Power distribution network power quality evaluation method and system

Abstract

The invention relates to the technical field of power quality evaluation, and discloses a power distribution network power quality evaluation method and system, and the method comprises the following steps: 1, collecting the voltage data of a power distribution network in a transient period, and obtaining the transient state feature data through data processing; wherein the transient state characteristic data comprises voltage sag depth and voltage sag duration; and 2, based on the transient state characteristic data, calculating an equipment endurance capability evaluation value. According to the method, the fault risk of the power distribution network can be accurately evaluated, the situation that the fault risk is underestimated due to neglect of key weak equipment is reduced, fault prevention and response measures can be specifically formulated based on determination of the potential fault triggering node set and the fault cascading nodes, the fault processing efficiency and effect are improved, and the fault risk can be accurately evaluated. By dividing the power distribution network fault area, a fault processing strategy can be effectively formulated, and the reliability and the stability of the power distribution network are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power quality assessment, and in particular to a method and system for assessing power quality in a distribution network. Background Art

[0002] With the continuous growth of electricity demand and the increasing complexity of power systems, distribution networks are facing many challenges, making power quality issues more prominent. The large-scale access of distributed energy sources, such as solar photovoltaic power generation and wind power generation, has alleviated energy pressure to a certain extent, but it has also brought new variables to the stability and power quality of distribution networks. During the operation of the distribution network, transient power quality problems will occur due to various faults and equipment operations. These problems not only affect the normal operation of power equipment and shorten the service life of equipment, but also have a serious impact on the user's power experience, and may even cause chain failures and lead to large-scale power outages. Traditional power quality assessment methods often focus on steady-state analysis, and lack comprehensive, accurate and timely assessment methods for power quality problems in transient processes, and cannot meet the requirements of modern distribution networks for safety, reliability and stability. Summary of the invention

[0003] The object of the present invention is to provide a method and system for evaluating power quality of a distribution network to solve at least one of the above-mentioned problems of the prior art.

[0004] In a first aspect, the present invention provides a method for evaluating power quality of a distribution network, comprising the following steps: Step 1: Collect voltage data of the distribution network during the transient period, and obtain transient state characteristic data based on the voltage state by processing the voltage data; Among them, transient state characteristic data include: voltage sag depth, voltage sag duration; Step 2: Based on the transient state characteristic data, calculate the equipment tolerance assessment value, evaluate the equipment tolerance, and obtain equipment risk data based on the assessment results; Step 3: Based on the equipment risk data, combined with the topological structure of the distribution network, cascading failure assessment is performed to obtain the risk path, and the set of potential fault-inducing nodes is screened. The fault propagation analysis is performed to obtain the set of cascading failure nodes and the distribution network fault area. Step 4: Analyze the fault area of ​​the distribution network and obtain the priority repair line sequence based on the fault area of ​​the distribution network.

[0005] In a second aspect, the present invention provides a distribution network power quality assessment system, specifically comprising: Transient data processing module: collects voltage data of the distribution network during the transient period, and obtains transient state characteristic data based on the voltage state by processing the voltage data; Among them, transient state characteristic data include: voltage sag depth, voltage sag duration; Equipment tolerance assessment module: Calculate the equipment tolerance assessment value based on transient state characteristic data, evaluate the equipment tolerance, and obtain equipment risk data based on the assessment results; Fault area acquisition module: Based on the equipment risk data and combined with the topological structure of the distribution network, cascading fault assessment is performed, the set of potential fault-inducing nodes is screened, and fault propagation analysis is performed to obtain the set of cascading fault nodes and the fault area of ​​the distribution network; Fault handling module: Analyze the fault area of ​​the distribution network and obtain the priority repair line sequence.

[0006] Beneficial effects of the present invention: The present invention can more accurately capture transient voltage changes in the distribution network through high-precision monitoring equipment and data processing algorithms, thereby improving the accuracy of power quality assessment. By evaluating the tolerance of equipment, potential equipment risks can be discovered in a timely manner, thereby enhancing the reliability and stability of the equipment. The present invention can accurately assess the fault risk of the distribution network, reduce the situation where the fault risk is underestimated due to neglect of key weak equipment, and based on the determination of the potential fault-inducing node set and the fault chain node, can formulate fault prevention and response measures in a targeted manner, improve the efficiency and effect of fault handling, and by dividing the distribution network fault area, can effectively formulate fault handling strategies, and improve the reliability and stability of the distribution network; The present invention can guide emergency repair personnel to quickly locate the most critical line for repair by determining the priority repair line sequence, thereby reducing blind operations. By determining the priority repair line sequence, resources can be invested in the emergency repair of the lines that are most needed. For lines with high priority repair values, more professionals and advanced equipment can be deployed to reduce resource waste on lines that have less impact on overall recovery, thereby improving resource utilization efficiency. Prioritizing the repair of the lines that are most critical to controlling fault propagation can effectively reduce the further spread of the fault. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0008] Figure 1It is a flow chart of a method for evaluating power quality of a distribution network according to the present invention; Figure 2 It is a structural schematic diagram of a power quality assessment system for a distribution network according to the present invention; Figure 3 It is a structural schematic diagram of a power quality assessment device for a distribution network according to the present invention.

[0009] In the figure: 3, computer device; 301, processor; 302, memory; 303, computer program; DETAILED DESCRIPTION

[0010] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention. Embodiment 1

[0011] Figure 1 A flow chart of a distribution network power quality assessment method provided in the first embodiment of the present invention, the embodiment of the present invention is applicable to the situation of distribution network power quality assessment in transient process, a distribution network power quality assessment method can be executed by a distribution network power quality assessment system, the distribution network power quality assessment system can be implemented by software and / or hardware, and the distribution network power quality assessment system can be configured in a distribution network power quality assessment device. Optionally, a distribution network power quality assessment device can be an electronic device, which can be a notebook, a desktop computer, a smart tablet, etc., and the embodiment of the present invention does not limit this.

[0012] like Figure 1 As shown, a method for evaluating power quality of a distribution network provided by an embodiment of the present invention specifically includes the following steps: Step 1: Collect the voltage data of the distribution network during the transient period through monitoring equipment, and obtain transient state characteristic data through data processing; Among them, transient state characteristic data include: voltage sag depth, voltage sag duration; In some embodiments, a number of collection points are set on the distribution network line, and monitoring equipment is installed at all the collection points; The collection points include but are not limited to: the outgoing terminal of the substation of the distribution network, important distribution line nodes, and large user access points; The monitoring equipment selected must have voltage collection function, including but not limited to: installing smart meters, power quality monitors, and fault recorders; Set the sampling frequency of the monitoring equipment. The sampling frequency can be set to 5000 Hz. The technicians in this field can adjust it according to the speed of change of the transient process of the distribution network. A higher sampling frequency helps to more accurately capture the rapidly changing voltage transient conditions. When the monitoring device detects a fault in the distribution network, it immediately and automatically starts the high-speed data acquisition mode to collect voltage data; Among them, fault events include but are not limited to: line short circuit, grounding, switch opening and closing, transformer switching; The collected voltage data is transmitted to the data processing platform in real time through wireless communication technology or wired communication network; After receiving the voltage data, the data processing platform processes the voltage data to obtain the voltage data sequence ; In this embodiment, the Kalman filter algorithm is used to filter the voltage data to remove noise caused by electromagnetic interference, measurement errors, etc., so that the voltage data is smoother and more accurate; Specifically, the Kalman filter algorithm is an iterative process for filtering data, which is mainly divided into two stages: prediction and update. The specific process is as follows: Prediction stage: Based on the state transition equation of the system, using the optimal state estimate at the previous moment The current state is predicted by calculating the value. The formula is: , where A is the state transfer matrix, describing the transition relationship of the system state from one moment to the next, and B is the control input matrix. is the control input vector. When there is no control input or the control input is not considered, Items can be omitted; Estimate the covariance matrix based on the state at the previous moment And the process noise covariance matrix Q, calculate the predicted state estimation covariance matrix, the formula is , the covariance matrix is ​​used to measure the uncertainty of state estimation; Update phase: Combine the predicted state estimate covariance matrix , the observation matrix H and the observation noise covariance matrix R to calculate the Kalman gain , the formula is , the Kalman gain determines the degree to which the new observation data updates the state estimate; Using Observations , Kalman gain and the predicted status To update the current state estimate, the formula is , by multiplying the residual between the predicted value and the observed value by the Kalman gain, the predicted value is corrected to obtain a more accurate state estimate; According to the Kalman gain and the predicted state estimate covariance matrix , update the state estimation covariance matrix at the current moment, the formula is , where is the I identity matrix, and the covariance update is used to provide an accurate covariance estimate for the next iteration; Starting from a given initial state estimate and covariance matrix, the prediction and update phases are repeated continuously. As new observation data is added, the estimate of the system state is gradually optimized, noise in the data is removed, and the voltage data is smoother and more accurate. Traverse the voltage data sequence , obtain the minimum voltage value during the transient period. If the rated voltage is known, the difference between the rated voltage and the minimum voltage value is calculated to obtain the voltage sag depth; Obtain the time point when the voltage starts to be lower than the normal fluctuation value and the time point when the voltage recovers to the normal fluctuation value, calculate the difference between the time point when the voltage recovers to the normal fluctuation value and the time point when the voltage starts to be lower than the normal fluctuation value, and obtain the duration of the voltage sag; Step 2: Based on transient state characteristic data, evaluate the tolerance of the equipment and obtain equipment risk data; In some embodiments, obtaining a voltage sag depth and a voltage sag duration; The voltage sag depth tolerance threshold and the sag duration tolerance threshold are set by technical personnel in the field according to the equipment type, by consulting the equipment's technical specifications, industry standards or relevant technical specifications to summarize and set them; For example, the voltage sag tolerance depth of industrial motors is 70% of the rated voltage and the tolerance time is 255ms; while some electronic devices with higher requirements on power quality, such as servers, have a voltage sag tolerance depth of 85% of the rated voltage and the tolerance time is 50ms; Based on the equipment tolerance evaluation formula , where R represents the equipment tolerance assessment value, D represents the actual voltage sag depth, T represents the actual voltage sag duration, WD represents the weight of the voltage sag depth, WT represents the weight of the voltage sag duration, and , f is a comprehensive evaluation function, and the appropriate form can be selected according to the actual situation; In this embodiment, f may be in the form of: , where DY represents the voltage sag depth tolerance threshold, and TY represents the sag duration tolerance threshold; Arrange the equipment tolerance evaluation values ​​in descending order to obtain the equipment tolerance evaluation value data sequence ; Integrate basic information of the equipment (such as equipment name, model, installation location, etc.), transient state characteristic data (voltage sag depth, sag duration), and tolerance assessment result value information to form equipment risk data; The equipment risk data is stored in the following format: | Equipment name | Model | Installation location | Voltage sag depth | Voltage sag duration | Tolerance assessment value |; The technical solution of this embodiment is: the voltage data of the distribution network in the transient period is collected by monitoring equipment, and transient state characteristic data such as voltage sag depth and duration are obtained through data processing. Then, based on these characteristic data, combined with the technical specifications of the equipment and the tolerance evaluation formula, the tolerance of the equipment is evaluated to obtain equipment risk data; Therefore, through high-precision monitoring equipment and data processing algorithms, the transient voltage changes in the distribution network can be captured more accurately, thereby improving the accuracy of power quality assessment. By evaluating the equipment's tolerance capability, potential equipment risks can be discovered in a timely manner, thereby enhancing the reliability and stability of the equipment. Embodiment 2

[0013] Based on the above embodiments, Figure 1 As shown, a method for evaluating power quality of a distribution network provided by an embodiment of the present invention specifically includes the following steps: Step 3: Based on the equipment risk data and combined with the topological structure of the distribution network, a cascading fault assessment is performed to screen the set of potential fault-causing nodes, and a fault propagation analysis is performed to obtain the fault area of ​​the distribution network; In some embodiments, a device tolerance evaluation value data sequence is obtained. ; Acquire the topological structure of the distribution network, wherein the topological structure of the distribution network is acquired through a distribution network management system based on GIS, and the distribution network management system based on GIS records the geographical location information and connection relationship of each device; Based on the topological structure of the distribution network, obtain the line connection path; For example, assume a distribution network topology, including a substation (denoted as Ss), two distribution transformers (denoted as Tt1 and Tt2 respectively), and four users (denoted as Uu1, Uu2, Uu3, and Uu4 respectively); Substation Ss is connected to distribution transformer Tt1 through an overhead line (denoted as Ll1) and to distribution transformer Tt2 through another overhead line (denoted as Ll2).

[0014] Distribution transformer Tt1 supplies power to users Uu1 and Uu2 through cable lines (denoted as Cc1), and the specific connections are Tt1 - Cc1 - Uu1 and Tt1 - Cc1 - Uu2.

[0015] The distribution transformer Tt2 supplies power to users Uu3 and Uu4 through a cable line (denoted as Cc2), and the specific connections are Tt2 - Cc2 - Uu3 and Tt2 - Cc2 - Uu4; In this example, the connection paths from the substation to each user are as follows: Ss - Ll1 - Tt1 - Cc1 - Uu1; Ss - Ll1 - Tt1 - Cc1 - Uu2; Ss - Ll2 - Tt2 - Cc2 - Uu3; Ss - Ll2 - Tt2 - Cc2 - Uu4; Based on any connection path, the device tolerance assessment values ​​on the connection path are summed and averaged to obtain the line path tolerance assessment mean value; Extract the maximum value of the equipment tolerance assessment value on the connection line; The comprehensive risk coefficient is calculated by weighting the mean value of the line path tolerance assessment and the maximum value of the equipment tolerance assessment, where the weight of the total value of the line path tolerance assessment is 0.47, and the weight of the maximum value of the equipment tolerance assessment is 0.53; It should be noted that the comprehensive risk coefficient is a weighted sum of the total value of the line path tolerance assessment and the maximum value of the equipment tolerance assessment, while taking into account the overall risk tolerance level of the equipment on the path and the impact of the single weakest equipment link. For example, on a connection path, even if the overall equipment tolerance is acceptable, there is a critical device with extremely low tolerance. The comprehensive risk coefficient can accurately reflect this situation and reduce the underestimation of failure risks due to neglect of critical weak equipment. Setting a comprehensive risk factor threshold, wherein the comprehensive risk factor threshold is set by a person skilled in the art based on historical experimental data and work experience; Arrange the comprehensive risk coefficients in descending order, retain the comprehensive risk coefficients greater than the comprehensive risk coefficient threshold, and mark the line path corresponding to the comprehensive risk coefficient as a risk path; Mark the starting node in the risk path as a potential fault-inducing node, and obtain a set of potential fault-inducing nodes; Perform fault propagation analysis based on the set of potential fault-causing nodes; Based on any potential fault-causing node, the impedance value and length value of the line between adjacent nodes are obtained according to the direction of the connection line; Set the typical impedance value and typical length value of the line. The typical impedance value and typical length value are summarized and set by technicians in this field according to the topological structure of the distribution network. For example, in a 10kV distribution network, the impedance value of a common overhead line per kilometer is about 0.3 + j0.4Ω / km. If most of the lines in the distribution network are 1-10km long, the impedance value of a 5km line (1.5 + j2Ω) can be selected as the typical impedance value. If most of the lines in the distribution network are concentrated in the range of 3-7km, 5km can be selected as the typical length value; The impedance value of the line is calculated by ratio with the typical impedance value to obtain the impedance ratio, and the length value of the line is calculated by ratio with the typical length value to obtain the length ratio; Calculate the fault influence intensity coefficient based on the fault influence intensity coefficient calculation formula; It needs to be explained that the impedance ratio and length ratio are inversely proportional to the fault intensity coefficient; Exemplarily, the calculation process of the fault impact intensity coefficient is: For a series circuit, the calculation formula for the fault intensity coefficient IQ is: ,in, It represents the equipment tolerance assessment value of the potential fault-inducing node, zk represents the impedance ratio, and xc represents the length ratio; For parallel circuits, the calculation formula for the fault intensity coefficient IQ is: ,in, It represents the equipment tolerance assessment value of the potential fault-causing node, xc represents the length ratio, It represents the current distribution coefficient, k means there are k parallel branches connected to different nodes, It represents the impedance ratio of the j-th branch, j=1,2,…,k; Traverse each node of the risk path and compare the fault impact intensity coefficient with the equipment tolerance assessment value. If the fault impact intensity coefficient is greater than the equipment tolerance assessment value, it is marked as a cascading failure node. If the fault impact intensity coefficient is less than or equal to the equipment tolerance assessment value, it is marked as a non-cascading failure node. Obtain the set of cascading fault nodes and divide the fault area of ​​the power grid; The technical solution of this embodiment is: based on the equipment risk data and the GIS topological structure of the distribution network, a weighted comprehensive risk coefficient of the line path tolerance assessment mean and the maximum value of the equipment tolerance assessment value is calculated to screen out a set of potential fault-causing nodes, and then a fault propagation analysis is performed. According to the comparison between the fault impact intensity coefficient and the equipment tolerance assessment value, the fault chain node is determined and the distribution network fault area is divided; Therefore, by comprehensively considering the overall tolerance capacity of the line path and the weakest link of a single device, the fault risk of the distribution network can be assessed more accurately, reducing the underestimation of fault risks due to neglect of key weak devices. Based on the determination of the potential fault-inducing node set and fault chain nodes, fault prevention and response measures can be formulated in a targeted manner to improve the efficiency and effectiveness of fault handling. By dividing the distribution network fault area, fault handling strategies can be effectively formulated to improve the reliability and stability of the distribution network. And when a fault occurs, the fault area of ​​the distribution network can be quickly demarcated, and emergency repair personnel can be guided to quickly locate the fault point and take effective repair measures, which helps to shorten the fault recovery time and reduce the impact of the fault on the operation of the distribution network and user electricity consumption. Embodiment 3

[0016] Based on the above embodiments, Figure 1 As shown, a method for evaluating power quality of a distribution network provided by an embodiment of the present invention specifically includes the following steps: Step 4: Analyze the fault area of ​​the distribution network and obtain the priority repair line sequence; In some embodiments, a set of cascading failure nodes is obtained, and based on any cascading failure node, the number of adjacent cascading failure nodes is counted; Obtain the fault impact intensity coefficients of the cascading fault nodes respectively; For each cascading failure node, the number of adjacent cascading failure nodes and the failure impact intensity coefficient are multiplied to obtain the node priority repair value; For any risk path containing a cascading failure node, sum up the node priority repair values ​​of all cascading failure nodes to obtain the total node priority repair value, and extract the maximum value of the node priority repair value; The total priority repair value is multiplied by the maximum priority repair value to obtain the line priority repair value; Arrange the line priority repair values ​​in descending order, which is the priority repair line order; This can guide repair personnel to quickly locate the most critical lines for repair and reduce blind operations. For example, in a large-scale power outage, if there is no priority order, repair personnel may spend time on some non-critical lines. After determining the priority repair line order, they can directly work on the lines that play a key role in restoring the operation of the power grid, greatly shortening the fault handling time and restoring power supply as soon as possible. The technical solution of this embodiment is as follows: first, a set of cascading failure nodes is obtained. For any cascading failure node, the number of adjacent cascading failure nodes is counted with the help of the distribution network topology information, and the node priority repair value is obtained by combining the fault impact intensity coefficient calculation. For each risk path containing the cascading failure node, the node priority repair values ​​of all cascading failure nodes are summed to obtain the total node priority repair value, and the maximum value thereof is extracted. The total priority repair value is then multiplied by the maximum priority repair value to obtain the line priority repair value, and the priority repair values ​​of all lines are arranged from large to small, thereby determining the priority repair line order; Therefore, when fault handling resources and time are limited, the priority repair line sequence can guide emergency repair personnel to quickly locate the most critical lines for repair and reduce blind operations. By determining the priority repair line sequence, resources can be invested in the repair of lines that are most needed. For lines with high priority repair values, more professionals and advanced equipment can be deployed to reduce resource waste on lines with less impact on overall recovery, improve resource utilization efficiency, and give priority to repairing the lines that are most critical to controlling fault propagation, which can effectively reduce the further spread of faults. Embodiment 4

[0017] Based on the above embodiments, Figure 2 As shown, a distribution network power quality assessment system provided by an embodiment of the present invention specifically includes: Transient data processing module: collects voltage data of the distribution network during the transient period through monitoring equipment, and obtains transient state characteristic data through data processing; Among them, transient state characteristic data include: voltage sag depth, voltage sag duration; Equipment tolerance assessment module: Based on transient state characteristic data, the tolerance capability of the equipment is assessed to obtain equipment risk data; Fault area acquisition module: Based on the equipment risk data and combined with the topological structure of the distribution network, cascading faults are evaluated, potential fault-causing node sets are screened, and fault propagation analysis is performed to obtain the fault area of ​​the distribution network; Fault handling module: Analyze the fault area of ​​the distribution network and obtain the priority repair line sequence. Embodiment 5

[0018] like Figure 3As shown, an embodiment of the present invention further provides a computer device 3, comprising: a memory 302 and a processor 301 and a computer program 303 stored in the memory 302. When the computer program 303 is executed on the processor 301, a distribution network power quality assessment method as described in any one of the above methods is implemented.

[0019] The computer device 3 may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art may understand that; Figure 3 It is only an example of computer device 3 and does not constitute a limitation on computer device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, etc.

[0020] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0021] In some embodiments, the memory 302 may be an internal storage unit of the computer device 3, such as a hard disk or memory of the computer device 3. In other embodiments, the memory 302 may also be an external storage device of the computer device 3, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device 3. Further, the memory 302 may also include both an internal storage unit and an external storage device of the computer device 3. The memory 302 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 302 may also be used to temporarily store data that has been output or is to be output. Embodiment 6

[0022] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, a method for evaluating power quality of a distribution network as described in any one of the above methods is implemented.

[0023] In this embodiment, if the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, USB flash drive, mobile hard disk, disk or optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0024] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0025] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0026] In the embodiments disclosed in the present application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0027] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0028] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0029] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for evaluating power quality of a distribution network, characterized in that: The following steps are involved: Step 1: Collect voltage data of the distribution network during the transient period, and obtain transient state characteristic data based on the voltage state by processing the voltage data; Among them, transient state characteristic data include: voltage sag depth, voltage sag duration; Step 2: Based on the transient state characteristic data, calculate the equipment tolerance assessment value, evaluate the equipment tolerance, and obtain equipment risk data based on the assessment results; Step 3: Based on the equipment risk data, combined with the topological structure of the distribution network, cascading failure assessment is performed to obtain the risk path, and the set of potential fault-inducing nodes is screened. The fault propagation analysis is performed to obtain the set of cascading failure nodes and the distribution network fault area. Step 4: Analyze the fault area of ​​the distribution network and obtain the priority repair line sequence based on the fault area of ​​the distribution network.

2. A method for evaluating power quality of a distribution network according to claim 1, characterized in that: The process of obtaining the voltage sag depth and voltage sag duration is as follows: Set up several collection points on the distribution network line, and obtain voltage data at each collection point when a fault event occurs in the distribution network; The collected voltage data is transmitted to the data processing platform in real time for integration and processing to obtain a voltage data sequence; Traverse the voltage data sequence, obtain the minimum voltage value during the transient period, calculate the difference between the rated voltage and the minimum voltage value, and obtain the voltage sag depth; The time point when the voltage starts to be lower than the normal fluctuation value and the time point when the voltage recovers to the normal fluctuation value are obtained, and the difference between the time point when the voltage recovers to the normal fluctuation value and the time point when the voltage starts to be lower than the normal fluctuation value is calculated to obtain the voltage sag duration.

3. A method for evaluating power quality of a distribution network according to claim 1, characterized in that: The process of obtaining the equipment risk data is as follows: Obtain the voltage sag depth and voltage sag duration, and set the voltage sag depth tolerance threshold and the sag duration tolerance threshold; Based on the equipment tolerance evaluation formula , where R represents the equipment tolerance assessment value, D represents the actual voltage sag depth, T represents the actual voltage sag duration, WD represents the weight of the voltage sag depth, and WT represents the weight of the voltage sag duration; Arrange the equipment tolerance capability evaluation values ​​in descending order to obtain an equipment tolerance capability evaluation value data sequence; Integrate the basic information of the equipment, transient state characteristic data, and tolerance capacity assessment result value information to form equipment risk data and store it.

4. A method for evaluating power quality of a distribution network according to claim 1, characterized in that: The process of obtaining the potential fault-causing node set is as follows: Analyze the topological structure of the distribution network and the equipment tolerance assessment value, obtain the comprehensive risk coefficient, set the comprehensive risk coefficient threshold, arrange the comprehensive risk coefficients in descending order, retain the comprehensive risk coefficients greater than the comprehensive risk coefficient threshold, and mark the line path corresponding to the comprehensive risk coefficient as a risk path; The starting node in the risk path is marked as a potential fault inducing node, and a set of potential fault inducing nodes is obtained.

5. A method for evaluating power quality of a distribution network according to claim 4, characterized in that: The process of obtaining the comprehensive risk coefficient is as follows: Obtaining a data sequence of equipment tolerance assessment values ​​and a topological structure of a distribution network; Based on the topological structure of the distribution network, obtain the line connection path; Based on any connection path, the device tolerance assessment values ​​on the connection path are summed and averaged to obtain the line path tolerance assessment mean value; Extract the maximum value of the equipment tolerance assessment value on the connection line; The comprehensive risk coefficient is calculated by taking the weighted sum of the mean value of the line path tolerance assessment and the maximum value of the equipment tolerance assessment.

6. A method for evaluating power quality of a distribution network according to claim 1, characterized in that: The process of obtaining the fault area of ​​the distribution network is as follows: Analyze the potential fault-causing node set, obtain the fault impact intensity coefficient, and obtain the equipment tolerance assessment value; Traverse each node of the risk path and compare the fault impact intensity coefficient with the equipment tolerance assessment value. If the fault impact intensity coefficient is greater than the equipment tolerance assessment value, it is marked as a cascading failure node. If the fault impact intensity coefficient is less than or equal to the equipment tolerance assessment value, it is marked as a non-cascading failure node. Get the set of nodes with cascading failures and divide the fault area of ​​the power grid.

7. A method for evaluating power quality of a distribution network according to claim 6, characterized in that: The process of obtaining the fault influence intensity coefficient is as follows: Obtain a set of potential fault-causing nodes, and based on any potential fault-causing node, obtain impedance values ​​and length values ​​of lines between adjacent nodes according to the direction of the connecting line; Set the typical impedance value and typical length value of the line; The impedance value of the line is calculated by ratio with the typical impedance value to obtain the impedance ratio, and the length value of the line is calculated by ratio with the typical length value to obtain the length ratio; The fault influence intensity coefficient is calculated based on the fault influence intensity coefficient calculation formula.

8. A method for evaluating power quality of a distribution network according to claim 1, characterized in that: The process of obtaining the priority repair line sequence is as follows: Analyze the nodes of the cascading failure nodes and the failure impact intensity coefficient to obtain the priority repair value; For any risk path containing a cascading failure node, sum up the node priority repair values ​​of all cascading failure nodes to obtain the total node priority repair value, and extract the maximum value of the node priority repair value; The total priority repair value is multiplied by the maximum priority repair value to obtain the line priority repair value; Arrange the line repair priority values ​​in descending order, which is the priority repair line order.

9. A method for evaluating power quality of a distribution network according to claim 8, characterized in that: The process of obtaining the priority repair value is as follows: Get the set of cascading failure nodes, and based on any cascading failure node, count the number of adjacent cascading failure nodes; Obtain the fault impact intensity coefficients of the cascading fault nodes respectively; For each cascading failure node, the number of adjacent cascading failure nodes and the failure impact intensity coefficient are multiplied to obtain the node priority repair value.

10. A power quality assessment system for a distribution network, characterized in that: The system is used to execute the method described in any one of claims 1 to 9, and the system comprises: Transient data processing module: collects voltage data of the distribution network during the transient period, and obtains transient state characteristic data based on the voltage state by processing the voltage data; Among them, transient state characteristic data include: voltage sag depth, voltage sag duration; Equipment tolerance assessment module: Calculate the equipment tolerance assessment value based on transient state characteristic data, evaluate the equipment tolerance, and obtain equipment risk data based on the assessment results; Fault area acquisition module: Based on the equipment risk data and combined with the topological structure of the distribution network, cascading fault assessment is performed, the set of potential fault-inducing nodes is screened, and fault propagation analysis is performed to obtain the set of cascading fault nodes and the fault area of ​​the distribution network; Fault handling module: Analyze the fault area of ​​the distribution network and obtain the priority repair line sequence.

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