Sensitivity analysis method and device for fault strength and fault distance based on virtual disturbance admittance

Abstract

This invention discloses a sensitivity analysis method and apparatus for fault intensity and fault distance based on virtual disturbance admittance. The key technical points include the following steps: establishing a virtual disturbance admittance that quantitatively characterizes the voltage sag process; establishing a voltage sag monitoring model, wherein each bus in the voltage sag monitoring model has at least two monitoring points, configured as POM power quality monitors; when any monitoring point in the system detects a voltage sag, all POM power quality monitors in the voltage sag monitoring model simultaneously start voltage and current recording; calculating the electrical distance *f* from the disturbance center in the same direction between any two adjacent buses in the voltage sag monitoring model using the virtual disturbance admittance. This provides a more sensitive and accurate fault monitoring method in a monitoring circuit compared to the effective voltage value.

Description

Technical Field

[0001] This invention relates to the technical field of fault sensitivity calculation methods based on virtual disturbance admittance, specifically to a sensitivity analysis method and apparatus for fault intensity and fault distance based on virtual disturbance admittance. Background Technology

[0002] Sensitivity analysis is a method for evaluating the rate of change of structural response characteristics caused by changes in design variables or parameters. Research on the sensitivity of structural systems is becoming increasingly important and is one of the main research directions in computational mechanics and structural engineering.

[0003] In practical applications, sensitivity analysis of structures plays a crucial role in structural optimization, reliability assessment, and parameter identification. Methods can be categorized into discrete methods and variational methods based on their strategies. Traditional sensitivity analysis methods generally require recalculating using finite element methods under perturbations. This is particularly problematic when the structure has flexible characteristics and a large number of finite element samples, leading to high computational complexity and low efficiency. Some operating conditions necessitate velocity measurement to perform sensitivity analysis on parameters such as mass based on velocity admittance information. Addressing the low efficiency of traditional sensitivity analysis methods has become a pressing practical engineering problem.

[0004] Voltage sags can propagate through power lines at the same voltage level or through transformers at different voltage levels. The former is called lateral propagation, and the latter is called longitudinal propagation. For any voltage sag event, both propagation methods exist simultaneously. When a voltage sag occurs at one node (the disturbance point), the intensity of the voltage sag detected by another node (the monitoring point) depends not only on the intensity of the voltage sag at the disturbance point but also on the topology of the power grid and the electrical distance between the monitoring node and the fault point. Therefore, the propagation of voltage sags can be viewed as the result of the combined effect of the voltage sag event and the power grid topology.

[0005] When a fault occurs in a circuit, it is usually accompanied by a voltage sag, which is usually accompanied by a sudden change in current. Existing technologies generally use the effective voltage value near the fault point to compare and determine the fault distance and fault intensity of the monitoring point relative to the fault point. However, in actual detection, due to the low resolution of the effective voltage value, the monitoring scheme of the effective voltage value often cannot effectively identify low fault intensity.

[0006] Based on current conventional technologies, there exists a voltage sag identification index with higher resolution than the RMS voltage value, namely virtual disturbance admittance. Given these technological requirements, there is an urgent need for a more sensitive and accurate fault detection method for monitoring circuits compared to the RMS voltage value. Summary of the Invention

[0007] The purpose of this invention is to provide a sensitivity analysis method and apparatus for fault intensity and fault distance based on virtual disturbance admittance. By using virtual disturbance admittance, the intensity of the fault can be more sensitively perceived, especially when monitoring some small faults, it can better reflect the intensity of the fault and quickly determine the location of the fault point.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a sensitivity analysis method for fault intensity and fault distance based on virtual disturbance admittance, comprising the following steps:

[0009] Establish a virtual perturbation admittance to quantitatively characterize the voltage sag process;

[0010] A voltage sag monitoring model is established, wherein at least two monitoring points are set on each bus in the voltage sag monitoring model, and the monitoring points are configured as POM power quality monitors;

[0011] When any monitoring point in the system detects a voltage sag, all POM power quality monitors in the voltage sag monitoring model simultaneously start voltage and current recording.

[0012] The electrical distance from the disturbance center f in the same direction is calculated using the virtual disturbance admittance between any two adjacent buses in the voltage sag monitoring model.

[0013] In one embodiment of this application, a sensitivity analysis device for fault intensity and fault distance based on virtual disturbance admittance is also disclosed, comprising:

[0014] A virtual disturbance admittance measurement unit is configured to establish and measure a virtual disturbance admittance that quantitatively characterizes the voltage sag process;

[0015] The voltage sag monitoring model unit is configured such that each bus in the voltage sag monitoring model has at least two monitoring points, and each monitoring point is equipped with a POM power quality monitor; when any monitoring point in the system detects a voltage sag, all POM power quality monitors in the voltage sag monitoring model simultaneously start voltage and current recording.

[0016] The electrical distance calculation unit is configured to calculate the electrical distance from the disturbance center f in the same direction by using the virtual disturbance admittance between any two adjacent buses in the voltage sag monitoring model.

[0017] In one embodiment of this application, a computer-readable storage medium is also provided, wherein a computer program is stored therein, wherein the computer program is configured to execute the steps of any of the above method embodiments at runtime.

[0018] In one embodiment of this application, an electronic device is also provided, including a memory and a processor, characterized in that the memory stores a computer program, and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows: by using a voltage sag identification index with higher resolution than the effective voltage value, namely virtual disturbance admittance, the virtual disturbance admittance fault analysis is more accurate and the intensity of the fault is more sensitive. Especially when monitoring some small faults, it can better reflect the intensity of the fault and quickly determine the location of the fault point. Attached Figure Description

[0020] Figure 1 This is a flowchart of the method steps in this application;

[0021] Figure 2 This is an equivalent model used in the embodiments of this application to illustrate the voltage sag monitoring point and the disturbance center;

[0022] Figure 3 This is a simplified schematic diagram illustrating the relative electrical distance between adjacent monitoring points and the disturbance center in this embodiment of the application.

[0023] Figure 4 This is a schematic diagram of the network before voltage sag in the embodiments of this application;

[0024] Figure 5 This is a network diagram used to illustrate the voltage sag process in the embodiments of this application;

[0025] Figure 6 This is an equivalent circuit diagram used to illustrate the short-circuit condition in the embodiments of this application;

[0026] Figure 7 This is a schematic diagram of the structure of the display device in the embodiments of this application. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] like Figure 1 As shown, in one embodiment, a sensitivity analysis method for fault intensity and fault distance based on virtual disturbance admittance includes the following steps:

[0029] Establish a virtual perturbation admittance to quantitatively characterize the voltage sag process;

[0030] A voltage sag monitoring model is established, wherein at least two monitoring points are set on each bus in the voltage sag monitoring model, and the monitoring points are configured as POM (Power quality monitoring) power quality monitors;

[0031] When any monitoring point in the system detects a voltage sag, all POM power quality monitors in the voltage sag monitoring model simultaneously start voltage and current recording.

[0032] The electrical distance from the disturbance center f in the same direction is calculated using the virtual disturbance admittance between any two adjacent buses in the voltage sag monitoring model.

[0033] It should be noted that a voltage sag can be viewed as a rapid increase in the admittance of a node in the power grid within a very short period of time, resulting in a large influx of current into that node and further causing a sudden drop in the voltage received by that node. The relative electrical distance of voltage sag monitoring points refers to the ranking of the electrical distances of multiple PQMs from the disturbance center for the same voltage sag disturbance source.

[0034] In an optional implementation, the virtual disturbance admittance that quantitatively characterizes the voltage sag process is established by recording the voltage and current before and after the onset of the voltage sag at each monitoring point. The virtual disturbance admittance is shown in the equation.

[0035]

[0036] In the formula, For virtual disturbance admittance, I is used to quantitatively characterize the admittance disturbance during voltage sag. p I is the effective value of n cycles fixed before the voltage sag. f U f These are the effective values ​​of current and voltage for a fixed n cycles during the voltage sag, respectively.

[0037] It should be noted that voltage sags are usually accompanied by sudden changes in current. Based on this, a voltage sag identification index with higher resolution than the RMS voltage value has been proposed, namely... This is the virtual disturbance admittance; the larger its absolute value, the deeper the sag.

[0038] In an optional implementation, the voltage sag monitoring model includes equivalent power sources G1 and G2 located at both ends of the model. Each of the equivalent power sources G1 and G2 has an adjacent generator bus. Multiple substation buses are provided between the two sets of generator buses. There is a line impedance Z between each substation bus and a load impedance ZL on each bus. There are line impedances MZ and NZ between the two sets of generator buses and the adjacent substation buses. The fault impedance of the disturbance center f is Zf.

[0039] The following example illustrates a voltage sag monitoring model for a substation with four busbars, providing a detailed description of the above method.

[0040] like Figure 2 As shown, 1 and 6 are generator buses, 2-5 are substation buses, Z and ZL are the line and load impedances respectively, and G1 and G2 are the equivalent power sources of the system. Two PQMs are configured at each bus location to monitor the voltage sag process of the feeder and the load respectively. When any PQM in the system detects a voltage sag, all PQMs in the network synchronously start voltage and current recording.

[0041] assumed Figure 2 A temporary sag disturbance occurs between buses 3 and 4. The magnitudes of the virtual disturbance admittances of buses 2 and 3 represent their electrical distances from the disturbance center f in the same direction. Similarly, this can be applied to buses 4 and 5. Therefore, the relative electrical distances of any adjacent monitoring points in the network from the disturbance center can be simplified to solving for the magnitudes of the virtual disturbance admittances of buses 2 and 3 as shown in the figure.

[0042] like Figure 3 As shown, this is a simplified schematic diagram of the relative electrical distance between adjacent monitoring points and the disturbance center. During the entire process of the voltage sag event, it is assumed that the voltages of power supplies G1 and G2 remain constant. The virtual disturbance admittances of monitoring points 2 and 3 are solved by superposition positioning.

[0043] like Figure 4 The diagram shown is a schematic of the network before a voltage sag. Kirchhoff's quantitative method yields the following results:

[0044]

[0045]

[0046]

[0047]

[0048]

[0049] like Figure 2-6 As shown,

[0050]

[0051]

[0052]

[0053]

[0054]

[0055]

[0056]

[0057]

[0058]

[0059] p + q = 1

[0060] Let's take a short circuit as an example first. During later verification, a non-metallic short circuit can be considered.

[0061] U A -U1=I A Z A

[0062] U1-U2=I 12 Z 12

[0063] U2-U f =I 2f Z 2f

[0064] U f -U B =I Bf Z Bf

[0065]

[0066]

[0067]

[0068]

[0069] f j (Z f Z 2f ) = r j Z f +s j (Z 2f )

[0070]

[0071] g(Z f ,Z 2f )=kZ f +t(Z 2f )

[0072] t(Z 2f )=(Z B -Z 2f )(n+mZ 2f )

[0073] k=Z1Z2(Z 12 +Z A +Z B )+Z A Z B (Z1+Z2)+Z 12 (Z1Z B +Z A Z B +Z2Z A )

[0074] m=(Z1+Z A )(Z2+Z 12 )+Z1Z A

[0075] n=Z1Z2Z 12 +Z1Z2Z A +Z2Z 12 Z A

[0076] j <![CDATA[r j ]]> <![CDATA[a j ]]> <![CDATA[U1]]> <![CDATA[Z1(Z2Z B +Z 12 Z B +Z2Z 12 )U A +Z1Z2Z A U B ]]> <![CDATA[-Z1(Z2+Z 12 )IN A ]]> <![CDATA[U2]]> <![CDATA[Z2(Z1Z A +Z 12 Z A +Z1Z 12 )U B +Z1Z2Z B U A ]]> <![CDATA[-Z1Z2U A ]]> <![CDATA[I 12 ]]> <![CDATA[Z1(Z2+Z B )U A -Z2(Z1+Z A )U B ]]> <![CDATA[-Z1U A ]]> <![CDATA[I 2f ]]> <![CDATA[Z1Z2U A -(Z1Z2+Z1Z 12 +Z1Z A +Z2Z A +Z 12 FROM A )AT B ]]> 0

[0077] j <![CDATA[b j ]]> <![CDATA[c j ]]> <![CDATA[U1]]> <![CDATA[Z1(Z2Z B +Z 12 Z B -Z2Z 12 )U A ]]> <![CDATA[Z1Z2Z 12 WITH B AT A ]]> <![CDATA[U2]]> <![CDATA[Z1Z2Z B IN A ]]> 0 <![CDATA[I 12 ]]> <![CDATA[Z1(Z B -Z2)U A ]]> <![CDATA[Z1Z2Z B IN A ]]> <![CDATA[I 2f ]]> <![CDATA[-Z1Z2U A ]]> <![CDATA[Z1Z2Z B IN A ]]>

[0078] k=Z1Z2(Z 12 +Z A +Z B )+Z A Z B (Z1+Z2)+Z 12 (Z1Z B +Z A Z B +Z2Z A )

[0079] m=(Z1+Z A )(Z2+Z 12 )+Z1Z A

[0080] n=Z1Z2Z 12 +Z1Z2ZA +Z2Z 12 Z A

[0081]

[0082] At the same monitoring point Z f Sensitivity analysis

[0083]

[0084]

[0085] in The faults are represented by Z respectively. f Voltage and feeder current at bus j This is represented as no fault, i.e., Z. f The feeder current at ∞. For ease of understanding, the fault distance is set to a constant value of 0 when analyzing the sensitivity of the virtual disturbance admittance to the magnitude of the fault resistance.

[0086]

[0087]

[0088] To compare the sensitivity of voltage and virtual disturbance admittance, the absolute values ​​of their derivatives are compared using differentiation, and partial derivatives are taken for equations 1 and 2 respectively:

[0089]

[0090]

[0091]

[0092]

[0093]

[0094]

[0095]

[0096]

[0097]

[0098]

[0099] Sensitivity between two points, high recognition rate even with a very short line.

[0100]

[0101]

[0102]

[0103] Sensitivity comparison at the same point

[0104]

[0105]

[0106] Specifically, when a metallic short-circuit fault occurs at bus 2.

[0107] For ease of understanding, when comparing the effective voltage value U and the virtual disturbance admittance... For Z f When the sensitivity is , let Z 2f =0, taking monitoring point 1 in the figure as an example, for u1(Z) f ,0) and Find Z f The partial derivatives of .

[0108]

[0109]

[0110] As we know from basic circuit theory, for any monitoring point in a normally operating system, the larger the fault resistance (i.e., the smaller the fault current), the larger the voltage measured at the monitoring point and the smaller the current fluctuation. Therefore, u1(Z) f ,0) is Z f Monotonically increasing function For Z f A monotonically decreasing function, i.e.:

[0111]

[0112]

[0113] u1(Z f +δZ f ,0)-u1(Z f ,0)>0

[0114]

[0115] at the same time:

[0116]

[0117]

[0118]

[0119]

[0120] Therefore, we have: ru1, since both cu1 and km are positive numbers, hence... This holds true consistently, meaning that the sensitivity of the virtual disturbance admittance is better than that of the effective voltage value.

[0121]

[0122]

[0123]

[0124]

[0125]

[0126]

[0127]

[0128]

[0129] Based on the examples above, it is evident that fault analysis using virtual disturbance admittance relative to the absolute value of voltage is more accurate.

[0130] like Figure 7 As shown, a sensitivity analysis device for fault intensity and fault distance based on virtual disturbance admittance is also provided, comprising:

[0131] A virtual disturbance admittance measurement unit is configured to establish and measure a virtual disturbance admittance that quantitatively characterizes the voltage sag process;

[0132] The voltage sag monitoring model unit is configured such that each bus in the voltage sag monitoring model has at least two monitoring points, and each monitoring point is equipped with a POM power quality monitor; when any monitoring point in the system detects a voltage sag, all POM power quality monitors in the voltage sag monitoring model simultaneously start voltage and current recording.

[0133] The electrical distance calculation unit is configured to calculate the electrical distance from the disturbance center f in the same direction by using the virtual disturbance admittance between any two adjacent buses in the voltage sag monitoring model.

[0134] According to another aspect of the embodiments of this application, an electronic device for a sensitivity analysis method based on virtual disturbance admittance for fault strength and fault distance is also provided. This electronic device can be, but is not limited to, applied in a server. It is configured to perform the steps of any of the above method embodiments via a computer program.

[0135] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0136] S1, establish a virtual perturbation admittance to quantitatively characterize the voltage sag process;

[0137] S2, Establish a voltage sag monitoring model. In the voltage sag monitoring model, at least two monitoring points are set on each bus. The monitoring points are configured as POM power quality monitors.

[0138] S3, when any monitoring point in the system detects a voltage sag, all POM power quality monitors in the voltage sag monitoring model simultaneously start voltage and current recording.

[0139] S4. Calculate the electrical distance from the disturbance center f in the same direction using the virtual disturbance admittance between any two adjacent buses in the voltage sag monitoring model.

[0140] Embodiments of this application also provide a computer-readable storage medium storing a computer program configured to execute the steps in any of the above method embodiments when run.

[0141] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0142] S1, establish a virtual perturbation admittance to quantitatively characterize the voltage sag process;

[0143] S2, Establish a voltage sag monitoring model. In the voltage sag monitoring model, at least two monitoring points are set on each bus. The monitoring points are configured as POM power quality monitors.

[0144] S3, when any monitoring point in the system detects a voltage sag, all POM power quality monitors in the voltage sag monitoring model simultaneously start voltage and current recording.

[0145] S4. Calculate the electrical distance from the disturbance center f in the same direction using the virtual disturbance admittance between any two adjacent buses in the voltage sag monitoring model.

[0146] Optionally, in this embodiment, those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0147] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0148] If the integrated units in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in the aforementioned computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause one or more computer devices (which may be personal computers, servers, or network devices, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0149] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0150] In the several embodiments provided in this application, it should be understood that the disclosed client can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between units or modules, and may be electrical or other forms.

[0151] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0152] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0153] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A sensitivity analysis method for fault intensity and fault distance based on virtual disturbance admittance, characterized in that, Includes the following steps: Establish a virtual perturbation admittance to quantitatively characterize the voltage sag process; A voltage sag monitoring model is established, wherein at least two monitoring points are set on each bus in the voltage sag monitoring model, and the monitoring points are configured as POM power quality monitors; When any monitoring point in the system detects a voltage sag, all POM power quality monitors in the voltage sag monitoring model simultaneously start voltage and current recording. The electrical distance from the disturbance center f in the same direction is calculated using the virtual disturbance admittance between any two adjacent buses in the voltage sag monitoring model; where, Record the voltage and current at each monitoring point before and after the start of the voltage sag. The virtual disturbance admittance is shown in the equation. ， In the formula, This is a virtual disturbance admittance, used to quantitatively characterize the admittance disturbance during a voltage sag. The effective value is fixed for n cycles before the voltage sag. , These are the effective values ​​of current and voltage for a fixed n cycles during the voltage sag, respectively.

2. The sensitivity analysis method for fault intensity and fault distance based on virtual disturbance admittance according to claim 1, characterized in that: The voltage sag monitoring model includes equivalent power sources G1 and G2 located at both ends of the model. Each equivalent power source G1 and G2 has an adjacent generator bus. Multiple substation buses are provided between the two sets of generator buses. There is a line impedance Z between each substation bus and a load impedance ZL on each bus. There are line impedances MZ and NZ between the two sets of generator buses and the adjacent substation buses. The fault impedance of the disturbance center f is Zf.

3. A sensitivity analysis device for fault intensity and fault distance based on virtual disturbance admittance, characterized in that, include: The virtual disturbance admittance measurement unit is configured to establish and measure the virtual disturbance admittance that quantitatively characterizes the voltage sag process; wherein, Record the voltage and current at each monitoring point before and after the start of the voltage sag. The virtual disturbance admittance is shown in the equation. ， In the formula, This is a virtual disturbance admittance, used to quantitatively characterize the admittance disturbance during a voltage sag. The effective value is fixed for n cycles before the voltage sag. , These are the effective values ​​of current and voltage, respectively, for a fixed n cycles during the voltage sag. The voltage sag monitoring model unit is configured such that each busbar in the voltage sag monitoring model has at least two monitoring points, and each monitoring point is equipped with a POM power quality monitor; when any monitoring point in the system detects a voltage sag, all POM power quality monitors in the voltage sag monitoring model simultaneously start voltage and current recording. The electrical distance calculation unit is configured to calculate the electrical distance from the disturbance center f in the same direction by using the virtual disturbance admittance between any two adjacent buses in the voltage sag monitoring model.

4. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, wherein the computer program is configured to execute the method described in any one of claims 1 to 2 when it is run.

5. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to run the computer program to perform the method described in any one of claims 1 to 2.

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