014] S2, for the I A Perform wavelet packet decomposition and record the i-th wavelet packet node of the j-th layer as node S j，i , node S j，i The wavelet packet coefficients are denoted as coefficients Where j is the decomposition level and j = 1, 2, ..., 6, a is the translation amount and a = 0, 1, ..., 2 j-1 , t is time, i is node S j，i Node number, i = 1, 2, 3, ..., 2 j ;

[0015] S3, take one of the j layers as the setting layer, record the setting layer as the mth layer, and record the nth node of the mth layer as node S m，n , n=1,2,..,8, computing nodes S m，n Energy E m，n ;

[0016] S4, computing node S m，1 The ratio G to the energy sum of the first n nodes m，1 and node S m，6 The ratio G to the energy sum of the first n nodes m，6 ;

[0017] S5, given a threshold, through the threshold and G m，1 , G m，6 The grid status is identified by comparing the sizes of

[0018] Preferably, in S2, the I A The binary wavelet function is used for wavelet packet decomposition:

[0019] ψ j，a (t) = 2 -j / 2 ψ(2 -j -a)

[0020] Preferably, the A phase current sampling value I A Perform 6-layer wavelet packet decomposition, the specific expression is:

[0021]

[0022] Where h(a) is a low-pass filter and g(a) is a high-pass filter. The data after the low-pass filter is the low-frequency component, and the data after the high-pass filter is the high-frequency component.

[0023] Preferably, according to f=1, 2, 3, ..., 2 j The maximum value of f is 64, and the A phase current I is transformed by wavelet packet transform. A Decomposed in the frequency domain with a span of 50 Hz, we get S 6，n specific frequency band.

[0024] Preferably, the S 6，i The specific frequency bands are [0, 50), [50, 100), [150, 200), [100, 150), [350, 400), [300, 350), [200, 250), [250, 300).

[0025] Preferably, the set layer in S3 is the 6th layer, that is, m=6, and the node S 6，n Energy E 6，n The calculation formula is as follows:

[0026]

[0027] Wherein, n=1, 2, .., 8.

[0028] Preferably, the ratio G in S4 6，1 , ratio G 6，6 The calculation formulas are as follows:

[0029]

[0030]

[0031] Preferably, the given threshold in S5 is determined by comparing the threshold with G m，1 , G m，6 The process of comparing the size of and identifying the power grid status is as follows:

[0032] Given a first threshold ε1 and a second threshold ε2:

[0033] If G 6，1 ≥ε1, the grid state is series compensation state;

[0034] If G 6，6 ≥ε2, the grid state is weak.

[0035] The present invention also provides a power grid status identification system, comprising:

[0036] The power generation system is connected to the power grid;

[0037] Used to obtain the A-phase current sampling value I of the common coupling point PCC A Sampling module;

[0038] For I A A processing module for performing wavelet packet decomposition;

[0039] Used to calculate the energy E of the set layer node m，n The calculation module;

[0040] Used to calculate the set layer node S m，1 The ratio G to the energy sum of the first n nodes m，1 and node S m，6 The ratio G to the energy sum of the first n nodes m，6 The calculation module;

[0041] For the given threshold and G m，1 , G m，6 An identification and judgment module for identifying the power grid state by comparing the size of

[0042] and a microprocessor and a memory connected to each other, wherein each module and the microprocessor are programmed or configured to execute the steps of the grid state identification method.

[0043] The present invention further provides a computer-readable storage medium storing a computer program programmed or configured to execute the power grid state identification method.

[0044] Compared with the existing technology, the beneficial effects of the present invention are:

[0045] 1. The method of the present invention identifies the weak grid and the series compensation grid by measuring the harmonic characteristics of the current at the grid connection point itself, and performs the next step according to the identified status;

[0046] 2. Skip the complex impedance calculation process and directly enter the state identification, which simplifies the algorithm and saves time costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a flow chart of the power grid state identification method based on wavelet packet decomposition of the present invention.

[0048] Figure 2 This is the wavelet packet decomposition waveform of the series compensated power grid in the embodiment of the present invention.

[0049] Figure 3 is the energy percentage of the wavelet packet coefficient in the series compensated power grid in the embodiment of the present invention.

[0050] Figure 4 This is the wavelet packet decomposition waveform under a weak power grid in an embodiment of the present invention.

[0051] Figure 5 is the energy percentage of the wavelet packet coefficients under the weak power grid in the embodiment of the present invention. DETAILED DESCRIPTION

[0052] This embodiment will be described in detail below with reference to the accompanying drawings.

[0053] Figure 1 This is a flow chart of the power grid state identification method based on wavelet packet decomposition of the present invention. Figure 1 It can be seen that the present invention provides a method for identifying the state of a power grid. The method decomposes the grid-connected current harmonics by wavelet packets and identifies the state of the power grid according to the distribution law of the harmonic amplitudes in different frequency bands. Specifically, the steps of the identification method are as follows:

[0054] Step 1: The connection point between the power generation system and the power grid is recorded as the common coupling point PCC, and the sampling frequency is f s = 6400 Hz to sample the A-phase current at the common coupling point PCC, and obtain the A-phase current sampling value I A .

[0055] Step 2: Phase A current I A Perform 6-layer wavelet packet decomposition and record the i-th wavelet packet node of the j-th layer as node S j，i , node S j，i The wavelet packet coefficients are denoted as coefficients Where j is the number of decomposition levels and j = 1, 2, ..., 6, a is the translation amount, a = 0, 1, ..., 2 j-1 , t is time, i is node S j，i Node number, i = 1, 2, 3, ..., 2 j .

[0056] In the wavelet packet transform, the decomposition level j is the scaling scale, corresponding to the frequency, and the translation a corresponds to the time.

[0057] The A-phase current I A The process of performing 6-layer wavelet packet decomposition is as follows:

[0058] The binary wavelet function is as follows:

[0059] ψ j，a (t) = 2 -j / 2 ψ(2 -j -a)

[0060] The A phase current I sampled in S1 A Perform 6-layer wavelet packet decomposition, the specific expression is:

[0061]

[0062] Where h(a) is a low-pass filter and g(a) is a high-pass filter. The data that passes through the low-pass filter is the low-frequency component, and the data that passes through the high-pass filter is the high-frequency component.

[0063] According to i=1,2,3,...,2 j The maximum value of i is 64, and the A phase current I is converted to A Decomposed in the frequency domain with a span of 50 Hz, we get S 6，n specific frequency band.

[0064] The S 6，n The specific frequency bands are [0, 50), [50, 100), [150, 200), [100, 150), [350, 400), [300, 350), [200, 250), [250, 300).

[0065] Step 3: record the first 8 nodes of the 6th layer as node S 6，n , n=1,2,..,8, computing nodes S 6，n Energy E 6，n .

[0066] In this embodiment, the energy E 6，n The calculation formula is as follows:

[0067]

[0068] Step 4: Calculate node S 6，1 The ratio G to the energy sum of the first 8 nodes 6，1 Node S 6，6 The ratio G to the energy sum of the first 8 nodes 6，6 .

[0069] In this embodiment, the ratio G 6，1 , ratio G 6，6 The calculation formulas are as follows:

[0070]

[0071]

[0072] Step 5: Set a threshold and identify the grid status.

[0073] In this embodiment, the specific process is as follows:

[0074] Given a first threshold ε1 and a second threshold ε2:

[0075] If G 6，1 ≥ε1 The grid state is series compensation state;

[0076] If G6，6 ≥ε2, the grid state is weak.

[0077] In this embodiment, ε1=ε2=10.

[0078] Figure 2 : This is the wavelet packet decomposition waveform of the embodiment of the present invention under the series compensation power grid, which represents the frequency bands [0, 50), [50, 100), [150, 200), [100, 150), [350, 400), [300, 350), [200, 250), [250, 300).

[0079] Figure 3 The energy ratio of the first 8 nodes to the total energy in the series compensation grid according to the embodiment of the present invention is as follows: 6，1 ≥ε1, it is identified as a series compensated power grid.

[0080] Figure 4 : This is the wavelet packet decomposition waveform of the embodiment of the present invention under weak power grid, and the frequency bands represented are [0, 50), [50, 100), [150, 200), [100, 150), [350, 400), [300, 350), [200, 250), [250, 300).

[0081] Figure 5 The energy ratio of the first 8 nodes to the total energy in the weak power grid of the embodiment of the present invention is shown in Figure 1. It can be seen that the energy ratio of the second node where the fundamental frequency is located is the largest, followed by the sixth node, and G 6，6 ≥ε2, identified as a weak power grid.

[0082] The present invention also provides a power grid status identification system, comprising:

[0083] The power generation system is connected to the grid; it is used to obtain the A-phase current sampling value I of the common coupling point PCC A Sampling module for I A Processing module for wavelet packet decomposition; used to calculate the energy E of the set layer node m，n Calculation module; used to calculate the set layer node S m，1 The ratio G to the energy sum of the first n nodes m，1 and node S m，6 The ratio G to the energy sum of the first n nodes m，6 The calculation module is used to calculate the value of G by giving a threshold value. m，1 , G m，6an identification and determination module for comparing the size of the grid state; and a microprocessor and a memory connected to each other, each of the modules and the microprocessor being programmed or configured to execute the steps of the grid state identification method.

[0084] The present invention further provides a computer-readable storage medium storing a computer program programmed or configured to execute the power grid state identification method.

[0085] The circuit topology and identification method of the present invention described above can be viewed as separate hardware implementations of the circuit topology, as software implementations of the identification method alone, or as implementations of a control system based on this combination of hardware and software. Furthermore, the identification method portion of the present invention can be implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code, in the form of a computer program product. The method can be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0086] Furthermore, the embodiments of the present invention are described in conjunction with flowcharts and / or block diagrams. It should be understood that each process and / or block in the flowcharts and / or block diagrams of the present invention, as well as the combination of the processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the present invention. Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the function specified in the process of the present invention. Figure 1 a process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process of the present invention. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0087] Therefore, the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Changes and modifications made by those skilled in the art based on the specific implementation methods of the present invention and the above circumstances should be regarded as equivalent solutions of this application and should fall within the scope of protection of the present invention.

Claims

1. A method for identifying a power grid state, characterized in that: Here are the steps: S1, with a given sampling frequency f s Get the A-phase current sampling value I of the common coupling point PCC A , the common coupling point PCC is the connection point between the power generation system and the power grid; S2, for the I A Perform wavelet packet decomposition and record the i-th wavelet packet node of the j-th layer as node S j,i , node S j,i The wavelet packet coefficients are denoted as coefficients Where j is the number of decomposition levels and j = 1, 2, ..., 6, a is the translation amount and a = 0, 1, ..., 2 j-1 , t is time, i is node S j,i Node number, i=1,2,3,...,2 j ; S3, take one of the j layers as the setting layer, record the setting layer as the mth layer, and record the nth node of the mth layer as node S m,n , n=1,2,..,8, computing nodes S m,n Energy E m,n ; S4, computing node S m,1 The ratio G to the energy sum of the first n nodes m,1 and node S m,6 The ratio G to the energy sum of the first n nodes m,6 ; S5, given a threshold, through the threshold and G m,1 , G m,6 The grid status is identified by comparing the size of S2 is for the I A The binary wavelet function is used for wavelet packet decomposition: ψ j,a (t)=2 -j / 2 ψ(2 -j -a) The sampling value of phase A current I A Perform 6-layer wavelet packet decomposition, the specific expression is: Where h(a) is a low-pass filter and g(a) is a high-pass filter. The data after the low-pass filter is the low-frequency component, and the data after the high-pass filter is the high-frequency component. The setting layer in S3 is the 6th layer, that is, m=6, the node S 6,n Energy E 6,n The calculation formula is as follows: Where n = 1, 2, ..., 8.

2. A method for identifying a power grid state according to claim 1, characterized in that: According to i=1,2,3,...,2 j The maximum value of i is 64, and the A phase current I is converted to A Decomposed in the frequency domain with a span of 50 Hz, we get S 6,i specific frequency band.

3. A method for identifying a power grid state according to claim 1 or 2, characterized in that: The S 6,i The specific frequency bands are [0,50), [50,100), [150,200), [100,150), [350,400), [300,350), [200,250), [250,300).

4. A method for identifying a power grid state according to claim 1, characterized in that: The ratio G described in S4 6,1 , ratio G 6,6 The calculation formulas are as follows:

5. A method for identifying a power grid state according to claim 1, characterized in that: The threshold value is given in S5, and the threshold value is compared with G m,1 , G m,6 The process of comparing the size of and identifying the power grid status is as follows: Given a first threshold ε1 and a second threshold ε2: If G 6,1 ≥ε1, the grid state is series compensation state; If G 6,6 ≥ε2, the grid state is weak.

6. A power grid status identification system, characterized in that: include: The power generation system is connected to the power grid; Used to obtain the A-phase current sampling value I of the common coupling point PCC A Sampling module; For I A A processing module for performing wavelet packet decomposition; Used to calculate the energy E of the set layer node m,n The calculation module; Used to calculate the set layer node S m,1 The ratio G to the energy sum of the first n nodes m,1 and node S m,6 The ratio G to the energy sum of the first n nodes m,6 The calculation module; For the given threshold and G m,1 , G m,6 An identification and judgment module for identifying the power grid state by comparing the size of and interconnected microprocessors and memories, each of the modules and microprocessors being programmed or configured to execute the steps of the grid status identification method according to any one of claims 1 to 5.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program programmed or configured to execute the power grid status identification method according to any one of claims 1 to 5.

Images