CN114944649B - Power grid state identification method based on electric quantity frequency spectrum - Google Patents
Power grid state identification method based on electric quantity frequency spectrum Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- G—PHYSICS
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
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Abstract
The invention discloses a power grid state identification method based on an electric quantity frequency spectrum, and belongs to the field of electric energy quality analysis and signal analysis. Specifically, the method is an online identification method of the state of the power grid based on signal processing of recursive discrete Fourier transform, and the method identifies that the system under study comprises an inverter main circuit (a direct-current side voltage source, a three-phase bridge inverter circuit and a three-phase LCL filter), a control unit, three-phase line impedance (three-term line inductance and three-phase line capacitance), an alternating-current side power grid (a three-phase power grid and a grounding module) and a power grid state identification unit (a state identification unit and a state output end). According to the method, disturbance does not need to be injected into the power grid, and the state of the power grid is judged only by carrying out recursive discrete Fourier transform on the current of the alternating current grid-connected side according to the distribution rule of harmonic frequency.
Description
Technical Field
The invention relates to the field of power quality analysis and signal analysis, in particular to a power grid state identification method based on an electric quantity frequency spectrum.
Background
With the increase of the permeability of the new energy in the power grid, the occupancy of the new energy power station is even equal to that of the traditional thermal power generation, but the input of the new energy can reduce the strength of the power grid; meanwhile, because of unbalanced distribution of natural resources, the strength of the power grid is weakened due to long-distance power transmission. In order to improve the remote power transmission capability, series compensation equipment is connected to the power transmission line to counteract the power grid. Thus, the line can be in weak power grid and series compensation state
Since the weak grid and the series compensation grid are two different grid states, the control adopted for the inverter control is also of different types. When the power grid is switched between two states, the stability margin of the grid-connected system also changes, so that the two states of the power grid need to be identified, and a control strategy is selected adaptively.
Currently, there is little research on pure grid state identification, more on grid impedance measurements, such as:
document 1 entitled "Alves D K, ribeiro R, costa F B, et al wavelet-Based Monitor for Grid Impedance Estimation of Three-Phase Networks", IEEE Transactions on Industrial Electronics,2020, PP (99): the article (wavelet-based three-phase grid impedance estimation, IEEE Transactions on Industrial Electronics,2020 network publication) estimates grid impedance by using real-time stationary discrete wavelet packet transforms associated with signal injection schemes when using wavelet coefficient energy analysis to detect grid impedance changes. Although this approach intermittently injects harmonics, it still affects the power quality of the grid.
Literature 2 entitled "on-line measurement of broadband grid impedance based on pseudo-random binary sequences" was published in the annual meeting of power electronics and electric drive in colleges and universities in 2017. The impedance of the power grid is measured by injecting harmonic waves, but the innovation of the method is that a novel dq axis orthogonal signal injection method is provided, and the amplitude of the harmonic waves of the power grid can be reduced to a certain extent on the basis of unchanged measurement precision, so that the electric energy quality during the harmonic wave injection period is effectively improved. Although this method can reduce the influence on the power quality of the power grid to a certain extent, the method is still an active measurement method
Document 3 entitled "harmonic analysis of electric power system based on synchronous extrusion transformation". Solar school report, article in 2021, 8 th year. The article proposes fourier synchronous extrusion transformation and synchronous extrusion wavelet transformation methods for harmonic analysis. The 2 methods respectively carry out time-frequency analysis on the power harmonic signals, synchronously squeeze and sharpen the harmonic instantaneous frequency to obtain a finer harmonic time-frequency curve, then decompose the power harmonic into a group of intra-modal class function components by utilizing the reversibility of the harmonic time-frequency curve, and finish the extraction of each component of the harmonic. The article only extracts the harmonics and does not perform subsequent state recognition analysis.
In combination with the above documents, the prior art has the following disadvantages:
1. the existing identification method mainly focuses on impedance measurement, and has little research on direct power grid state identification;
2. the existing method for identifying the state of the power grid through impedance is usually realized by injecting disturbance, which can influence the electric energy quality of the power grid, and meanwhile, the identification of a weak power grid and a series compensation power grid is rarely performed;
3. the existing state identification method is usually added with hardware peripherals, and the cost is increased. It is therefore necessary to study weak and series compensation grid identification methods based on passive measurements.
Disclosure of Invention
The invention provides a power grid state identification method based on an electric quantity frequency spectrum, which does not need to inject disturbance and add extra equipment, and only identifies a weak power grid and a series compensation power grid by measuring the self current harmonic wave of a PCC point, so that the next self-adaptive control of an inverter is performed, and the stability of a grid-connected system is improved.
The object of the present invention is thus achieved. The invention provides a power grid state identification method based on an electric quantity frequency spectrum, and a system applying the method comprises an inverter main circuit, a control unit, three-phase line impedance, an alternating-current side power grid and a power grid state identification unit; the inverter main circuit comprises a direct current power supply, a three-phase full-bridge inverter circuit and a three-phase LCL filter which are sequentially connected in series, the three-phase line impedance comprises a three-phase line inductance and a three-phase line capacitance, the alternating current side power comprises a three-phase power grid and a grounding module, and the power grid state identification unit comprises a state identification unit and a state output end; the output end of the inverter main circuit is connected with one end of three-phase line impedance, the connection point is a common coupling point PCC, the other end of the three-phase line impedance is connected with a three-phase power grid, and the other side of the three-phase power grid is connected with a grounding module; the input end of the control unit is connected with the PCC, the output end of the control unit is connected with a three-phase full-bridge inverter circuit in the inverter main circuit, the input end of the power grid state identification unit is connected with the PCC, and the output end of the power grid state identification unit is connected with the state output end;
the identification method identifies the power grid state by analyzing the distribution rule of the harmonic frequencies of the grid-connected current, and specifically comprises the following steps:
step 1, setting parameters
The fundamental frequency of the power grid is recorded as f g Sampling frequency f s Sampling is carried out according to the equal sampling interval tau in one power grid fundamental wave period, and the sampling is carried out for N times in the initial sampling, wherein N is a positive integer, and N=f s /f g ；
Selecting a frequency band including fundamental wave as frequency interval, dividing the frequency interval at 1Hz interval, simplifying the divided interval into N_Har frequency points, and marking any one of the N_Har frequency points as a frequency point Γ k Where k is a sequence number of n_har frequency points arranged in order of frequency values from small to large, k=1, 2, 3.
An array X, x= { X is introduced 1 ，x 2 ，...，x i ，...x N X, where x i For any element in the array, it is denoted as element x i I=1, 2,; setting the initial values of all elements in the array X to be 0;
step 2, initial sampling and calculation
At the frequency point Γ k The A-phase current output by the main circuit of the sampling inverter is N times to obtain N initial A-phase current sampling values I 01 ，I 02 ，...，I 0N Sampling value I of N initial A-phase current 01 ，I 02 ，...，I 0N Form an initial current value queue E 0 ，E 0 ＝{I 01 ，I 02 ，...，I 0N }；
Queue E of initial current values 0 The N initial A-phase current sampling values in the grid state identification unit are filled into an array X according to the arrangement sequence and are input into the grid state identification unit to be identified and subjected to discrete Fourier transformation to obtain a frequency point Γ k Cosine component and frequency point Γ k The sine component at this point, and is denoted as the initial cosine component A k0 And an initial sinusoidal component B k0 The discrete fourier transform formula is:
step 3, recursive sampling and recursive computation
Step 3.1, giving the simulation time length T m And recursively sampling N in the simulation time according to the equal sampling interval tau c Secondary, N c Is a positive integer, N c ＝T m /τ；
After the initial sampling in step 2 is completed, the 1 st recursive sampling and calculation are performed at intervals of a sampling interval τ, specifically, at a frequency point Γ k The A-phase current output by the main circuit of the sampling inverter is 1 time to obtain a 1 st recursion A-phase current sampling value I A1 Sampling value I of the 1 st recursion A phase current A1 And an initial current value queue E 0 The 2 nd to the N th initial A-phase current sampling values are combined, and the 1 st recursion A-phase current sampling value I A1 For the tail of the queue, a 1 st recursion current value queue E consisting of N A-phase current sampling values is formed 1 ，E 1 ＝{I 02 ，I 03 ，...，I 0N+1 }, wherein I 0N+1 ＝I A1 The method comprises the steps of carrying out a first treatment on the surface of the Queue E the 1 st recursion current value 1 The N A-phase current sampling values in the array X are filled in the array X according to the arrangement sequence, and the 1 st recursive sampling time frequency point Γ is obtained according to a recursive formula k Cosine component at and 1 st recursive sampling time frequency point Γ k The sine components at the positions are respectively marked as cosine components A at the 1 st recursion sampling moment k1 And sinusoidal component B at 1 st recursive sampling instant k1 ；
After the 1 st recursive sampling is completed, the 2 nd recursive sampling and calculation are performed at intervals of one sampling interval tau, specifically, at a frequency point gamma k The A-phase current output by the main circuit of the sampling inverter is 1 time to obtain a 2 nd recursive A-phase current sampling value I A2 Sampling value I of the phase A current of the 2 nd recursion A2 And a 1 st recursive current value queue E 1 The 2 nd to N th A phase current sampling values are combined, and the 2 nd recursive A phase current sampling value I A2 For the tail of the queue, a 2 nd recursion current value queue E consisting of N A-phase current sampling values is formed 2 Queuing the 2 nd recursive current value E 2 The N A-phase current sampling values in the array X are filled in the array X according to the arrangement sequence, and the frequency point gamma of the 2 nd recursive sampling time is obtained according to a recursive formula k Cosine component at and frequency point Γ at the 2 nd recursive sampling time k The sine components at the positions are respectively marked as cosine components A at the 2 nd recursive sampling time k2 And sinusoidal component B at the 2 nd recursive sampling time k2 ；
And so on, obtaining an nth recursion A-phase current sampling value I by nth recursion sampling An And an nth recursive current value queue E consisting of N A-phase current sample values n N is N c Any one of the sub-recursive samplings, n=1, 2,.. c The method comprises the steps of carrying out a first treatment on the surface of the Queuing the nth recursive current value E n The N A-phase current sampling values in the array X are filled in the array X according to the arrangement sequence, and the frequency point gamma of the nth recursive sampling time is obtained according to a recursive formula k Cosine component at and nth recursive sampling time frequency point Γ k The sine component at the position is respectively recorded as the cosine component A of the current moment kn And a current moment sinusoidal component B kn ；
The expression of the recursive formula is as follows:
wherein A 'is' k Cosine obtained for last sampling time of current timeComponent, B' k The sinusoidal component obtained for the last sampling time of the current time is specifically:
when n=1, a' k ＝A k0 ，B′ k ＝B k0 ；
When n > 1, A' k ＝A kn-1 I.e. the cosine component obtained at the n-1 th recursion sampling instant, B' k ＝B kn-1 The sinusoidal component is obtained at the n-1 th recursion sampling time;
step 3.2, sampling every other sampling interval tau once in the simulation duration according to the method of step 3.1, and performing a recursive calculation to obtain the Nth sample c The cosine component and the sine component of the subsampled moment are respectively marked as an emulated cosine component A k And a simulated sinusoidal component B k ；
The A phase current is at the frequency point gamma k The harmonic amplitude at this point is noted as harmonic amplitude amp_i k ，
Step 4, searching a low-frequency harmonic peak value g and a high-frequency harmonic peak value h
Substituting k=1, 2,3, and performing calculation by substituting n_har into the step 2 and the step 3 respectively to obtain harmonic amplitude amp_i corresponding to n_har frequency points k Harmonic amplitude Amp_I corresponding to the N_Har frequency points k Constitutes a harmonic amplitude sequence amp_i, amp_i= { amp_i 1 ，Amp_I 2 ，...Amp_I k ，...，Amp_I N_Har }；
Dividing the harmonic amplitude sequence Amp_I into a harmonic amplitude section with k less than 50 and a harmonic amplitude section with k more than or equal to 50, and taking the harmonic amplitude Amp_I from the harmonic amplitude section with k less than 50 k The maximum value of the low frequency maximum value Amp_I is recorded as g Wherein g is the maximum value Amp_I of the low frequency g The corresponding frequency value is recorded as a low-frequency harmonic peak value g; in a harmonic amplitude section with k more than or equal to 50, taking harmonic amplitude Amp_I k The maximum value of the high frequency maximum value Amp_I is recorded as h Wherein h is the maximum value Amp_I of the high frequency h The corresponding frequency value is used to determine the frequency value,the high-frequency harmonic peak value h is marked;
step 5, identification of the grid state
Setting a threshold epsilon, setting a first constant a, a second constant b, a third constant c and a fourth constant d, and setting [ a, b ] as characteristic frequency bands of a series compensation power grid, and [ c, d ] as characteristic frequency bands of a weak power grid;
judging whether the frequencies of the low-frequency harmonic peak value g and the high-frequency harmonic peak value h are in a characteristic frequency band or not, and judging whether the harmonic amplitude reaches a given threshold epsilon or not, wherein the specific judgment is as follows:
when a is not less than g and not less than b and Amp_I g /Amp_I 50 When epsilon is more than epsilon, the power grid state at the moment is considered as a series compensation power grid, and a state Flag bit flag=2 is output; wherein, amp_I 50 Amplitude Amp_I for fundamental wave 50 ；
When c is less than or equal to h is less than or equal to d and Amp_I h /Amp_I 50 When epsilon is more than epsilon, the current grid state is determined to be a weak current grid, and a state Flag bit flag=1 is output;
the state output end in the power grid state identification unit outputs a state flag bit F1ag, and identification is finished.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the identification method, disturbance is not required to be injected, and the weak power grid and the series compensation power grid are identified only by measuring the current harmonic wave of the PCC point, so that the inverter self-adaption control of the next step is further carried out, and the stability of a grid-connected system is improved;
2. according to the identification method, the power grid state can be judged only by analyzing the current waveform of the PCC point without analyzing the waveform of the voltage and judging the current harmonic distribution condition;
3. the identification method is improved only by the method, and does not need to increase peripheral hardware equipment or hardware cost.
Drawings
FIG. 1 is a diagram of a system architecture to which the identification method of the present invention is applied.
Fig. 2 is a waveform of identification of a strong grid-weak grid-series compensation grid in an embodiment of the invention.
Fig. 3 is a waveform of identification of a series compensation grid, a weak grid, and a strong grid in an embodiment of the present invention.
Detailed Description
The present embodiment will be described in detail with reference to the accompanying drawings.
Fig. 1 is a system structural diagram of a system to which the identification method of the present invention is applied, and as can be seen from fig. 1, the system to which the method is applied includes an inverter main circuit 10, a control unit 20, a three-phase line impedance 30, an ac-side power grid 40, and a grid state identification unit 50. The inverter main circuit 10 includes a dc power supply, a three-phase full-bridge inverter circuit, and a three-phase LCL filter sequentially connected in series, the three-phase line impedance 30 includes a three-phase line inductance and a three-phase line capacitance, the ac side power grid 40 includes a three-phase power grid and a grounding module, and the power grid state identification unit 50 includes a state identification unit and a state output terminal. An output end of the inverter main circuit 10 is connected with one end of the three-phase line impedance 30, a connection point of the inverter main circuit is a PCC, the other end of the three-phase line impedance 30 is connected to a three-phase power grid, and the other side of the three-phase power grid is connected to a grounding module. The input end of the control unit 20 is connected to the PCC, the output end is connected to the three-phase full-bridge inverter circuit in the main inverter circuit 10, and the input end of the grid state identification unit 50 is connected to the PCC, and the output end is connected to the state output end.
In FIG. 1, L 1 、L 2 Is a filter inductance and C in a three-phase LCL filter f Is the filter capacitance in the three-phase LCL filter, L g Line inductance, C, in three-phase line impedance g Is a line capacitance, grid is a three-phase power Grid, V dc Is the dc side voltage at the dc power supply.
The main circuit parameters in this embodiment are: v (V) dc =770V, the rated output line voltage of the inverter is 380V/50Hz, the rated power of the inverter is 20kW, the filter inductance L 1 The value of (2) is 1.832mH, and the filter inductance L 2 Has a value of 0.7mH, filter capacitor C f The value of (2) is 16.4uF/1.5 omega, and the line inductance L is high when the power grid is strong g The value of (2) is 4.6mH, and the line inductance L is low in the power grid g The value of (2) is 7mH, and the line capacitance C is used for series compensation of the power grid g The value of (2) was 16.4uF.
The invention provides a power grid state identification method based on an electric quantity frequency spectrum, which is used for identifying the power grid state by analyzing the distribution rule of harmonic frequencies of grid-connected current, and specifically comprises the following steps:
step 1, setting parameters
The fundamental frequency of the power grid is recorded as f g Sampling frequency f s Sampling is carried out according to the equal sampling interval tau in one power grid fundamental wave period, the sampling is carried out for N times, N is a positive integer, and N=f s /f g ；
Selecting a frequency band including fundamental wave as frequency interval, dividing the frequency interval at 1Hz interval, simplifying the divided interval into N_Har frequency points, and marking any one of the N_Har frequency points as a frequency point Γ k Where k is a sequence number of n_har frequency points arranged in order of frequency values from small to large, k=1, 2, 3.
An array X, x= { X is introduced 1 ，x 2 ，...，x i ，...x N X, where x i For any element in the array, it is denoted as element x i I=1, 2,; the initial values of all elements in array X are set to 0.
In this embodiment, n=150, n_har=50.
Step 2, initial sampling and calculation
At the frequency point Γ k The A-phase current output by the main circuit 10 of the sampling inverter is N times to obtain N initial A-phase current sampling values I 01 ，I 02 ，...，I 0N Sampling value I of N initial A-phase current 01 ，I 02 ，...，I 0N Form an initial current value queue E 0 ，E 0 ＝{I 01 ，I 02 ，...，I 0N }；
Queue E of initial current values 0 The N initial A-phase current sampling values in the grid state identification unit 50 are filled into an array X according to the arrangement sequence and are input into the grid state identification unit to be identified and discrete Fourier transformed to obtain a frequency point Γ k Cosine component and frequency point Γ k The sine component at this point, and is denoted as the initial cosine component A k0 And an initial sinusoidal component B k0 The discrete fourier transform formula is:
step 3, recursive sampling and recursive computation
Step 3.1, giving the simulation time length T m And recursively sampling N in the simulation time according to the equal sampling interval tau c Secondary, N c Is a positive integer, N c ＝T m /τ；
After the initial sampling in step 2 is completed, the 1 st recursive sampling and calculation are performed at intervals of a sampling interval τ, specifically, at a frequency point Γ k The A-phase current output by the sampling inverter main circuit 10 is 1 time to obtain a 1 st recursion A-phase current sampling value I A1 Sampling value I of the 1 st recursion A phase current A1 And an initial current value queue E 0 The 2 nd to the N th initial A-phase current sampling values are combined, and the 1 st recursion A-phase current sampling value I A1 For the tail of the queue, a 1 st recursion current value queue E consisting of N A-phase current sampling values is formed 1 ，E 1 ＝{I 02 ，I 03 ，...，I 0N+1 }, wherein I 0N+1 ＝I A1 The method comprises the steps of carrying out a first treatment on the surface of the Queue E the 1 st recursion current value 1 The N A-phase current sampling values in the array X are filled in the array X according to the arrangement sequence, and the 1 st recursive sampling time frequency point Γ is obtained according to a recursive formula k Cosine component at and 1 st recursive sampling time frequency point Γ k The sine components at the positions are respectively marked as cosine components A at the 1 st recursion sampling moment k1 And sinusoidal component B at 1 st recursive sampling instant k1 ；
After the 1 st recursive sampling is completed, the 2 nd recursive sampling and calculation are performed at intervals of one sampling interval tau, specifically, at a frequency point gamma k The A-phase current output by the sampling inverter main circuit 10 is 1 time to obtain a 2 nd recursive A-phase current sampling value I A2 Sampling the 2 nd recursive A-phase currentValue I A2 And a 1 st recursive current value queue E 1 The 2 nd to N th A phase current sampling values are combined, and the 2 nd recursive A phase current sampling value I A2 For the tail of the queue, a 2 nd recursion current value queue E consisting of N A-phase current sampling values is formed 2 Queuing the 2 nd recursive current value E 2 The N A-phase current sampling values in the array X are filled in the array X according to the arrangement sequence, and the frequency point gamma of the 2 nd recursive sampling time is obtained according to a recursive formula k Cosine component at and frequency point Γ at the 2 nd recursive sampling time k The sine components at the positions are respectively marked as cosine components A at the 2 nd recursive sampling time k2 And sinusoidal component B at the 2 nd recursive sampling time k2 ；
And so on, obtaining an nth recursion A-phase current sampling value I by nth recursion sampling An And an nth recursive current value queue E consisting of N A-phase current sample values n N is N c Any one of the sub-recursive samplings, n=1, 2,.. c The method comprises the steps of carrying out a first treatment on the surface of the Queuing the nth recursive current value E n The N A-phase current sampling values in the array X are filled in the array X according to the arrangement sequence, and the frequency point gamma of the nth recursive sampling time is obtained according to a recursive formula k Cosine component at and nth recursive sampling time frequency point Γ k The sine component at the position is respectively recorded as the cosine component A of the current moment kn And a current moment sinusoidal component B kn ；
The expression of the recursive formula is as follows:
wherein A 'is' k For the cosine component obtained at the last sampling time of the current time, B' k The sinusoidal component obtained for the last sampling time of the current time is specifically:
when n=1, a' k ＝A k0 ，B′ k ＝B k0 ；
When n > 1, A' k ＝A kn-1 I.e. the nth-1 recursive miningCosine component obtained at sample time, B' k ＝B kn-1 The sinusoidal component is obtained at the n-1 th recursion sampling time;
step 3.2, sampling every other sampling interval tau once in the simulation duration according to the method of step 3.1, and performing a recursive calculation to obtain the Nth sample c The cosine component and the sine component of the subsampled moment are respectively marked as an emulated cosine component A k And a simulated sinusoidal component B k ；
The A phase current is at the frequency point gamma k The harmonic amplitude at this point is noted as harmonic amplitude amp_i k ，
Step 4, searching a low-frequency harmonic peak value g and a high-frequency harmonic peak value h
Substituting k=1, 2,3, and performing calculation by substituting n_har into the step 2 and the step 3 respectively to obtain harmonic amplitude amp_i corresponding to n_har frequency points k Harmonic amplitude Amp_I corresponding to the N_Har frequency points k Constitutes a harmonic amplitude sequence amp_i, amp_i= { amp_i 1 ，Amp_I 2 ，...Amp_I k ，...，Amp_I N_Har }；
Dividing the harmonic amplitude sequence Amp_I into a harmonic amplitude section with k less than 50 and a harmonic amplitude section with k more than or equal to 50, and taking the harmonic amplitude Amp_I from the harmonic amplitude section with k less than 50 k The maximum value of the low frequency maximum value Amp_I is recorded as g Wherein g is the maximum value Amp_I of the low frequency g The corresponding frequency value is recorded as a low-frequency harmonic peak value g; in a harmonic amplitude section with k more than or equal to 50, taking harmonic amplitude Amp_I k The maximum value of the high frequency maximum value Amp_I is recorded as h Wherein h is the maximum value Amp_I of the high frequency h The corresponding frequency value is marked as a high-frequency harmonic peak value h;
step 5, identification of the grid state
Setting a threshold epsilon, setting a first constant a, a second constant b, a third constant c and a fourth constant d, and setting [ a, b ] as characteristic frequency bands of a series compensation power grid, and [ c, d ] as characteristic frequency bands of a weak power grid;
judging whether the frequencies of the low-frequency harmonic peak value g and the high-frequency harmonic peak value h are in a characteristic frequency band or not, and judging whether the harmonic amplitude reaches a given threshold epsilon or not, wherein the specific judgment is as follows:
when a is not less than g and not less than b and Amp_I g /Amp_I 50 When epsilon is more than epsilon, the power grid state at the moment is considered as a series compensation power grid, and a state Flag bit flag=2 is output; wherein, amp_I 50 Amplitude Amp_I for fundamental wave 50 ；
When c is less than or equal to h is less than or equal to d and Amp_I h /Amp_I 50 When epsilon is more than epsilon, the current grid state is determined to be a weak current grid, and a state Flag bit flag=1 is output;
the status output terminal in the grid status identifying unit 50 outputs the status Flag bit Flag, and the identification is ended.
In this embodiment, a=1, b=15, c=110, d=140, and ε=0.00167.
Fig. 2 is a waveform of an identification result of the embodiment of the present invention from a strong power grid to a weak power grid and then to a series compensation power grid. The system is slowly started up to be completed at 1.6s, and is in a strong power grid state at the moment; when the power grid is changed into a weak power grid in 3s, judging that the amplitude meeting the condition exists in the (110 Hz,140 Hz) characteristic frequency band after the transition time is 0.2s, and identifying the Flag as the weak power grid as flag=1; and when the time is 5s, the power grid is changed into a series compensation power grid from a weak power grid, the amplitude which accords with the condition in the characteristic frequency band (1 Hz,15 Hz) is judged through the transition time of 0.6s, and the Flag is flag=2, so that the series compensation power grid is identified.
Fig. 3 is a waveform of an identification result of the embodiment of the present invention from the series compensation power grid to the weak power grid and then to the strong power grid. As can be seen from the graph, after the slow start is completed at 1.6s, the series compensation power grid is identified, and the Flag bit flag=2; when 5s, the power grid is changed into a weak power grid, the amplitude meeting the condition in the (110 Hz,140 Hz) characteristic frequency band is judged through the transition time of 0.6s, and the Flag bit flag=1 is identified as the weak power grid; and when 8s, the power grid is changed from a weak power grid to a strong power grid, the amplitude which does not meet the condition in the characteristic frequency bands (1 Hz,15 Hz), (110 Hz and 140 Hz) is judged through the transition time of 0.9s, and the flag=0 is identified as the strong power grid.
Figures 2 and 3 prove that the invention can accurately identify the weak power grid and the series compensation power grid.
Claims (1)
1. A power grid state identification method based on an electric quantity frequency spectrum, wherein a system applying the method comprises an inverter main circuit (10), a control unit (20), three-phase line impedance (30), an alternating current side power grid (40) and a power grid state identification unit (50); the inverter main circuit (10) comprises a direct current power supply, a three-phase full-bridge inverter circuit and a three-phase LCL filter which are sequentially connected in series, the three-phase line impedance (30) comprises a three-phase line inductance and a three-phase line capacitance, the alternating current side power grid (40) comprises a three-phase power grid and a grounding module, and the power grid state identification unit (50) comprises a state identification unit and a state output end; the output end of the inverter main circuit (10) is connected with one end of the three-phase line impedance (30), the connecting point is a common coupling point PCC, the other end of the three-phase line impedance (30) is connected with a three-phase power grid, and the other side of the three-phase power grid is connected with a grounding module; the input end of the control unit (20) is connected with the PCC, the output end of the control unit is connected with a three-phase full-bridge inverter circuit in the inverter main circuit (10), the input end of the power grid state identification unit (50) is connected with the PCC, and the output end of the power grid state identification unit is connected with the state output end;
the identification method is characterized in that the grid state is identified by analyzing the grid-connected current harmonic frequency distribution rule, and specifically, the identification method comprises the following steps:
step 1, setting parameters
The fundamental frequency of the power grid is recorded as f g Sampling frequency f s Sampling is carried out according to the equal sampling interval tau in one power grid fundamental wave period, and the sampling is carried out for N times in the initial sampling, wherein N is a positive integer, and N=f s /f g ；
Selecting a frequency band including fundamental wave as frequency interval, dividing the frequency interval at 1Hz interval, simplifying the divided interval into N_Har frequency points, and marking any one of the N_Har frequency points as a frequency point Γ k Where k is a sequence number of n_har frequency points arranged in order of frequency values from small to large, k=1, 2, 3.
Introducing arraysX，X＝{x 1 ，x 2 ，...，x i ，...x N X, where x i For any element in the array, it is denoted as element x i I=1, 2,; setting the initial values of all elements in the array X to be 0;
step 2, initial sampling and calculation
At the frequency point Γ k The A-phase current output by the main circuit (10) of the sampling inverter is N times to obtain N initial A-phase current sampling values I 01 ，I 02 ，...，I 0N Sampling value I of N initial A-phase current 01 ，I 02 ，...，I 0N Form an initial current value queue E 0 ，E 0 ＝{I 01 ，I 02 ，...，I 0N }；
Queue E of initial current values 0 N initial A-phase current sampling values in the grid state identification unit (50) are filled into an array X according to the arrangement sequence and are input into the grid state identification unit to be identified and discrete Fourier transformed to obtain a frequency point Γ k Cosine component and frequency point Γ k The sine component at this point, and is denoted as the initial cosine component A k0 And an initial sinusoidal component B k0 The discrete fourier transform formula is:
step 3, recursive sampling and recursive computation
Step 3.1, giving the simulation time length T m And recursively sampling N in the simulation time according to the equal sampling interval tau c Secondary, N c Is a positive integer, N c ＝T m /τ；
After the initial sampling in step 2 is completed, the 1 st recursive sampling and calculation are performed at intervals of a sampling interval τ, specifically, at a frequency point Γ k The A-phase current output by the sampling inverter main circuit (10) is 1 time to obtain a 1 st recursion A-phase current sampling value I A1 Sampling value I of the 1 st recursion A phase current A1 And an initial current value queue E 0 The 2 nd to the N th initial A-phase current sampling values are combined, and the 1 st recursion A-phase current sampling value I A1 For the tail of the queue, a 1 st recursion current value queue E consisting of N A-phase current sampling values is formed 1 ，E 1 ＝{I 02 ，I 03 ，...，I 0N+1 }, wherein I 0N+1 ＝I A1 The method comprises the steps of carrying out a first treatment on the surface of the Queue E the 1 st recursion current value 1 The N A-phase current sampling values in the array X are filled in the array X according to the arrangement sequence, and the 1 st recursive sampling time frequency point Γ is obtained according to a recursive formula k Cosine component at and 1 st recursive sampling time frequency point Γ k The sine components at the positions are respectively marked as cosine components A at the 1 st recursion sampling moment k1 And sinusoidal component B at 1 st recursive sampling instant k1 ；
After the 1 st recursive sampling is completed, the 2 nd recursive sampling and calculation are performed at intervals of one sampling interval tau, specifically, at a frequency point gamma k The A-phase current output by the sampling inverter main circuit (10) is 1 time to obtain a 2 nd recursive A-phase current sampling value I A2 Sampling value I of the phase A current of the 2 nd recursion A2 And a 1 st recursive current value queue E 1 The 2 nd to N th A phase current sampling values are combined, and the 2 nd recursive A phase current sampling value I A2 For the tail of the queue, a 2 nd recursion current value queue E consisting of N A-phase current sampling values is formed 2 Queuing the 2 nd recursive current value E 2 The N A-phase current sampling values in the array X are filled in the array X according to the arrangement sequence, and the frequency point gamma of the 2 nd recursive sampling time is obtained according to a recursive formula k Cosine component at and frequency point Γ at the 2 nd recursive sampling time k The sine components at the positions are respectively marked as cosine components A at the 2 nd recursive sampling time k2 And sinusoidal component B at the 2 nd recursive sampling time k2 ；
And so on, obtaining an nth recursion A-phase current sampling value I by nth recursion sampling An And an nth recursive current value queue E consisting of N A-phase current sample values n N is N c Any one of the sub-recursive samplings, n=1, 2,.. c The method comprises the steps of carrying out a first treatment on the surface of the Queuing the nth recursive current valueColumn E n The N A-phase current sampling values in the array X are filled in the array X according to the arrangement sequence, and the frequency point gamma of the nth recursive sampling time is obtained according to a recursive formula k Cosine component at and nth recursive sampling time frequency point Γ k The sine component at the position is respectively recorded as the cosine component A of the current moment kn And a current moment sinusoidal component B kn ；
The expression of the recursive formula is as follows:
wherein A 'is' k For the cosine component obtained at the last sampling time of the current time, B' k The sinusoidal component obtained for the last sampling time of the current time is specifically:
when n=1, a' k ＝A k0 ，B′ k ＝B k0 ；
When n > 1, A' k ＝A kn-1 I.e. the cosine component obtained at the n-1 th recursion sampling instant, B' k ＝B kn-1 The sinusoidal component is obtained at the n-1 th recursion sampling time;
step 3.2, sampling every other sampling interval tau once in the simulation duration according to the method of step 3.1, and performing a recursive calculation to obtain the Nth sample c The cosine component and the sine component of the subsampled moment are respectively marked as an emulated cosine component A k And a simulated sinusoidal component B k ；
The A phase current is at the frequency point gamma k The harmonic amplitude at this point is noted as harmonic amplitude amp_i k ，
Step 4, searching a low-frequency harmonic peak value g and a high-frequency harmonic peak value h
Substituting k=1, 2,3, and performing calculation by substituting n_har into the step 2 and the step 3 respectively to obtain harmonic amplitude amp_i corresponding to n_har frequency points k The N isHarmonic amplitude Amp_I corresponding to_Har frequency points k Constitutes a harmonic amplitude sequence amp_i, amp_i= { amp_i 1 ，Amp_I 2 ，...Amp_I k ，...，Amp_I N_Har }；
Dividing the harmonic amplitude sequence Amp_I into a harmonic amplitude section with k less than 50 and a harmonic amplitude section with k more than or equal to 50, and taking the harmonic amplitude Amp_I from the harmonic amplitude section with k less than 50 k The maximum value of the low frequency maximum value Amp_I is recorded as g Wherein g is the maximum value Amp_I of the low frequency g The corresponding frequency value is recorded as a low-frequency harmonic peak value g; in a harmonic amplitude section with k more than or equal to 50, taking harmonic amplitude Amp_I k The maximum value of the high frequency maximum value Amp_I is recorded as h Wherein h is the maximum value Amp_I of the high frequency h The corresponding frequency value is marked as a high-frequency harmonic peak value h;
step 5, identification of the grid state
Setting a threshold epsilon, setting a first constant a, a second constant b, a third constant c and a fourth constant d, and setting [ a, b ] as characteristic frequency bands of a series compensation power grid, and [ c, d ] as characteristic frequency bands of a weak power grid;
judging whether the frequencies of the low-frequency harmonic peak value g and the high-frequency harmonic peak value h are in a characteristic frequency band or not, and judging whether the harmonic amplitude reaches a given threshold epsilon or not, wherein the specific judgment is as follows:
when a is not less than g and not less than b and Amp_I g /Amp_I 50 When epsilon is more than epsilon, the power grid state at the moment is considered as a series compensation power grid, and a state Flag bit flag=2 is output; wherein, amp_I 50 Amplitude Amp_I for fundamental wave 50 ；
When c is less than or equal to h is less than or equal to d and Amp_I h /Amp_I 50 When epsilon is more than epsilon, the current grid state is determined to be a weak current grid, and a state Flag bit flag=1 is output;
the state output end in the power grid state identification unit (50) outputs a state Flag bit Flag, and identification is finished.
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