A power distribution network risk early warning method, system, device and medium

Abstract

The application relates to the technical field of intelligent power distribution networks, in particular to a power distribution network risk early warning method, system, device and medium, and the technical scheme is as follows: first and last end measurement data and topological information of a power distribution network are acquired, real-time line loss and branch line currents are calculated according to the first and last end measurement data and the topological information, a linear relationship model of current square and line loss is established according to the real-time line loss and the branch line currents, line impedance and distribution transformer impedance are obtained, and distribution transformer parameter results are reserved; the distribution transformer branch of the linear relationship model is removed, the real-time line loss corresponding to the thermal loss on the distribution transformer branch impedance is removed, impedance estimation is performed on the line branch, and refined line impedance is obtained; a maintenance value is acquired, and comparison is made between the distribution transformer impedance and the refined line impedance and the maintenance value; whether the parameters of the equipment are abnormal is detected, the identification and evaluation of the parameters of the power distribution network equipment are accurate, and the reliability of risk evaluation is improved.

Description

Technical Field

[0001] This application relates to the field of smart distribution network technology, and in particular to a method, system, device and medium for early warning of distribution network risks. Background Technology

[0002] In terms of distribution network parameter calculation and verification, there are issues such as missing, incorrect, or unverifiable parameters. Traditional distribution network reliability assessment methods, which rely on constant results from historical equipment failure statistics as reliability parameters, are insufficient. Furthermore, distribution networks operate under varying load conditions, voltage curves, and environmental factors, and these dynamic conditions affect equipment performance and parameters.

[0003] Currently, a fault rate correction model is obtained by combining the baseline failure rate of distribution network equipment obtained from historical statistics with the operating status of distribution network equipment, taking into account actual conditions such as equipment operating time, equipment operating status, and natural weather factors. However, when standardized equipment data is lacking or the collected data contains inaccurate parameters, the identification and estimation results of distribution network equipment parameters are inaccurate, affecting the reliability of risk assessment. These problems need to be addressed. Summary of the Invention

[0004] To ensure accurate identification and assessment of power distribution network equipment parameters and improve the reliability of risk assessment, this application provides a power distribution network risk early warning method, system, equipment, and medium, employing the following technical solution:

[0005] Firstly, this application provides a method for early warning of risks in a power distribution network, including:

[0006] Acquire the measurement data and topology information of the beginning and end of the distribution network, and calculate the real-time line loss and the current of each branch line based on the measurement data and topology information of the beginning and end of the distribution network.

[0007] A linear relationship model between the square of the current and the line loss is established based on the real-time line loss and the current of each branch line to obtain the line impedance and the transformer impedance, and the transformer parameter results are retained.

[0008] By removing the distribution transformer branch from the linear relationship model and correspondingly removing the real-time line loss from the heat loss on the impedance of the distribution transformer branch, impedance estimation is performed on the line branch to obtain a refined line impedance.

[0009] Obtain maintenance values ​​and compare them with the transformer impedance and refined line impedance to detect whether there are any parameter changes in the equipment.

[0010] Preferably, the specific steps for calculating the real-time line loss based on the initial and final measurement data and topology information include:

[0011]

[0012] Where I0% is the short-circuit current percentage, S N For the distribution transformer capacity; P s,t Q s,t S represents the active and reactive power measurement data at the distribution network bus outlet at time t. loss,t Let p be the line loss of the distribution network at time t, and there are n branches including distribution transformers. l,t q l,t This is the power measurement value of the l-th distribution transformer.

[0013] Preferably, the specific steps for calculating the current of each branch line based on the measurement data of the first and last ends and the topology information include:

[0014]

[0015]

[0016] Among them, I p1 I q1 For the active and reactive currents of the distribution transformer branch corresponding to the upstream line, I p,2 I q,2 The current on the low-voltage side of the distribution transformer is k, where k is the transformer ratio, (I p,2 +jI q,2 ) / k represents the high-voltage side current of the transformer, and the square of this current is used as one of the characteristic quantities in the model calculation; U is the measured value of the low-voltage side voltage of the distribution transformer; I p I q I represents the active and reactive currents of the upstream line. pr I qr Let be the active and reactive current of the r-th downstream line.

[0017] Preferably, the linear relationship model includes:

[0018]

[0019] Among them, a i,t and I i,t and are the linear regression coefficient and apparent current value of the i-th branch in the distribution network at time t, respectively, and m is the number of branches.

[0020] Preferably, the specific steps for obtaining the refined line impedance are as follows:

[0021]

[0022]

[0023] Among them, S 1,loss,t Let I be the real-time line loss of the distribution network after the transformer branch is removed at time t. i,p2,t I i,q2,t Z represents the active and reactive current on the low-voltage side of the i-th distribution transformer branch at time t.i ,p b This is the impedance value of the i-th distribution transformer branch referred to the high-voltage side.

[0024] Preferred options also include:

[0025] It issues alarms for abnormal operating conditions of distribution transformers and lines.

[0026] Preferred options also include:

[0027] The equipment parameter maintenance values ​​include the impedance parameter values ​​recorded in the equipment ledger.

[0028] Secondly, this application provides a power distribution network risk early warning system, comprising:

[0029] Acquisition module: used to acquire the measurement data and topology information of the beginning and end of the distribution network, and calculate the real-time line loss and the current of each branch line based on the measurement data and topology information of the beginning and end of the distribution network;

[0030] Model building module: used to establish a linear relationship model between the square of current and line loss based on real-time line loss and the current of each branch line, to obtain the line impedance and transformer impedance, and to retain the transformer parameter results;

[0031] Refinement module: Used to remove the distribution transformer branches from the linear relationship model, remove the real-time line loss corresponding to the heat loss on the impedance of the distribution transformer branches, perform impedance estimation on the line branches, and obtain refined line impedance.

[0032] Comparison module: Used to obtain maintenance values, and compare the transformer impedance and refined line impedance with the maintenance values ​​to detect whether the equipment parameters have changed abnormally.

[0033] Thirdly, this application provides a power distribution network risk early warning device, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the power distribution network risk early warning method as described above.

[0034] Fourthly, this application provides a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the power distribution network risk early warning method as described above when it is run.

[0035] In summary, compared with the prior art, the beneficial effects of the technical solution provided in this application include at least the following:

[0036] This application collects measurement data and topology information from the beginning and end of the distribution network. Using this data, it calculates real-time line losses and currents in each branch line. By regressing the line losses from the currents in each branch, a linear relationship model between the square of the current and the line losses is established, yielding line impedance and transformer impedance. However, only the transformer parameters are retained. Next, the heat loss on the impedance of each transformer is calculated and correspondingly removed from the line losses. Only the line current is regressed for calculation, refining the line parameters. Finally, the estimated values ​​of transformer and line impedance parameters are compared with the maintenance values ​​to detect any parameter anomalies and provide early warnings. This significantly improves the quality management of distribution network data, contributes to the construction of a new type of intelligent power system, ensures accurate identification and evaluation of distribution network equipment parameters, and enhances the reliability of risk assessment. Attached Figure Description

[0037] Figure 1 This is a schematic diagram of a power distribution network risk early warning process as described in an embodiment of this application.

[0038] Figure 2 This is a diagram of the medium-voltage distribution network topology described in the embodiments of this application.

[0039] Figure 3 This is a schematic diagram of a power distribution network risk early warning module as described in an embodiment of this application.

[0040] Explanation of reference numerals in the attached figures:

[0041] 1. Acquisition module; 2. Model building module; 3. Refinement module; 4. Comparison module. Detailed Implementation

[0042] The following combination Figures 1-3 The present application will be described in further detail below. The terminology used in the embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting.

[0043] Reference Figure 1 The distribution network risk early warning method involved in this application specifically includes:

[0044] Step S1: Obtain the measurement data and topology information of the beginning and end of the distribution network, and calculate the real-time line loss and the current of each branch line based on the measurement data and topology information of the beginning and end of the distribution network.

[0045] Step S2: Based on the real-time line loss and the current of each branch line, establish a linear relationship model between the square of the current and the line loss to obtain the line impedance and the transformer impedance, and retain the transformer parameter results;

[0046] Step S3: Remove the distribution transformer branch from the linear relationship model, remove the corresponding real-time line loss from the heat loss on the impedance of the distribution transformer branch, perform impedance estimation on the line branch, and obtain the refined line impedance.

[0047] Step S4: Obtain maintenance values ​​and compare them with the transformer impedance and refined line impedance to detect whether the equipment parameters have changed abnormally.

[0048] Specifically, this embodiment calculates the real-time line loss and current of each line in the distribution network, and regresses the line loss from the current of each line and distribution transformer to calculate the line impedance and distribution transformer impedance parameters. In the first round, only the distribution transformer parameters are retained. Then, the heat loss on the impedance of each distribution transformer is calculated and correspondingly removed from the line loss. Only the line branch current is used to regress the line loss to obtain the accurate line impedance. Finally, the calculated distribution transformer and line parameters are integrated, and the calculated values ​​are compared with the maintenance values ​​to detect abnormal equipment parameters and provide risk warnings. This improves the efficiency of distribution network data quality management, makes the identification and evaluation of distribution network equipment parameters accurate, and enhances the reliability of risk assessment.

[0049] As one implementation method, the specific steps for calculating real-time line loss based on end-to-end measurement data and topology information include:

[0050]

[0051] Where I0% is the short-circuit current percentage, S N For the distribution transformer capacity; P s,t Q s,t S represents the active and reactive power measurement data at the distribution network bus outlet at time t. loss,t Let p be the line loss of the distribution network at time t, and there are n branches including distribution transformers. l,t q l,t This is the power measurement value of the l-th distribution transformer.

[0052] Specifically, in a medium-voltage distribution network, the first end is a 10kV distribution feeder, and the last end is a distribution transformer, connected in the middle by switching stations, ring main units, and various branch lines. The real-time line loss of the distribution network is calculated by subtracting the low-voltage side power of the distribution transformer and the copper and iron losses of the distribution transformer from the bus outlet power. The bus outlet power and the secondary side power of the distribution transformer are measured values ​​obtained from smart meters. The no-load loss ΔP0 of the distribution transformer is directly given by the distribution transformer technical parameters, and the no-load loss of the distribution transformer is also an iron loss. The short-circuit loss ΔQ0 is calculated from the percentage of short-circuit current in the distribution transformer technical parameters, and the short-circuit loss is also called copper loss.

[0053] As one implementation method, the specific steps for calculating the current of each branch line based on the first and last end measurement data and topology information include:

[0054]

[0055]

[0056] Among them, I p1 I q1 For the active and reactive currents of the distribution transformer branch corresponding to the upstream line, Ip,2 I q,2 The current on the low-voltage side of the distribution transformer is k, where k is the transformer ratio, (I p,2 +jI q,2 ) / k represents the high-voltage side current of the transformer, and the square of this current is used as one of the characteristic quantities in the model calculation; U is the measured value of the low-voltage side voltage of the distribution transformer; I p I q I represents the active and reactive currents of the upstream line. pr I qr Let be the active and reactive current of the r-th downstream line.

[0057] Specifically, branches in a distribution network can be divided into line branches and transformer branches. Given the current operating topology of the distribution network, the current of each upstream branch is the vector sum of the currents of the downstream branches. Therefore, the active and reactive current measurements on the low-voltage side of the terminal transformer can be converted to the high-voltage side through the transformer ratio and copper and iron losses. Based on the topology information, the apparent current of each branch line of the distribution network can be derived.

[0058] As one implementation method, the linear relationship model includes:

[0059]

[0060] Among them, a i,t and I i,t and are the linear regression coefficient and apparent current value of the i-th branch in the distribution network at time t, respectively, and m is the number of branches.

[0061] Specifically, at any given time, the power loss of a distribution feeder is equal to the sum of the heat losses caused by the current in each branch line across that branch impedance. Therefore, by decomposing the line loss step by step, studying the current vector sum and the heat loss caused in each line segment, and establishing a linear regression model that relates to the total loss, the distribution network impedance parameters can be calculated.

[0062] For this model, the obtained regression coefficients correspond to the impedance parameters of the branch lines or distribution transformers. Furthermore, based on electrical characteristics, distribution network line losses are essentially a linear combination of the power at the beginning and end points; therefore, the intercept is not included in the calculation in the regression model. However, in actual distribution network operation, line losses are mainly provided by the heat loss on the distribution transformer impedance. Typically, the distribution transformer impedance is around 8Ω, while the line impedance is less than 0.1Ω. This results in the regression coefficients of the distribution transformer branches contributing significantly more to the line losses than the regression coefficients of the line branches, causing errors in line impedance estimation during calculation. Therefore, a refinement step is needed to further refine the solution for the line impedance.

[0063] As one implementation method, the specific steps for obtaining the refined line impedance are as follows:

[0064]

[0065]

[0066] Among them, S 1,loss,t Let I be the real-time line loss of the distribution network after the transformer branch is removed at time t. i,p2,t I i,q2,t Z represents the active and reactive current on the low-voltage side of the i-th distribution transformer branch at time t. i ,p b This is the impedance value of the i-th distribution transformer branch referred to the high-voltage side.

[0067] Specifically, the distribution transformer branches are removed from the model, and the heat loss on the impedance of all distribution transformer branches is removed in real time. Only the impedance of the line branches is estimated. At this time, the feature in the linear regression model is the square value of the current of mn line branches.

[0068] As one implementation method, it also includes:

[0069] It issues alarms for abnormal operating conditions of distribution transformers and lines.

[0070] Specifically, by comparing the calculated transformer and line parameters with the system maintenance values, abnormal impedance parameter fluctuations can be detected, and timely alarms can be issued for abnormal operation of transformers and lines. The equipment parameter maintenance values ​​include the impedance parameter values ​​recorded in the equipment ledger.

[0071]

[0072] Among them, Z i,pb Z i,line Z represents the estimated impedance of the distribution transformer and the line. i,pb0 Z i,line0 ε is the impedance maintenance value. pb ε line The abnormality threshold is used to determine whether the transformer or line is in an abnormal operating state when the difference between the estimated value and the maintenance value exceeds the abnormality threshold.

[0073] In one implementation method, the real-time line loss of the present invention is a calculated line loss that takes into account the time-series power acquisition data and the transformer's own losses, specifically expressed as follows:

[0074]

[0075] At this point, the physical meaning of line loss is the heat loss between the line and the transformer impedance, or

[0076]

[0077] At this point, the physical meaning of line loss is the heat loss of the line. In the above content, the active and reactive power data of the low-voltage side of the distribution transformer and the bus outlet are the time-series measurement data of the meters. The no-load loss and short-circuit loss of the distribution transformer are obtained from the technical parameters of the distribution transformer. The voltage data used to calculate the short-circuit loss is the voltage of the high-voltage side of the distribution transformer, which can be obtained by converting the low-voltage side voltage measurement value through the turns ratio; or it can be replaced by the rated voltage of the high-voltage side of the transformer.

[0078] Reference Figure 2 The diagram shows a simplified topology of a medium-voltage distribution network, including the initial busbar, branch lines, intermediate switching stations, ring main units, and terminal distribution transformers. Measurement data for the distribution network is not comprehensive; voltage and load measurements are available at the beginning and end points, while switching stations only have incoming and outgoing power transmission data. The remaining nodes typically lack measurement data. During normal operation, the distribution network's topology is fixed. Therefore, based on the actual topology information and the low-voltage side current measurements of the distribution transformers, the apparent current values ​​of all distribution network branches can be derived from the bottom up.

[0079] A parameter estimation linear regression model is established, with the characteristic quantity being the squared value of the branch current, the label being the real-time line loss, and the regression coefficients representing the equipment impedance parameters. It should be noted that the characteristic quantity includes both transformer current characteristics and line current characteristics, where the transformer current characteristic is the current value on the high-voltage side of the transformer branch, derived from (I... p2 +jI q2 The line current characteristic is obtained by ) / k; that is, the current value of intermediate lines other than the beginning and end of the distribution network, including the branch current provided by the copper and iron losses of the distribution transformer. The calculation formula is:

[0080]

[0081]

[0082] With a measurement sampling frequency of 96 points per day, the model input is the measurement data for one day; when the sampling frequency is 48 or 24, the number of measurement sampling days needs to be increased accordingly. After calculating the square of the apparent current of each branch, the regression coefficients of each characteristic quantity are obtained by solving the model, which correspond to the equipment impedance parameters.

[0083] The mathematical model can be represented as:

[0084]

[0085] In actual distribution network operation, line losses are mainly provided by the heat loss on the transformer impedance, which is much greater than the line impedance. This will cause the contribution of the transformer branch regression coefficient to line losses to be much greater than that of the line branch regression coefficient, leading to errors in line impedance estimation during calculation. Therefore, the calculation results in this round only retain the transformer impedance parameter, and the line impedance will be refined in the next round.

[0086] Based on the calculated transformer impedance, the heat loss on each transformer is calculated and correspondingly removed from the line loss. At this point, the model characteristic is the square of the line current, the label is the real-time line loss after the transformer branch is removed, and the model output is the impedance of each line.

[0087] By integrating the results of the two parameter estimations, comparing the calculated and maintained values ​​of the equipment impedance, the system can detect whether the equipment is in an abnormal operating state and issue an alarm, thereby realizing parameter estimation and risk warning for distribution network equipment.

[0088] Reference Figure 3 This application provides a power distribution network risk early warning system, which includes:

[0089] Acquisition Module 1: Used to acquire the measurement data and topology information of the beginning and end of the distribution network, and calculate the real-time line loss and the current of each branch line based on the measurement data and topology information of the beginning and end of the distribution network.

[0090] Model building module 2: Used to establish a linear relationship model between the square of the current and the line loss based on the real-time line loss and the current of each branch line, to obtain the line impedance and the transformer impedance, and to retain the transformer parameter results;

[0091] Refined processing module 3: It is used to remove the distribution transformer branches from the linear relationship model, remove the heat loss on the impedance of the distribution transformer branches corresponding to the real-time line loss, perform impedance estimation on the line branches, and obtain refined line impedance.

[0092] Comparison Module 4: Used to obtain maintenance values. It compares the transformer impedance and refined line impedance with the maintenance values ​​to detect whether the equipment parameters have changed abnormally.

[0093] This application provides a power distribution network risk early warning device, including a memory and a processor. The memory stores a computer program, and the processor is configured to run the computer program to execute the power distribution network risk early warning method as described above.

[0094] This application provides a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the power distribution network risk early warning method described above when it is run.

[0095] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the device and product described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0096] In the several embodiments provided in this application, it should be understood that the disclosed methods, systems, apparatus and program products can be implemented in other ways.

[0097] 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.

[0098] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for early warning of risks in a power distribution network, characterized in that, include: Acquire the measurement data and topology information of the beginning and end of the distribution network, and calculate the real-time line loss and the current of each branch line based on the measurement data and topology information of the beginning and end of the distribution network. The specific steps for calculating real-time line loss based on initial and final measurement data and topology information include: ； Where I0% is the short-circuit current percentage, S N For the distribution transformer capacity; P s,t Q s,t S represents the active and reactive power measurement data at the distribution network bus outlet at time t. loss,t Let p be the line loss of the distribution network at time t, and there are n branches including distribution transformers. l,t q l,t This is the power measurement value of the l-th distribution transformer; The specific steps for calculating the current of each branch line based on the measurement data from the beginning and end points and the topology information include: ； ； Among them, I p1 I q1 For the active and reactive currents of the distribution transformer branch corresponding to the upstream line, I p,2 I q,2 The current on the low-voltage side of the distribution transformer is k, which is the transformer ratio (I p,2 +jI q,2 ) / k represents the high-voltage side current of the transformer, and the square of this current is used as one of the characteristic quantities in the model calculation; U is the measured value of the low-voltage side voltage of the distribution transformer; I p I q I represents the active and reactive currents of the upstream line. pr I qr Let be the active and reactive current of the r-th downstream line; A linear relationship model between the square of the current and the line loss is established based on the real-time line loss and the current of each branch line to obtain the line impedance and the transformer impedance, and the transformer parameter results are retained. By removing the distribution transformer branch from the linear relationship model and correspondingly removing the real-time line loss from the heat loss on the impedance of the distribution transformer branch, impedance estimation is performed on the line branch to obtain a refined line impedance. Obtain maintenance values ​​and compare them with the transformer impedance and refined line impedance to detect whether there are any parameter changes in the equipment.

2. The distribution network risk early warning method according to claim 1, characterized in that, The linear relationship model includes: ； Among them, a i,t and I i,t and are the linear regression coefficient and apparent current value of the i-th branch in the distribution network at time t, respectively, and m is the number of branches.

3. The distribution network risk early warning method according to claim 2, characterized in that, The specific steps for obtaining the refined line impedance are as follows: ； ； Among them, S 1,loss,t Let I be the real-time line loss of the distribution network after the transformer branch is removed at time t. i,p2,t I i,q2,t Z represents the active and reactive current on the low-voltage side of the i-th distribution transformer branch at time t. i ,p b This is the impedance value of the i-th distribution transformer branch referred to the high-voltage side.

4. The distribution network risk early warning method according to claim 1, characterized in that, Also includes: It issues alarms for abnormal operating conditions of distribution transformers and lines.

5. The distribution network risk early warning method according to claim 4, characterized in that, Also includes: The equipment parameter maintenance values ​​include the impedance parameter values ​​recorded in the equipment ledger.

6. A power distribution network risk early warning system, characterized in that, include: Acquisition module: Used to acquire the measurement data and topology information of the beginning and end of the distribution network, and calculate the real-time line loss and the current of each branch line based on the measurement data and topology information; the specific steps for calculating the real-time line loss based on the measurement data and topology information include: ； Where I0% is the short-circuit current percentage, S N For the distribution transformer capacity; P s,t Q s,t S represents the active and reactive power measurement data at the distribution network bus outlet at time t. loss,t Let p be the line loss of the distribution network at time t, and there are n branches including distribution transformers. l,t q l,t This is the power measurement value of the l-th distribution transformer; The specific steps for calculating the current of each branch line based on the measurement data from the beginning and end points and the topology information include: ； ； Among them, I p1 I q1 For the active and reactive currents of the distribution transformer branch corresponding to the upstream line, I p,2 I q,2 The current on the low-voltage side of the distribution transformer is k, which is the transformer ratio (I p,2 +jI q,2 ) / k represents the high-voltage side current of the transformer, and the square of this current is used as one of the characteristic quantities in the model calculation; U is the measured value of the low-voltage side voltage of the distribution transformer; I p I q I represents the active and reactive currents of the upstream line. pr I qr Let be the active and reactive current of the r-th downstream line; Model building module: used to establish a linear relationship model between the square of current and line loss based on real-time line loss and the current of each branch line, to obtain the line impedance and transformer impedance, and to retain the transformer parameter results; Refined processing module: used to remove the distribution transformer branches from the linear relationship model, remove the real-time line loss corresponding to the heat loss on the impedance of the distribution transformer branches, perform impedance estimation on the line branches, and obtain refined line impedance. Comparison module: Used to obtain maintenance values, and compare the transformer impedance and refined line impedance with the maintenance values ​​to detect whether the equipment parameters have changed abnormally.

7. A power distribution network risk early warning device, characterized in that, It includes a memory and a processor, the memory storing a computer program and the processor being configured to run the computer program to perform the power distribution network risk early warning method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program is configured to execute the power distribution network risk early warning method according to any one of claims 1-5 when it is run.

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