A power quality assessment method and system for a distribution network

Abstract

The present invention relates to the technical field of power quality assessment, and discloses a power quality assessment method and system for a distribution network, including the following steps: Step 1: Collect voltage data of the distribution network during the transient period, and obtain transient state characteristic data through data processing; wherein, the transient state characteristic data includes: voltage sag depth, voltage sag duration; Step 2: Calculate the equipment tolerance assessment value based on the transient state characteristic data. The present invention can accurately assess the fault risk of the distribution network, reduce the situation of underestimating the fault risk due to ignoring key weak equipment, and based on the determination of the node set caused by potential faults and the fault chain nodes, targeted fault prevention and response measures can be formulated to improve the efficiency and effect of fault handling. By dividing the fault area of the distribution network, a fault handling strategy can be effectively formulated to improve the reliability and stability of the distribution network.

Description

Technical Field

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

[0002] With the continuous growth of power demand and the increasing complexity of power systems, distribution networks are facing numerous challenges, making power quality problems more prominent. The large-scale access of distributed energy sources, such as solar photovoltaic power generation and wind power generation, although alleviates the energy pressure to a certain extent, also brings new variables to the stability of the distribution network and power quality;

[0003] During the operation of the distribution network, due to various faults and equipment operations, etc., transient power quality problems will occur. These problems not only affect the normal operation of power equipment, shorten the service life of the equipment, but also have a serious impact on the user's power consumption experience, and may even trigger cascading failures, leading to large-scale power outages. Traditional power quality assessment methods often focus on steady-state analysis and lack comprehensive, accurate and timely assessment means for power quality problems in the transient process, and cannot meet the requirements of modern distribution networks for safety, reliability and stability. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for assessing the power quality of a distribution network to solve at least one of the above-mentioned problems of the prior art.

[0005] In a first aspect, the present invention provides a method for assessing the power quality of a distribution network, including the following steps:

[0006] 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;

[0007] Among them, the transient state characteristic data includes: voltage sag depth, voltage sag duration;

[0008] Step 2: Calculate the equipment tolerance evaluation value based on the transient state characteristic data, evaluate the tolerance of the equipment, and obtain equipment risk data based on the evaluation results;

[0009] Step 3: Based on the equipment risk data, conduct a cascading failure assessment in combination with the topological structure of the distribution network, obtain risk paths, screen the set of potential fault triggering nodes, conduct fault propagation analysis, obtain the set of cascading failure nodes, and obtain the fault area of the distribution network;

[0010] Step 4: Analyze based on the fault area of the distribution network to obtain the priority repair line sequence based on the fault area of the distribution network.

[0011] In a second aspect, the present invention provides a power quality assessment system for a distribution network, specifically including:

[0012] A transient data processing module: It collects voltage data of the distribution network during the transient period, and through processing the voltage data, obtains transient state characteristic data based on the voltage state.

[0013] Among them, the transient state characteristic data includes: voltage sag depth, voltage sag duration.

[0014] An equipment tolerance assessment module: Based on the transient state characteristic data, it calculates an equipment tolerance ability assessment value, evaluates the tolerance ability of the equipment, and obtains equipment risk data based on the evaluation results.

[0015] A fault area acquisition module: Based on the equipment risk data, it combines the topological structure of the distribution network to conduct a cascading fault assessment, screens a set of potential fault triggering nodes, conducts a fault propagation analysis, obtains a set of cascading fault nodes, and obtains the fault area of the distribution network.

[0016] A fault handling module: Based on the analysis of the fault area of the distribution network, it obtains the order of priority for repairing lines.

[0017] Advantages of the present invention:

[0018] Through high-precision monitoring equipment and data processing algorithms, the present invention can capture the transient voltage changes of the distribution network more accurately, thereby improving the accuracy of power quality assessment. By evaluating the equipment tolerance ability, potential equipment risks can be detected in a timely manner, enhancing the reliability and stability of the equipment.

[0019] The present invention can accurately assess the fault risk of the distribution network, reduce the situation of underestimating the fault risk due to neglecting key vulnerable equipment. Based on the determination of the set of potential fault triggering nodes and fault cascading nodes, targeted fault prevention and response measures can be formulated, improving the efficiency and effect of fault handling. By dividing the fault area of the distribution network, an effective fault handling strategy can be formulated, improving the reliability and stability of the distribution network.

[0020] Through the determination of the order of priority for repairing lines, the present invention can guide the repair personnel to quickly locate the most critical lines for repair, reducing blind operations. By determining the order of priority for repairing lines, resources can be allocated to the repair of the lines that most need it. For the lines with a high priority repair value, more professional personnel and advanced equipment can be deployed, reducing the waste of resources on the lines that have little impact on the overall recovery, improving the resource utilization efficiency, and giving priority to repairing the lines that are most critical for fault propagation control can effectively reduce the further spread of faults. Description of the Drawings

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0022] Figure 1 is a flowchart of a method for evaluating the power quality of a distribution network according to the present invention;

[0023] Figure 2 is a schematic structural diagram of a power quality evaluation system for a distribution network according to the present invention;

[0024] Figure 3 is a schematic structural diagram of a power quality evaluation device for a distribution network according to the present invention.

[0025] In the figure: 3. Computer device; 301. Processor; 302. Memory; 303. Computer program; Specific embodiments

[0026] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention. Embodiment 1

[0027] Figure 1 is a flowchart of a method for evaluating the power quality of a distribution network provided in Embodiment 1 of the present invention. The embodiments of the present invention are applicable to the situation of evaluating the power quality of a distribution network during a transient process. A method for evaluating the power quality of a distribution network can be executed by a power quality evaluation system for a distribution network. The power quality evaluation system for a distribution network can be implemented by software and / or hardware, and the power quality evaluation system for a distribution network can be configured in a power quality evaluation device for a distribution network. Optionally, a power quality evaluation device for a distribution network can be an electronic device, and the electronic device can be a notebook, a desktop computer, a smart tablet, etc. The embodiments of the present invention do not limit this.

[0028] As Figure 1 shown, a method for evaluating the power quality of a distribution network provided in the embodiments of the present invention specifically includes the following steps:

[0029] Step 1: Collect voltage data of the distribution network during the transient period through a monitoring device, and obtain transient state characteristic data through data processing;

[0030] Among them, the transient state characteristic data includes: the depth of voltage sag and the duration of voltage sag;

[0031] In some embodiments, a number of acquisition points are set on the distribution network line, and monitoring devices are installed at all the acquisition points;

[0032] Among them, the setting of the acquisition points includes but is not limited to: the outlet end of the substation of the distribution network, important distribution line nodes, and large user access points;

[0033] The selection of the monitoring device must have the function of voltage acquisition, including but not limited to: installing intelligent meters, power quality monitors, and fault recorders;

[0034] Set the sampling frequency of the monitoring device. Among them, the sampling frequency can be set to 5000Hz. Those skilled in the art can adjust it according to the change speed of the transient process of the distribution network. A higher sampling frequency helps to capture the rapidly changing voltage transient conditions more accurately;

[0035] When the monitoring device detects a fault event in the distribution network, it immediately automatically starts the high-speed data acquisition mode to acquire voltage data;

[0036] Among them, the fault events include but are not limited to: line short circuit, grounding, switch opening and closing, and transformer switching;

[0037] Through wireless communication technology or a wired communication network, the acquired voltage data is transmitted to the data processing platform in real time;

[0038] After the data processing platform receives the voltage data, it processes the voltage data to obtain a voltage data sequence ;

[0039] In this embodiment, the Kalman filtering algorithm is used to filter the voltage data to remove the noise generated by electromagnetic interference, measurement errors, etc., making the voltage data smoother and more accurate;

[0040] Specifically, the process of filtering the data by the Kalman filtering algorithm is an iterative process, mainly divided into two stages: prediction and update. The specific process is as follows:

[0041] Prediction stage: Based on the state transition equation of the system, use the optimal state estimate value at the previous moment to predict the state at the current moment. The formula is: , where A is the state transition matrix, which describes the transition relationship of the system state from one moment to the next moment, B is the control input matrix, is the control input vector. When there is no control input or the control input is not considered, the term can be omitted;

[0042] 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 the state estimation;

[0043] Update phase: Combine the predicted state estimation 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 of update of the new observation data to the state estimation;

[0044] Use the observation value , the Kalman gain And the predicted state To update the state estimation value at the current moment, the formula is , by multiplying the residual between the predicted value and the observation value by the Kalman gain, the predicted value is corrected to obtain a more accurate state estimation;

[0045] According to the Kalman gain And the predicted state estimation covariance matrix , update the state estimation covariance matrix at the current moment, the formula is , where I is the identity matrix, and the covariance update is used to provide an accurate covariance estimate for the next iteration;

[0046] Starting from the given initial state estimation value and covariance matrix, continuously repeat the prediction and update phases. As new observation data is continuously added, gradually optimize the estimation of the system state, remove the noise in the data, and make the voltage data smoother and more accurate;

[0047] Traverse the voltage data sequence , obtain the minimum voltage value during the transient period. Given the rated voltage, then calculate the difference between the rated voltage and the minimum voltage value to obtain the voltage sag depth;

[0048] 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 to obtain the voltage sag duration;

[0049] Step 2: Based on the transient state characteristic data, evaluate the tolerance of the equipment and obtain the equipment risk data;

[0050] In some embodiments, obtain the voltage sag depth and the voltage sag duration;

[0051] Set the tolerance threshold for the depth of voltage sag and the tolerance threshold for the duration of voltage sag. Those skilled in the art shall summarize and set them according to the equipment type by referring to the technical specification manual of the equipment, industry standards or relevant technical specifications;

[0052] Exemplarily, the tolerance depth of voltage sag for industrial motors is 70% of the rated voltage, and the tolerance time is 255 ms; while for some electronic devices with high requirements for power quality, such as servers, the tolerance depth of voltage sag is 85% of the rated voltage, and the tolerance time is 50 ms;

[0053] Based on the equipment tolerance ability evaluation formula , where R represents the equipment tolerance ability evaluation 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 a suitable form can be selected according to the actual situation;

[0054] In this embodiment, the form of f can be: , where DY represents the tolerance threshold of the voltage sag depth, and TY represents the tolerance threshold of the sag duration;

[0055] Arrange the equipment tolerance ability evaluation values in descending order to obtain the equipment tolerance ability evaluation value data sequence ;

[0056] Integrate the basic information of the equipment (such as equipment name, model, installation location, etc.), transient state characteristic data (voltage sag depth, sag duration), and tolerance ability evaluation result values to form equipment risk data;

[0057] Store the equipment risk data, and its storage format is: |Equipment Name|Model|Installation Location|Voltage Sag Depth|Sag Duration|Tolerance Ability Evaluation Value|;

[0058] The technical solution of this embodiment is: By monitoring the equipment to collect the voltage data of the distribution network during the transient period, and through data processing to obtain transient state characteristic data such as voltage sag depth and duration. Then, based on these characteristic data, combined with the technical specifications of the equipment and the tolerance ability evaluation formula, evaluate the tolerance ability of the equipment to obtain equipment risk data;

[0059] Thus, through high-precision monitoring equipment and data processing algorithms, the transient voltage changes of the distribution network can be captured more accurately, thereby improving the accuracy of power quality evaluation. By evaluating the tolerance ability of the equipment, potential equipment risks can be discovered in time, enhancing the reliability and stability of the equipment. Embodiment Two

[0060] Based on the above embodiments, as Figure 1 shown, a power quality assessment method for a distribution network provided by an embodiment of the present invention specifically includes the following steps:

[0061] Step 3: Based on the equipment risk data, combine the topological structure of the distribution network to conduct a cascading failure assessment, screen the set of potential fault triggering nodes, and conduct a fault propagation analysis to obtain the fault area of the distribution network;

[0062] In some embodiments, obtain the data sequence of the equipment tolerance ability assessment value ;

[0063] Obtain the topological structure of the distribution network, wherein the topological structure of the distribution network is obtained through a GIS-based distribution network management system, and the geographical location information and connection relationship of each device are recorded in the GIS-based distribution network management system;

[0064] Based on the topological structure of the distribution network, obtain the line connection path;

[0065] Exemplarily, assume the topological structure of the distribution network includes a substation (denoted as Ss), two distribution transformers (denoted as Tt1 and Tt2 respectively), and four users (denoted as Uu1, Uu2, Uu3, Uu4 respectively);

[0066] The substation Ss is connected to the distribution transformer Tt1 through an overhead line (denoted as Ll1), and at the same time is connected to the distribution transformer Tt2 through another overhead line (denoted as Ll2).

[0067] The distribution transformer Tt1 supplies power to users Uu1 and Uu2 through a cable line (denoted as Cc1), and the specific connection is Tt1 - Cc1 - Uu1 and Tt1 - Cc1 - Uu2.

[0068] The distribution transformer Tt2 supplies power to users Uu3 and Uu4 through a cable line (denoted as Cc2), and the specific connection is Tt2 - Cc2 - Uu3 and Tt2 - Cc2 - Uu4;

[0069] In this example, the connection paths from the substation to each user are as follows:

[0070] Ss - Ll1 - Tt1 - Cc1 - Uu1;

[0071] Ss - Ll1 - Tt1 - Cc1 - Uu2;

[0072] Ss - Ll2 - Tt2 - Cc2 - Uu3;

[0073] Ss - Ll2 - Tt2 - Cc2 - Uu4;

[0074] Based on any one connection path, sum up the device tolerance evaluation values on the connection path and take the average to obtain the average evaluation value of the line path tolerance;

[0075] Extract the maximum value of the device tolerance evaluation values on the connection line;

[0076] Perform a weighted summation process on the average evaluation value of the line path tolerance and the maximum value of the device tolerance evaluation value to calculate the comprehensive risk coefficient. Among them, the weight value of the total evaluation value of the line path tolerance is 0.47, and the weight value of the maximum value of the device tolerance evaluation value is 0.53;

[0077] It should be noted that the comprehensive risk coefficient performs a weighted summation on the total evaluation value of the line path tolerance and the maximum value of the device tolerance evaluation value, taking into account both the overall risk tolerance level of the devices on the path and the influence of the single weakest device link. For example, on a connection path, even if the overall device tolerance is acceptable, but there is a key device with extremely low tolerance, the comprehensive risk coefficient can accurately reflect this situation and reduce the underestimation of the failure risk due to neglecting the key weak devices;

[0078] Set the comprehensive risk coefficient threshold, where the comprehensive risk coefficient threshold is set by those skilled in the art based on historical experimental data and work experience;

[0079] Arrange the comprehensive risk coefficients in descending order, retain the comprehensive risk coefficients greater than the comprehensive risk coefficient threshold, and mark the line paths corresponding to the comprehensive risk coefficients as risk paths;

[0080] Mark the starting nodes in the risk paths as potential fault triggering nodes, and obtain the set of potential fault triggering nodes;

[0081] Based on the set of potential fault triggering nodes, conduct fault propagation analysis;

[0082] Based on any one potential fault triggering node, in the direction of the connection line, respectively obtain the impedance value and length value of the line between adjacent nodes;

[0083] 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 those skilled in the art according to the topology of the distribution network. For example, in a 10 kV distribution network, the impedance value per kilometer of a common overhead line is about 0.3 + j0.4 Ω / km. If most of the line lengths in this distribution network are between 1 - 10 km, the impedance value (1.5 + j2 Ω) of a 5 km line can be selected as the typical impedance value. If most of the line lengths in the distribution network are concentrated between 3 - 7 km, 5 km can be selected as the typical length value;

[0084] Calculate the ratio of the impedance value of the line to the typical impedance value to obtain the impedance ratio, and calculate the ratio of the length value of the line to the typical length value to obtain the length ratio;

[0085] Calculate the fault impact intensity coefficient based on the fault impact intensity coefficient calculation formula;

[0086] It should be noted that both the impedance ratio and the length ratio are inversely proportional to the fault intensity coefficient;

[0087] Exemplarily, the calculation process of the fault impact intensity coefficient is as follows:

[0088] For a series circuit, the calculation formula for the fault impact intensity coefficient IQ is: , where represents the evaluation value of the equipment tolerance capacity of the node caused by the potential fault, zk represents the impedance ratio, and xc represents the length ratio;

[0089] For a parallel circuit, the calculation formula for the fault impact intensity coefficient IQ is: , where represents the evaluation value of the equipment tolerance capacity of the node caused by the potential fault, xc represents the length ratio, represents the current distribution coefficient, k represents that there are k parallel branches connected to different nodes, represents the impedance ratio of the jth branch, j = 1, 2,..., k;

[0090] Traverse each node of the risk path, compare the fault impact intensity coefficient with the evaluation value of the equipment tolerance capacity. If the fault impact intensity coefficient is greater than the evaluation value of the equipment tolerance capacity, it is marked as a cascading fault node. If the fault impact intensity coefficient is less than or equal to the evaluation value of the equipment tolerance capacity, it is marked as a non-cascading fault node;

[0091] Obtain the set of cascading fault nodes and delimit the fault area of the distribution network;

[0092] The technical solution of this embodiment is as follows: Based on the device risk data and the GIS topology structure of the distribution network, by calculating the weighted comprehensive risk coefficient of the average value of the line path tolerance capacity evaluation and the maximum value of the device tolerance capacity evaluation, the set of potential fault triggering nodes is screened out, and then the fault propagation analysis is carried out. According to the comparison between the fault impact intensity coefficient and the device tolerance capacity evaluation value, the fault chain nodes are determined, and the distribution network fault area is delimited;

[0093] Thus, 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 evaluated more accurately, reducing the situation of underestimating the fault risk due to neglecting key weak devices. Based on the determination of the set of potential fault triggering nodes and the fault chain nodes, targeted fault prevention and response measures can be formulated, improving the efficiency and effect of fault handling. By delimiting the distribution network fault area, an effective fault handling strategy can be formulated, improving the reliability and stability of the distribution network;

[0094] And when a fault occurs, the distribution network fault area can be delimited relatively quickly, guiding the repair personnel 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 the power consumption of users. Embodiment Three

[0095] Based on the above embodiments, as Figure 1 shown, a method for evaluating the power quality of a distribution network provided by an embodiment of the present invention specifically includes the following steps:

[0096] Step Four: Analyze based on the distribution network fault area to obtain the order of priority for repairing lines;

[0097] In some embodiments, obtain the set of cascading fault nodes. Based on any one cascading fault node, count the number of its adjacent cascading fault nodes;

[0098] Respectively obtain the fault impact intensity coefficients of the cascading fault nodes;

[0099] For each cascading fault node, calculate the product of the number of its adjacent cascading fault nodes and the fault impact intensity coefficient to obtain the node priority repair value;

[0100] For any risk path containing cascading fault nodes, sum up the node priority repair values of all cascading fault nodes to obtain the total node priority repair value, and extract the maximum value of the node priority repair value;

[0101] Calculate the product of the total priority repair value and the maximum value of the priority repair to obtain the line priority repair value;

[0102] Arrange the line priority repair values in descending order, which is the order of priority for repairing lines;

[0103] Thus, it can guide the emergency repair personnel to quickly locate the most critical lines for repair, reducing blind operations. For example, in the event of a large-scale power outage, without a priority order, the emergency repair personnel may waste time on some non-critical lines. After determining the priority order of the lines to be repaired, they can directly work on the lines that play a key role in restoring the power grid operation, significantly shortening the fault handling time and restoring power supply as soon as possible;

[0104] The technical solution of this embodiment is as follows: First, obtain the set of cascading fault nodes. For any one of the cascading fault nodes, count the number of its adjacent cascading fault nodes with the help of the distribution network topology structure information, and combine the calculation of the fault impact intensity coefficient to obtain the node priority repair value. For each risk path containing cascading fault nodes, sum up the node priority repair values of all cascading fault nodes to obtain the total node priority repair value, extract the maximum value among them, then multiply the total priority repair value by the maximum priority repair value to obtain the line priority repair value, and arrange the priority repair values of all lines from largest to smallest, thereby determining the priority order of the lines to be repaired;

[0105] Thus, when the fault handling resources and time are limited, the priority order of the lines to be repaired can guide the emergency repair personnel to quickly locate the most critical lines for repair, reducing blind operations. By determining the priority order of the lines to be repaired, resources can be allocated to the most needed line repairs. For lines with a high priority repair value, more professional personnel and advanced equipment can be deployed, reducing resource waste on lines that have less impact on the overall restoration, improving resource utilization efficiency, and giving priority to repairing the lines that are most critical for fault propagation control, which can effectively reduce the further spread of the fault. Embodiment 4

[0106] Based on the above embodiments, as Figure 2 shown, a distribution network power quality assessment system provided by an embodiment of the present invention specifically includes:

[0107] Transient data processing module: Through monitoring devices, collect voltage data of the distribution network during the transient period, and through data processing, obtain transient state characteristic data;

[0108] Among them, the transient state characteristic data includes: voltage sag depth, voltage sag duration;

[0109] Equipment tolerance assessment module: Based on the transient state characteristic data, evaluate the tolerance of the equipment to obtain equipment risk data;

[0110] Fault area acquisition module: Based on the equipment risk data, combine the topology structure of the distribution network for cascading fault assessment, screen the set of potential fault triggering nodes, and conduct fault propagation analysis to obtain the fault area of the distribution network;

[0111] Fault handling module: Analyze based on the fault area of the distribution network to obtain the order of lines to be repaired first. Embodiment 5

[0112] As Figure 3 shown, an embodiment of the present invention further provides a computer device 3, including: a memory 302, a processor 301, and a computer program 303 stored on the memory 302. When the computer program 303 is executed on the processor 301, it implements a method for evaluating the power quality of a distribution network as described in any one of the above methods.

[0113] The computer device 3 may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The computer device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art can understand;

[0114] Figure 3 merely examples of the computer device 3, which do not constitute a limitation on the computer device 3. It may include more or fewer components than shown in the figure, or combine some components, or different components. For example, it may also include input / output devices, network access devices, etc.

[0115] The so-called processor 301 may be a central processing unit (CPU), and the processor 301 may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0116] 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 the internal storage unit and the external storage device of the computer device 3. The memory 302 is used to store an operating system, application programs, a BootLoader, data, and other programs, such as program codes of the computer program. The memory 302 may also be used to temporarily store data that has been output or will be output. Embodiment Six

[0117] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, it implements a power quality assessment method for a distribution network as described in any one of the above methods.

[0118] 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, to implement all or part of the processes in the above embodiment methods of the present application, a computer program can be used to instruct relevant hardware to complete. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium may at least include: any entity or device that can carry the computer program code to the photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk, or an optical disc, etc. In some jurisdictions, according to legislation and patent practice, the computer-readable medium may not be an electrical carrier signal and a telecommunication signal.

[0119] In the above embodiments, the descriptions of the various embodiments have their own emphases. For parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0120] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0121] In the embodiments disclosed in this application, it should be understood that the disclosed device / terminal device and method can be implemented in other ways. For example, the device / terminal device embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, 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 displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the device or unit can be in electrical, mechanical or other forms.

[0122] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0123] The above formulas are all dimensionless and take their numerical calculations. The formulas are obtained by collecting a large amount of data for software simulation to get a formula that is closest to the actual situation. The preset parameters in the formulas are set by technicians in this field according to the actual situation.

[0124] The above has described a detailed description of an embodiment of the present invention, but the content described is only the preferred embodiment of the present invention and cannot be considered to be used to limit the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the application of the present invention should still fall within the scope covered by the patent of the present invention.

Claims

1. A method for evaluating the power quality of a distribution network, characterized in that, It includes the following steps: Step 1: Collect the voltage data of the distribution network during the transient period, and obtain the transient state characteristic data based on the voltage state by processing the voltage data; Among them, the transient state characteristic data includes: voltage sag depth and voltage sag duration; Step 2: Based on the transient state characteristic data, calculate the equipment tolerance evaluation value, evaluate the tolerance ability of the equipment, and obtain the equipment risk data based on the evaluation result; The acquisition process of the equipment risk data is as follows: Obtain the voltage sag depth and the voltage sag duration, and set the voltage sag depth tolerance threshold and the sag duration tolerance threshold; Equipment tolerance capacity evaluation formula , where R represents the equipment tolerance capacity evaluation 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 evaluation values in descending order to obtain the equipment tolerance evaluation value data sequence; Integrate the basic information of the equipment, the transient state characteristic data, and the tolerance ability evaluation result value information to form the equipment risk data and store it; Step 3: Based on the equipment risk data, combine the topological structure of the distribution network to conduct a cascading fault assessment, obtain the risk path, screen the set of potential fault triggering nodes, conduct a fault propagation analysis, obtain the cascading fault node set, and obtain the distribution network fault area; Step 4: Analyze based on the distribution network fault area to obtain the priority repair line sequence based on the distribution network fault area.

2. The power quality assessment method for a distribution network according to claim 1, wherein The acquisition process of the voltage sag depth and the voltage sag duration is as follows: Set several acquisition points on the distribution network line. When a fault event occurs in the distribution network, obtain the voltage data of each acquisition point; Transmit the collected voltage data to the data processing platform for real-time integration and processing to obtain the 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 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 returns to the normal fluctuation value, and calculate the difference between the time point when the voltage returns to the normal fluctuation value and the time point when the voltage starts to be lower than the normal fluctuation value to obtain the voltage sag duration.

3. A power quality assessment method for a distribution network according to claim 1, characterized in that, The acquisition process of the set of potential fault triggering nodes is as follows: Analyze the topological structure of the distribution network and the equipment tolerance evaluation 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 paths corresponding to the comprehensive risk coefficients as risk paths; Mark the starting nodes in the risk paths as potential fault triggering nodes to obtain the set of potential fault triggering nodes.

4. A power quality assessment method for a distribution network according to claim 3, characterized in that The acquisition process of the comprehensive risk coefficient is as follows: Obtain the equipment tolerance evaluation value data sequence and the topological structure of the distribution network; Based on the topological structure of the distribution network, obtain the line connection path; Based on any one connection path, sum and average the equipment tolerance evaluation values on the connection path to obtain the average line path tolerance evaluation value; Extract the maximum value of the equipment tolerance evaluation values on the connection line; Perform a weighted summation process on the average line path tolerance evaluation value and the maximum value of the equipment tolerance evaluation value to calculate the comprehensive risk coefficient.

5. The power quality assessment method for a distribution network according to claim 1, characterized in that, The acquisition process of the distribution network fault area is as follows: Analyze the set of nodes caused by potential faults to obtain the fault impact intensity coefficient, and obtain the evaluation value of the equipment tolerance ability; Traverse each node of the risk path, compare the fault impact intensity coefficient with the evaluation value of the equipment tolerance ability. If the fault impact intensity coefficient is greater than the evaluation value of the equipment tolerance ability, mark it as a cascading fault node; if the fault impact intensity coefficient is less than or equal to the evaluation value of the equipment tolerance ability, mark it as a non-cascading fault node; Obtain the set of cascading fault nodes and delimit the fault area of the distribution network.

6. The power quality assessment method for a distribution network according to claim 5, characterized in that The process of obtaining the fault impact intensity coefficient is as follows: Obtain the set of nodes caused by potential faults. Based on any one of the nodes caused by potential faults, respectively obtain the impedance value and length value of the line between adjacent nodes according to the direction of the connecting line; Set the typical impedance value and typical length value of the line; Calculate the ratio of the impedance value of the line to the typical impedance value to obtain the impedance ratio, and calculate the ratio of the length value of the line to the typical length value to obtain the length ratio; Based on the fault impact intensity coefficient calculation formula, calculate the fault impact intensity coefficient.

7. A power quality assessment method for a distribution network according to claim 1, characterized in that The process of obtaining the order of priority for repairing lines is as follows: Analyze the nodes of the cascading fault nodes and the fault impact intensity coefficient to obtain the priority repair value; For any risk path containing cascading fault nodes, sum up the node priority repair values of all cascading fault nodes to obtain the total node priority repair value, and extract the maximum value of the node priority repair value; Perform a product calculation on the total priority repair value and the maximum value of the priority repair to obtain the line priority repair value; Arrange the line priority repair values in descending order, which is the order of priority for repairing lines.

8. A power quality assessment method for a distribution network according to claim 7, characterized in that The process of obtaining the priority repair value is as follows: Obtain the set of cascading fault nodes. Based on any one of the cascading fault nodes, count the number of adjacent cascading fault nodes; Respectively obtain the fault impact intensity coefficients of the cascading fault nodes; For each cascading fault node, perform a product calculation on the number of adjacent cascading fault nodes and the fault impact intensity coefficient to obtain the node priority repair value.

9. A power quality assessment system for a distribution network, characterized in that, This system is used to execute the method described in any one of claims 1-8 above. This system includes: Transient data processing module: 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, the transient state characteristic data includes: voltage sag depth, voltage sag duration; Equipment tolerance evaluation module: Based on the transient state characteristic data, calculate the evaluation value of the equipment tolerance ability, evaluate the tolerance ability of the equipment, and obtain equipment risk data based on the evaluation results; 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 sag duration tolerance threshold; Equipment tolerance capacity evaluation formula , where R represents the equipment tolerance capacity evaluation 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 evaluation values of the equipment tolerance ability in descending order to obtain the equipment tolerance ability evaluation value data sequence; Integrate the basic information of the equipment, transient state characteristic data, and tolerance ability evaluation result value information to form equipment risk data and store it; Fault area acquisition module: Based on device risk data, combined with the topological structure of the distribution network, conduct cascading fault assessment, screen the set of potential fault triggering nodes, perform fault propagation analysis, obtain the set of cascading fault nodes, and obtain the fault area of the distribution network; Fault handling module: Analyze based on the fault area of the distribution network to obtain the order of priority for repairing lines.

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