CN110618314B - Harmonic wave responsibility division method for resisting short-circuit fault interference of power distribution system - Google Patents
Harmonic wave responsibility division method for resisting short-circuit fault interference of power distribution system Download PDFInfo
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Abstract
The invention discloses a power distribution network harmonic responsibility division method for resisting short-circuit fault interference. By establishing a distribution network distributed multi-harmonic source harmonic responsibility division model, equivalent harmonic transmission impedance between a harmonic source and a concerned node and background harmonic voltage at the concerned node can be calculated, and harmonic voltage component projection calculation is further utilized to obtain harmonic responsibility of each harmonic source at the concerned node. The responsibility of each harmonic source at each concerned node can be effectively divided according to three-phase voltage and current data measured by each common connection point and the concerned node.
Description
Technical Field
The invention belongs to the field of harmonic responsibility division, and relates to a harmonic responsibility division method for resisting short-circuit fault interference of a power distribution system.
Background
In an electric power system, three-phase voltage and current waveforms are ideally standard sine waves with a frequency of 50 Hz. Along with the rapid development of science and technology and economy, more and more novel load and power access distribution system, novel load and power contain power electronic transformation device mostly, because power electronic transformation device can produce wave form distortion transmission harmonic, consequently harmonic pollution is more serious in the past in the current distribution system. Harmonic waves can aggravate temperature rise, electrical element aging is accelerated, the service life of electrical equipment is shortened, even the interference protection device correctly acts to cause huge influence on the operation safety and economy of a power grid, harmonic wave responsibility division is the premise and important guarantee for effectively governing the harmonic waves, effective punishment bases can be provided, and disputes are reduced.
At present, research on harmonic responsibility division has been explored a lot of benefits, and a 'non-intervention' method is convenient for engineering application due to no interference to a power grid, and becomes a mainstream method. The non-intervention method mainly comprises a fluctuation quantity method, a linear regression method, a blind source separation method and a statistical probability method. The principle of the fluctuation quantity method is to estimate the harmonic impedance of the system side by utilizing the natural fluctuation of the current and voltage of a Point of Common Coupling (PCC), further calculate the harmonic voltage component caused by the PCC at the load side and the system side respectively, and calculate the harmonic responsibility through projection. The principle of the linear regression method is that a multiple linear regression model is established by dividing the harmonic voltage of the concerned node into a plurality of components, the linear regression method is used for calculating regression coefficients and equivalent to harmonic impedance and background harmonic voltage, and finally the harmonic responsibility is calculated by using the harmonic voltage projection. According to the principle of the blind source separation method, harmonic responsibility is divided into equivalent parts to a blind source separation problem, components corresponding to harmonic currents of each harmonic source are extracted from harmonic voltages of the concerned nodes, then a demixing matrix is obtained through calculation, and finally the harmonic responsibility of each harmonic source is calculated through the demixing matrix. The principle of the statistical probability method is to extract the harmonic impedance of the system side and calculate the harmonic responsibility by utilizing the mathematical relationship between statistics and probability.
However, harmonic responsibility division researches are about harmonic responsibility attribution problems under a steady state condition, and a short-circuit fault interferes with a harmonic emission level of a harmonic source to influence harmonic responsibility division accuracy, so that interference of a power grid short-circuit fault needs to be eliminated in harmonic responsibility division, and the harmonic responsibility division is not involved in previous researches, so that a harmonic responsibility division method for resisting short-circuit fault interference of a power distribution system is urgently needed to be provided.
Disclosure of Invention
In order to solve the technical problems, the invention provides a harmonic responsibility division method for resisting short-circuit fault interference of a power distribution system, which can divide harmonic responsibility of each harmonic source of the power distribution system at an attention node by using three-phase voltage and current data measured by each public connection point and the attention node, and can eliminate the interference of the power grid short-circuit fault.
The technical scheme of the invention is as follows:
a harmonic responsibility division method for resisting short-circuit fault interference of a power distribution system comprises the following steps:
step 1: acquiring interference characteristics of various types of short-circuit faults on fundamental wave monitoring data of each public connection point of the power distribution network;
step 2: obtaining interference characteristic data identification and elimination processes of each common connection point and each subharmonic of the concerned node based on the interference characteristics;
and step 3: establishing a distributed multi-harmonic source harmonic responsibility division model of the power distribution network;
and 4, step 4: obtaining equivalent harmonic transmission impedance between each harmonic source and the concerned node and background harmonic voltage at the concerned node;
and 5: and dividing each harmonic source into respective harmonic responsibilities at the concerned node by utilizing harmonic voltage vector projection.
Further, the various types of short-circuit faults described in step 1 include: single-phase ground faults, two-phase short-circuit faults, two-phase ground faults, and three-phase ground faults; and the interference characteristics of the two-phase short-circuit fault, the two-phase earth fault and the three-phase earth fault on the fundamental wave monitoring data of the common connection point are obtained according to the interference time limit, and the interference characteristics of the single-phase earth fault on the fundamental wave monitoring data of the common connection point are obtained according to the three-phase voltage amplitude variation relation when the single-phase earth fault occurs.
The interference characteristic of the fundamental wave monitoring data in the step 1 is sudden change of fundamental wave voltage.
Further, the step 2 comprises the following steps:
step 2.1: calculating wavelet coefficients and thresholds of data points in the fundamental voltage data segment, starting to detect whether the wavelet coefficients of the data points exceed the thresholds from the first data point, and if the wavelet coefficients of the data points exceed the thresholds, considering that mutation occurs, and entering step 2.2;
step 2.2: recording data point labels from the beginning of mutation, continuously detecting wavelet coefficients, considering that the mutation process is finished when the wavelet coefficients are smaller than a threshold value, comparing data before and after mutation, considering that the harmonic source state has mutation if the variation reaches +/-10%, and entering step 2.3; otherwise, the data points are considered to belong to the interference of the abnormal data points, the data point labels are stopped being recorded until the mutation is finished, and the data of the recorded labels are removed;
step 2.3: continuously detecting the wavelet coefficients, if sudden change is detected again within 1 second, stopping recording the data point labels until the sudden change is finished, considering that faults that two-phase short circuits, two-phase grounding and three-phase short circuits can be quickly cut off occur, and removing corresponding labeled harmonic data; if the sudden change is detected again more than 1 second or the sudden change is not detected again until the last data point, stopping recording the data point labels, considering that the single-phase earth fault or the change of the running state occurs, and then entering the step 2.4;
step 2.4: comparing the three-phase data before and after the first mutation, if the difference between the two phases is small, the two phases are increased, then the single-phase earth fault is considered to occur, and the harmonic data of the record label is removed; otherwise, normal switching of the load state is considered to occur, data is reserved, and the fault data elimination is completed.
The calculation process of the wavelet coefficients comprises the following steps: determining a scale function, calculating the wavelet coefficient according to the scale function, normalizing the wavelet coefficient, and calculating the standard deviation of the wavelet coefficient.
The threshold value is calculated by adopting a global threshold value.
Further, the step 3 comprises the following steps: each harmonic source is connected to a power distribution network through different nodes, each subharmonic voltage of each node is generated by the combined action of each harmonic source, monitoring devices are arranged on each harmonic source load node and the concerned node, fundamental waves and each subharmonic current and voltage are measured, unknown harmonic components in the system are represented by background harmonics, and a multi-pc model of the multi-target node is established.
Further, the step 4 comprises the following steps: and calculating the coefficients of a regression model, namely equivalent harmonic transfer impedances between each harmonic source and the concerned node and background harmonic voltages at the concerned node by using a multi-dependent variable form complex field partial least square method.
Further, the step 5 comprises the following steps: and calculating h-order harmonic duty ratio indexes of the harmonic source loads and the background harmonics at the concerned nodes according to h-order harmonic voltage amplitude and phase angle of each harmonic source load at each node and h-order background harmonic voltage amplitude and phase angle of each concerned node.
Compared with the prior art, the invention has the beneficial effects that:
(1) the fault occurrence time interval can be identified according to three-phase voltage and current data obtained by measuring each public coupling point and the attention node in the system, and harmonic data of the time interval corresponding to each public coupling point and the attention node are removed based on a mutation detection algorithm;
(2) the harmonic responsibility of the power distribution system can be divided by resisting fault interference only based on three-phase voltage and current data measured by each public coupling point and the concerned node, and the method is simple and practical.
(3) According to the harmonic contribution, a quantitative standard is provided for the identification of the main harmonic source, and the position of the main harmonic source can be quickly and accurately identified.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application.
Fig. 1 is a flow chart of the identification and elimination of harmonic data affected by fault interference according to the present invention.
FIG. 2 is a diagram of a distributed multi-harmonic source model according to the present invention.
Fig. 3 is a schematic diagram of harmonic responsibility division provided by the present invention.
Fig. 4 is a topological diagram of the research system provided by the present invention.
Fig. 5 is a diagram illustrating the screening effect of fault data.
FIG. 6 is a harmonic responsibility comparison chart of harmonic sources calculated by the present invention and calculated by the robust regression method when various short-circuit faults occur.
Fig. 7 is a flowchart of a harmonic responsibility division method for resisting short-circuit fault interference of a power distribution system provided by the invention.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
As introduced in the background art, the harmonic responsibility division method in the prior art has the defect that the accuracy of harmonic responsibility division is affected due to the fact that steady-state harmonic data interfered by a short-circuit fault cannot be identified in the harmonic responsibility division method.
As shown in fig. 7, the method mainly comprises the following steps: analyzing the interference characteristics of the short-circuit fault in the power distribution network on the fundamental wave monitoring data of the common connection point; providing a fault interference data identification and elimination process of each harmonic based on fault interference characteristics; establishing a distributed multi-harmonic source harmonic responsibility division model of the power distribution network; calculating to obtain equivalent harmonic transfer impedances of each order between a harmonic source and the concerned node and background harmonic voltages of each order at the concerned node; and then, the harmonic voltage component projection calculation is utilized to obtain the harmonic responsibility of each harmonic source at the concerned node.
1. And analyzing the characteristics of the fundamental wave monitoring data of each public connection point of the power distribution network, which are interfered by various types of short-circuit faults.
Assuming that a relay protection device in a power grid reliably acts, three faults except a single-phase earth fault can be reliably removed within 1 second, and the time scale is smaller than other steady-state disturbances such as system operation mode change, load input and exit and the like. Therefore, two-phase short-circuit faults, two-phase ground faults and three-phase short-circuit faults can be selected according to the interference time limit. The distribution network usually adopts a neutral point indirect grounding system, and can still continue to operate for a period of time after a single-phase grounding fault occurs, so that the single-phase grounding system is not easily distinguished from fundamental voltage sudden change caused by steady-state disturbance on a time scale. The distribution network is a neutral point indirect grounding system, and when a single-phase grounding fault occurs: the three-phase voltage amplitude change relationship is that the amplitude of the fault phase voltage is reduced, and the amplitude of the non-fault phase voltage is increased.
2. And obtaining characteristic interference data identification and elimination processes of each common connection point and each subharmonic of the concerned node based on the fault interference characteristics.
Mutation detection is a prerequisite for ensuring accurate data elimination. The wavelet transform can be used for detecting mutation, and the Mexican Hat (Mexican Hat) wavelet base is adopted because the Mexican Hat (Mexican Hat) wavelet has excellent mutation detection performance.
Using wavelet functions to detect anomalous data first the scale parameters should be determined:
in the formula, d represents the average sample distance, l represents the length of the wavelet function calculation interval, and k is a coefficient to be determined and represents the number of samples contained in the wavelet calculation interval. Calculating a wavelet coefficient according to the scale parameter, wherein the wavelet coefficient calculation formula comprises the following steps:
calculating wavelet coefficients from (1) and (2) and then normalizing:
wt'j＝(wtj-M)/S (3)
wherein M is a reference value (here, 0), S is a standard deviation of the wavelet coefficient, and the calculation formula is:
where n is the signal sample length. Whether the sudden change occurs or not is judged according to the relative size relation between the wavelet coefficient and the threshold, and if the wavelet coefficient of a certain point of the sample is larger than the threshold, the sudden change occurs in the point signal sample. The selection of the threshold is very critical in abnormal data detection, the threshold calculation has two modes at present, namely a global threshold and a local threshold, and the global threshold calculation is simple and has strong practicability. In order to take account of the usability and precision of the method, a global threshold proposed by Donoho and Johnstone is adopted, and the calculation formula of the threshold is as follows:
as shown in fig. 1, it comprises the following main steps:
1) calculating wavelet coefficients and threshold values of data points in the fundamental voltage data segment according to the formulas (1) to (5), starting from a first data point, detecting whether the wavelet coefficients of the data points exceed the threshold values, and if the wavelet coefficients of the data points exceed the threshold values, considering that sudden change occurs and entering 2);
2) and recording data point labels from the beginning of mutation, continuously detecting the wavelet coefficients, and considering that the mutation process is ended when the wavelet coefficients are smaller than a threshold value. Comparing data before and after mutation, if the variation reaches +/-10%, determining that the harmonic source state is mutated, and entering 3); otherwise, the data points are considered to belong to the interference of individual abnormal data points, the data point labels are stopped being recorded until the mutation is finished, and the data of the recorded labels are removed.
3) Continuously detecting the wavelet coefficients, if sudden change is detected again within 1 second, stopping recording the data point labels until the sudden change is finished, considering that faults which can be quickly removed such as two-phase short circuit, two-phase grounding, three-phase short circuit and the like occur, and removing corresponding labeled harmonic data; if the sudden change is detected again for more than 1 second or not until the last data point, the recording of the data point labels is stopped, and a single-phase earth fault or a change in the operating state is considered to have occurred, and then 4) is entered.
4) Comparing the three-phase data before and after the first mutation, if the difference between the two phases is small, the two phases are increased, then the single-phase earth fault is considered to occur, and the harmonic data of the record label is removed; otherwise, normal switching of the load state is considered to occur, data is reserved, and the fault data elimination is completed.
3. And establishing a distribution network distributed multi-harmonic source each harmonic responsibility division model.
As shown in fig. 2, there are 5 known distributed harmonic sources in the system, each connected to the distribution grid through a different node. Harmonic voltage of each node
(i denotes a node, and h denotes a harmonic order) is generated by the interaction of the harmonic sources. The load nodes and the concerned nodes of the harmonic sources are provided with monitoring devices which can measure the fundamental wave and the current and voltage of each harmonic and the background harmonic for the unknown harmonic component in the system
And (4) showing.
A multi-PCC model of the multi-target node can be established, as shown in equation (6).
In the formula (I), the compound is shown in the specification,
indicating that the node of interest k is at trThe voltage of the h-th harmonic at a time,
denotes the harmonic source m at trThe h harmonic current at time.
Representing the equivalent harmonic impedance between the harmonic source load i and the node of interest j,
representing the background harmonics at the node j of interest.
4. And obtaining the equivalent harmonic transmission impedance between each harmonic source and the attention node and the background harmonic voltage at the attention node.
The multi-dependent variable form complex domain partial least square method is utilized to calculate regression model coefficients, namely equivalent harmonic transfer impedances between harmonic sources and attention nodes and background harmonic voltages at attention nodes, and order Ee0＝X，F0＝Y。
1) From original data e0And F0Calculating
Maximum eigenvalue λ of1Corresponding feature vector w1
2) Calculating the component t1
t1＝E0w1(8)
3) Establishing a regression model and estimating a principal component coefficient vector p1And look back coefficient vector b1
4) Computing a data residual matrix E1And F1
5) Calculating other components
According to the reduced data residual error matrix EiAnd FiCalculating
Maximum eigenvalue λ ofi+1Corresponding feature vector wi+1I-1, …, s-1, s is e0Is determined.
6) Calculate the i +1 st component ti+1And coefficient vector pi+1And bi+1
7) Computing a data residual matrix Ei+1And Fi+1
The process is repeated until all w, t and b are calculated. And determining the number of the final main components by adopting a cross-checking method. If the final number of principal components is s, then there are
In the formula
I.e. the coefficient of the complex domain partial least squares regression equation, corresponding to equation (6)
And
5. and dividing the responsibility of each harmonic source for each subharmonic based on voltage vector projection.
As shown in fig. 3, the principle of harmonic responsibility division of a multi-harmonic source at a multi-focus node is given,
and
representing the total harmonic voltage of the load nodes 1 and 2,
and
respectively, the h-order harmonic voltage components (i ═ 1,2,3,4,5) induced at node 1 and node 2 by the harmonic source load i,
and
representing the h-th background harmonic voltage of nodes 1 and 2 of interest,
and
respectively representing phasors
And
the phase angle of (c). Defining an index
An h-order harmonic duty ratio index of a harmonic source load i (i ═ 1,2, …) at a focus node j (j ═ 1,2, …),
the responsibility duty ratio of h-th background harmonic at the focus node j is given.
In the formula
Is composed of
The phase angle of (a) is,
is composed of
The phase angle of (c).
As shown in fig. 4, a node 812 is connected to a 0.6MVA doubly-fed fan, a node 844 is connected to a 0.04MVA linear load, a node 848 is connected to a 3.5MVA flexible direct-current power transmission system, a node 858 is connected to a 0.3MVA photovoltaic power generation system, and a node 834 is a concerned node.
The basic parameters of the system of fig. 4 are: standard IEEE-34 node system parameters.
And setting the A-phase grounding fault at the 812 node for 3.5-5.5 seconds, setting the BC-phase grounding fault for 7.3-7.5 seconds, and setting the ABC-phase short-circuit fault for 8.5-8.7 seconds.
According to the above-mentioned research system setting operation simulation, the three-phase voltage, current fundamental wave and each subharmonic data of the node of interest (834 node) and each point of common coupling (812 node, 848 node, 858 node, 844 node) are sent to the fault data identification and elimination process shown in fig. 1, and the screening result is shown in fig. 5, so that the invention can accurately identify all 3 set fault periods. Then, establishing a harmonic responsibility division model for each harmonic data subjected to fault data elimination by utilizing the steps (3), (4) and (5) of the method, calculating each equivalent harmonic transmission impedance between each harmonic source and the concerned node and each background harmonic voltage of the concerned node, and further dividing the harmonic responsibility of each harmonic source at the concerned node 834; in addition, the harmonic source harmonic responsibility of each harmonic is calculated based on the three-phase voltage and current subharmonic data of the concerned node and each common coupling point by directly utilizing a robust regression method, and the effect pair of the two is shown in fig. 6.
The above embodiments are only intended to illustrate the technical solution of the present invention and not to limit the same, and a person of ordinary skill in the art can make modifications or equivalents to the specific embodiments of the present invention with reference to the above embodiments, and such modifications or equivalents without departing from the spirit and scope of the present invention are within the scope of the claims of the present invention as set forth in the claims.
Claims (6)
1. A harmonic responsibility division method for resisting short-circuit fault interference of a power distribution system is characterized by comprising the following steps:
step 1: acquiring interference characteristics of various types of short-circuit faults on fundamental wave monitoring data of each public connection point of the power distribution network, wherein the interference characteristics of the fundamental wave monitoring data are sudden changes of fundamental wave voltage;
step 2: obtaining interference characteristic data identification and elimination processes of each common connection point and each subharmonic of the concerned node based on the interference characteristics;
and step 3: establishing a distribution network distributed multi-harmonic source each harmonic responsibility division model, wherein the step 3 comprises the following steps: each harmonic source is connected to a power distribution network through different nodes, each subharmonic voltage of each node is generated by the combined action of each harmonic source, monitoring devices are arranged on each harmonic source load node and the concerned node, fundamental waves and each subharmonic current and voltage are measured, unknown harmonic components in the system are represented by background harmonics, and a multi-PCC model of a multi-target node is established;
and 4, step 4: obtaining equivalent harmonic transmission impedance between each harmonic source and the concerned node and background harmonic voltage at the concerned node;
and 5: dividing each harmonic source into respective harmonic responsibilities at the node of interest using harmonic voltage vector projection, said step 5 comprising the steps of: and calculating h-order harmonic duty ratio indexes of the harmonic source loads and the background harmonics at the concerned nodes according to h-order harmonic voltage amplitude and phase angle of each harmonic source load at each node and h-order background harmonic voltage amplitude and phase angle of each concerned node.
2. The harmonic responsibility division method for resisting short-circuit fault interference of the power distribution system as claimed in claim 1, wherein the various types of short-circuit faults in the step 1 comprise: single-phase ground faults, two-phase short-circuit faults, two-phase ground faults, and three-phase ground faults; and the interference characteristics of the two-phase short-circuit fault, the two-phase earth fault and the three-phase earth fault on the fundamental wave monitoring data of the common connection point are obtained according to the interference time limit, and the interference characteristics of the single-phase earth fault on the fundamental wave monitoring data of the common connection point are obtained according to the three-phase voltage amplitude variation relation when the single-phase earth fault occurs.
3. The harmonic responsibility division method for resisting short-circuit fault interference of the power distribution system as claimed in claim 1, wherein the step 2 comprises the steps of:
step 2.1: calculating wavelet coefficients and thresholds of data points in the fundamental voltage data segment, starting to detect whether the wavelet coefficients of the data points exceed the thresholds from the first data point, and if the wavelet coefficients of the data points exceed the thresholds, considering that mutation occurs, and entering step 2.2;
step 2.2: recording data point labels from the beginning of mutation, continuously detecting wavelet coefficients, considering that the mutation process is finished when the wavelet coefficients are smaller than a threshold value, comparing data before and after mutation, considering that the harmonic source state has mutation if the variation reaches +/-10%, and entering step 2.3; otherwise, the data points are considered to belong to the interference of the abnormal data points, the data point labels are stopped being recorded until the mutation is finished, and the data of the recorded labels are removed;
step 2.3: continuously detecting the wavelet coefficients, if sudden change is detected again within 1 second, stopping recording the data point labels until the sudden change is finished, considering that faults that two-phase short circuits, two-phase grounding and three-phase short circuits can be quickly cut off occur, and removing corresponding labeled harmonic data; if the sudden change is detected again more than 1 second or the sudden change is not detected again until the last data point, stopping recording the data point labels, considering that the single-phase earth fault or the change of the running state occurs, and then entering the step 2.4;
step 2.4: comparing the three-phase data before and after the first mutation, if the difference between the two phases is small, the two phases are increased, then the single-phase earth fault is considered to occur, and the harmonic data of the record label is removed; otherwise, normal switching of the load state is considered to occur, data is reserved, and the fault data elimination is completed.
4. The harmonic responsibility division method for resisting short-circuit fault interference of the power distribution system as claimed in claim 3, wherein the calculation process of the wavelet coefficients comprises the following steps: determining a scale function, calculating the wavelet coefficient according to the scale function, normalizing the wavelet coefficient, and calculating the standard deviation of the wavelet coefficient.
5. The harmonic responsibility division method for resisting short-circuit fault interference of the power distribution system as claimed in claim 3, wherein the threshold calculation adopts global threshold calculation.
6. The harmonic responsibility division method for resisting short-circuit fault interference of the power distribution system as claimed in claim 1, wherein the step 4 comprises the steps of: and calculating the coefficients of a regression model, namely equivalent harmonic transfer impedances between each harmonic source and the concerned node and background harmonic voltages at the concerned node by using a multi-dependent variable form complex field partial least square method.
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