Discrete distribution of power distribution network automation switch optimization method

Abstract

This invention relates to the field of distribution networks, and more particularly to a discrete distribution network automation switch placement optimization method. The method includes: acquiring the switches and their attributes in the main feeder of the distribution network; dividing the main feeder into minimum outage units based on a single-line diagram to obtain the number of users affected by each switch; acquiring historical switch fault outage data; calculating the fault rate and fault duration of each switch under each attribute factor based on the historical switch fault outage data and the attribute factors of each switch, and constructing a fault standard table; constructing a reliability simulation model based on the fault standard table; comparing the reliability simulation values ​​with preset theoretical reliability target values ​​and calculating the line modification weight for each line using a grid ledger; and calculating the switch modification weight based on the line modification weight and switch attributes, thereby optimizing switches with high modification weights. This invention offers high accuracy and enables precise operation and maintenance.

Description

Technical Field

[0001] This invention relates to the field of power distribution networks, and more particularly to a method for optimizing the placement of discrete power distribution network automation switches. Background Technology

[0002] Currently, the insufficient deployment of remote control terminals in the power distribution network results in a small size of equipment capable of remote operation, hindering a significant improvement in the practical application of power distribution automation. Furthermore, relying on manual offline data collection and statistics for terminal deployment and other business needs is inefficient, inaccurate, and lacks real-time performance. This leads to a lack of precise coordination in the construction and operation of power distribution automation, resulting in limited regional application effectiveness. Summary of the Invention

[0003] The purpose of this invention is to provide a discrete distribution network automation switch placement optimization method. Based on discrete events, the method simulates the switches and automatically identifies the switches that need to be modified, achieving high accuracy and precise operation and maintenance.

[0004] To solve the above technical problems, the technical solution of this invention is: a method for optimizing the placement of discrete distribution network automation switches, comprising:

[0005] Step 1: Obtain the switches and their attributes in the main feeder of the distribution network. Divide the main feeder of the distribution network into the smallest outage unit according to the single line diagram to obtain the number of users affected by the switches.

[0006] The switch attributes include switch location, switch type, and switch zone level; specifically:

[0007] Identify the switch positions on each line based on the single-line diagram of the power distribution network feeder;

[0008] Switches are classified into types based on automated switch ledgers and switch locations;

[0009] Identify the switch zone level based on the grid ledger;

[0010] Step 2: Obtain historical switch failure power outage data to obtain the number of power outages and their duration;

[0011] Step 3: Based on historical switch failure and power outage data and the switch attribute factors from Step 1, calculate the switch failure rate and failure duration under each attribute factor, and construct a fault standard table.

[0012] Step 4: Construct a reliability simulation model based on the fault standard table: Based on the switches obtained in Step 1, match the fault standard table and combine it with the number of users affected by the switches in Step 1. Calculate the annual number of users affected by power outages for each switch under each line and the total number of users affected by power outages for each line to obtain the annual average number of power outage events, and thus calculate the reliability simulation value of a single line.

[0013] Step 5: Compare the reliability simulation values ​​with the preset reliability theoretical target values ​​and calculate the line modification weight for each line using the grid ledger.

[0014] Step 6: Calculate the switch modification weight based on the line modification weight and switch attributes, and then optimize the switches with large modification weights.

[0015] Furthermore, in step 1, the switch positions include tie, section, branch, and boundary. The method for identifying the switch positions is as follows: based on the line topology of the single-line diagram of the distribution network feeder, the feeder trunk and branches are classified. Switches belonging to the trunk line are section switches. If a section switch is connected to another trunk line, it is a tie switch. Switches belonging to the branch line are branch switches. If a branch switch is the final stage, i.e., located in front of the user, it is a boundary switch.

[0016] In step 1, the switch types include ordinary switches, two-remote switches, and three-remote switches. The method for classifying switch types is as follows: extract the switch set, match it with the distribution network automation switch ledger, and define the switch type with labels. Unmatched switches are ordinary switches, and other switches are classified as two-remote or three-remote switches according to the distribution network automation switch ledger.

[0017] In step 1, the switch area level includes level A, level B and level C; the method for identifying the switch area level is: the grid ledger is a grid level division method that includes the division of the line to which the switch belongs and the grid to which the line belongs. Based on the grid level division, the switch area level is divided into level A, level B and level C.

[0018] Furthermore, in step 1, the specific method for obtaining the number of users affected by the switch is as follows: based on the topology of the line, recursively divide the topology into N smallest power supply units according to the current direction of the normal operation of the power grid, and simulate the power outage of each switch to obtain the corresponding number of affected users, which is the number of users affected by the switch.

[0019] Furthermore, in step 1, the specific method for obtaining the number of users affected by the switch is as follows:

[0020] Based on the line topology, we first recursively proceed in the direction of current during normal grid operation, and divide the topology into N smallest power supply units according to segmented switches or branch switches. We then simulate a power outage for each switch and obtain the corresponding number of affected users, which is the number of users affected by the first switch.

[0021] Meanwhile, considering the situation of interconnected power supply, the current direction of the interconnected operator is recursively followed to obtain the corresponding number of affected users, which is the number of users affected by the second switch.

[0022] Set the impact coefficient for normal operations and the impact coefficient for communication operations;

[0023] Calculate the number of users affected by the switch: Number of users affected by the switch = Number of users affected by the first switch * Normal operation impact coefficient + Number of users affected by the second switch * Inter-operation operation impact coefficient.

[0024] Further, step 2 specifically involves: obtaining historical battery outage information, i.e., historical switch failure power outage data. The historical battery outage information includes a main table and a sub-table. The main table includes the outage line, the start time of the outage, the end time of the outage, and the reason for the outage. The sub-table includes the outage equipment, the start time of the outage, and the end time of the outage.

[0025] Based on the cause of the power outage, obtain the specific power outage equipment and the power outage duration of the corresponding sub-table. The power outage duration is the difference between the power outage end time and the power outage start time. Divide the power outage equipment into the smallest power outage unit, remove the fault data of a single distribution transformer, and use the maximum power outage duration of a single record as the power outage duration of the switch.

[0026] Furthermore, step 3 specifically includes:

[0027] Step 3.1: Based on the attribute factors of the switch attributes in Step 1, calculate the number of power outages Cs and the power outage duration Sc for each type of switch fault;

[0028] Step 3.2: Summarize the number of power outages and the duration of all switches to obtain the total number of power outages and the total duration of power outages for each type, and calculate the annual average failure rate and average failure duration;

[0029] Wherein, the annual average failure rate = total number of power outages / N (years) * total number of switches; N indicates that the selected historical switch failure power outage data is from N years of data;

[0030] Wherein, average fault duration = total power outage duration / total number of power outages;

[0031] Step 3.3: Construct a fault standard table based on the annual average failure rate and annual average failure duration of the switch under each attribute factor.

[0032] Furthermore, step 4 specifically includes:

[0033] Step 4.1: Based on the switches obtained in Step 1, match them to the fault standard table to obtain the annual average failure rate and average power outage duration for each switch;

[0034] Step 4.2: Iterate through each major feeder and calculate the annual number of users affected by each switch on each feeder based on the number of users affected by the switch.

[0035] Among them, the number of households experiencing power outages per year for each switch = the average annual failure rate of each switch * the number of users affected by the switch * the average duration of the failure;

[0036] Step 4.3: Summing up the total number of households affected by power outages for each line based on the hierarchical relationship between lines and switches in the line topology path;

[0037] Step 4.4: Calculate the annual average number of power outage events to obtain the reliability simulation value for each line;

[0038] Among them, the average annual power outage events = total number of households experiencing power outages / total number of users;

[0039] The reliability simulation value is calculated as 1 - (annual average power outage events / 365 * 24).

[0040] Furthermore, step 5 specifically includes:

[0041] Step 5.1: Preset the theoretical target value for reliability;

[0042] Step 5.2: Calculate the target weight for each line; Target weight for each line = Theoretical reliability target value - Simulated reliability value;

[0043] Step 5.3: Calculate the line renovation weight based on the line area level weight and the line target weight; whereby the line area level weight is a preset value based on the line area level in the grid ledger.

[0044] Furthermore, step 6 specifically includes:

[0045] Step 6.1: Obtain all ordinary switches and remote control switches for each line under the weighting coefficient of each line;

[0046] Step 6.2: Calculate the switch weight coefficient for each obtained switch. Switch weight coefficient = number of households when the switch is out of power / total number of households when the current line is out of power * line renovation weight;

[0047] Step 6.3: Calculate the switch modification weight based on the switch position weight and the switch weight coefficient; whereby the switch position weight is a preset value based on the switch positions in the grid ledger.

[0048] Furthermore, the optimization method also includes the following steps:

[0049] Step 7: Construct constraints to modify switches with high modification weights under limited modification cost constraints.

[0050] The present invention has the following beneficial effects:

[0051] I. This invention obtains the switch and its attributes, constructs a fault standard table based on historical switch fault outage data and switch data, and builds a reliability simulation model based on the fault standard table to realize the simulation calculation of line switch reliability. This invention generates discrete events through the constructed fault standard table to simulate random faults in line switches, thereby realizing reliability calculation under random faults.

[0052] Second, this invention uses simulation calculations to determine the reliability of lines and switches, identify the switches on lines that require priority for remote control upgrades, and calculates the switches or lines that most urgently need upgrades with the goal of maximizing power supply reliability under limited economic investment. It is highly efficient, accurate, and real-time, enabling precise operation and maintenance, and has achieved significant results in regional applications. Attached Figure Description

[0053] Figure 1 This is an overall flowchart of the method of the present invention;

[0054] Figure 2 This is a topology diagram showing the number of users affected by the switch in an embodiment of the present invention. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0056] Please refer to Figure 1 This invention is a method for optimizing the placement of discrete switch points in distribution network automation, comprising:

[0057] Step 1: Obtain the switches and their attributes in the main feeder of the distribution network. Divide the main feeder of the distribution network into the smallest outage unit according to the single line diagram to obtain the number of users affected by the switches.

[0058] Switch attributes include switch location, switch type, and switch zone level; specifically:

[0059] Identify the switch positions on each line according to the single-line diagram of the distribution network feeder. Switch positions include interconnection, section, branch, and boundary. The method for identifying switch positions is as follows: based on the line topology of the single-line diagram of the distribution network feeder, classify the feeder trunk and branches. Switches belonging to the trunk line are section switches. If a section switch is connected to another trunk line, it is an interconnection switch. Switches belonging to the branch line are branch switches. If a branch switch is the final stage, i.e., located before the user, it is a boundary switch.

[0060] Switches are classified into switch types based on the automated switch ledger and switch location. Switch types include ordinary switches, two-remote switches, and three-remote switches. The method for classifying switch types is as follows: extract the switch set, match it with the distribution network automated switch ledger, and define the switch type label. Unmatched switches are ordinary switches, and other switches are classified into two-remote switches or three-remote switches according to the distribution network automated switch ledger.

[0061] The switch area level is identified based on the grid ledger; the switch area level includes level A, level B and level C; the method for identifying the switch area level is as follows: the grid ledger includes the grid level division of the line to which the switch belongs and the grid to which the line belongs, and the switch area level is divided into level A, level B and level C according to the grid level division.

[0062] The specific method for obtaining the number of users affected by the switch is as follows: In this embodiment, "users" specifically refers to distribution transformers or medium-voltage users, and the number of affected users is calculated according to the power flow direction; in this embodiment, refer to... Figure 2 Based on the line topology, recursively divide the topology into N smallest power supply units according to the current direction of normal grid operation, using the sectionalizing switches or branch switches of the main feeder. Figure 2 (where N is 5), simulate a power outage for each switch and obtain the number of users affected, which is the number of users affected by the switch; Figure 2 For example, if 5 users are connected to switch K1, then the number of users affected by the switch is 5. If 2 users are connected to switch T2, then the number of users affected by the switch is 2. The number of affected users is determined by dividing the switch into the smallest power outage unit. That is, if this switch is turned off, all users connected to it will lose power.

[0063] In some other embodiments, the power grid is normally in normal operation mode, but when the power grid is under emergency repair, the operation mode is interconnected. In order to improve the accuracy of obtaining the number of users affected by the switch, in other embodiments, the specific method for obtaining the number of users affected by the switch is as follows:

[0064] Based on the line topology, we first recursively proceed in the direction of current during normal grid operation, and divide the topology into N smallest power supply units according to segmented switches or branch switches. We then simulate a power outage for each switch and obtain the corresponding number of affected users, which is the number of users affected by the first switch.

[0065] Meanwhile, considering the situation of interconnected power supply, the current direction of the interconnected operator is recursively followed to obtain the corresponding number of affected users, which is the number of users affected by the second switch.

[0066] Set the influence coefficients for normal operations and communication operations; the influence coefficient for normal operations can be set to 80%, and the influence coefficient for communication operations can be set to 20%.

[0067] Calculate the number of users affected by the switch: Number of users affected by the switch = Number of users affected by the first switch * Normal operation impact coefficient + Number of users affected by the second switch * Inter-operation operation impact coefficient.

[0068] This method involves multiplying the number of users in normal operation and contact operation by the corresponding percentages to calculate the number of users affected by each switch in each operating mode, and finally summing them up to obtain the number of users affected by each switch.

[0069] Step 2: Obtain historical switch fault outage data to obtain the number of outages and their duration. In this embodiment, Step 2 specifically involves obtaining the city's medium-voltage outage information for the past three years, i.e., historical switch fault outage data for the past three years, through the distribution network reliability system. The historical outage information includes a main table and a sub-table. The main table includes the outage line, the outage start time, the outage end time, and the outage reason. The sub-table includes the outage equipment, the equipment outage start time, and the equipment outage end time.

[0070] Based on the cause of the power outage, obtain the specific power outage equipment and the power outage duration of the corresponding sub-table. The power outage duration is the difference between the power outage end time and the power outage start time, in minutes. Divide the power outage equipment into the smallest power outage unit, remove the fault data of a single distribution transformer, and use the maximum power outage duration of a single record as the power outage duration of the switch.

[0071] Step 3: Based on historical switch fault outage data and the switch attribute factors from Step 1, calculate the fault rate and fault duration of the switch under each attribute factor, and construct a fault standard table; Step 3 specifically involves:

[0072] Step 3.1: Based on the switch attributes in Step 1, calculate the number of power outages Cs and the outage duration Sc for each type of switch fault; that is, according to the switch attributes, obtain the total power outage data for the past three years in the city through the distribution network automation system, and then classify them according to the switch attributes, namely switch location, switch type, and power supply area level, to obtain the number of power outages and the outage duration for all switches.

[0073] Step 3.2: According to the switch attributes, summarize the number of power outages and the duration of power outages for all switches in the city over the past three years by type, obtain the total number of power outages and the total duration of power outages for each type, and calculate the annual average failure rate and average failure duration;

[0074] Wherein, the annual average failure rate = total number of power outages / N (years) * total number of switches; N represents the selected historical switch failure power outage data for N years; in this embodiment, N = 3;

[0075] Wherein, average fault duration = total power outage duration / total number of power outages;

[0076] Step 3.3: Based on the annual average failure rate and annual average failure duration of the switch under each attribute factor, construct a fault standard table to form the following maximum permutation and combination table.

[0077]

[0078] Step 4: Construct a reliability simulation model based on the fault standard table: Based on the switches obtained in Step 1, match the fault standard table and combine it with the number of users affected by the switches in Step 1. Calculate the annual number of users experiencing power outages for each switch on each line and the total number of users experiencing power outages on each line to obtain the annual average number of power outage events, thereby calculating the reliability simulation value for a single line. In this embodiment, machine learning is used for simulation calculations, which are highly consistent with historical data. Machine learning is an existing data processing method and will not be elaborated here. Step 4 specifically involves:

[0079] Step 4.1: Based on the switches obtained in Step 1, match them to the fault standard table to obtain the annual average failure rate and average power outage duration for each switch;

[0080] Step 4.2: Iterate through each major feeder and calculate the annual number of users affected by each switch on each feeder based on the number of users affected by the switch.

[0081] Among them, the number of households experiencing power outages per year for each switch = the average annual failure rate of each switch * the number of users affected by the switch * the average duration of the failure (unit converted to hours);

[0082] Step 4.3: Summing up the total number of households affected by power outages for each line based on the hierarchical relationship between lines and switches in the line topology path;

[0083] Step 4.4: Calculate the annual average number of power outage events to obtain the reliability simulation value for each line;

[0084] Among them, the average annual power outage events = total number of households experiencing power outages / total number of users;

[0085] The reliability simulation value is calculated as 1 - (annual average power outage events / 365 * 24).

[0086] Step 5: Compare the reliability simulation values ​​with the preset reliability theoretical target values, and calculate the line modification weight for each line using the grid ledger; Step 5 specifically involves:

[0087] Step 5.1: Preset the theoretical reliability target value; in this embodiment, the theoretical reliability target value is set to 99.9%;

[0088] Step 5.2: Calculate the target weight for each line; Target weight for each line = Theoretical reliability target value - Simulated reliability value;

[0089] Step 5.3: Calculate the line renovation weight based on the line area level weight and the line target weight; wherein, the line area level weight is a preset value based on the line area level in the grid ledger. In this embodiment, the A level area is set to 10, the B level area is set to 8, and the C level area is set to 5.

[0090] Step 6: Calculate the switch modification weight based on the line modification weight and switch attributes, and then optimize switches with high modification weights; Step 6 specifically involves:

[0091] Step 6.1: Obtain all ordinary switches and remote control switches for each line under the weighting coefficient of each line;

[0092] Step 6.2: Calculate the switch weight coefficient for each obtained switch. Switch weight coefficient = number of households when the switch is out of power / total number of households when the current line is out of power * line renovation weight;

[0093] Step 6.3: Calculate the switch modification weight based on the switch position weight and the switch weight coefficient; wherein, the switch position weight is a preset value based on the switch position in the grid ledger; in this embodiment, the switch position is set to 10 for connection, 6 for segment, 3 for branch, and 1 for boundary.

[0094] Step 7: Construct constraints based on the annual investment amount / unit price of switch renovation, and renovate switches with high renovation weight under the constraint of limited renovation cost, so as to maximize the overall unit power supply reliability with limited investment.

[0095] This invention fully considers the reliability of power supply during the site planning and uses discrete mathematical algorithms to simulate and calculate line reliability. Discrete events refer to state changes that occur randomly only at discrete moments; in layman's terms, a power grid experiences random faults under normal operation. Discrete events include three characteristics: entity, attribute, and activity. Entity—the specific object that makes up the power grid (including the object of study and components); in this invention, the entity is a switch. Attribute—the characteristics of the entity (reflecting the entity's state and parameters); in this invention, the characteristics are the switch's switching attributes and the number of users affected by the switch. Activity—the state change of the entity over time (the process of changing between two consecutive states); in this invention, the activity is a power outage event of the switch. To simulate and calculate the reliability of line switches, it is necessary to describe the operating state of the line and the switch. Therefore, this invention constructs a reliability simulation model based on a fault standard table to generate discrete events, obtains the switches under simulated line state changes, and calculates the reliability of the line and switches through simulation to identify the switches on lines that require priority for remote control upgrades. With limited economic investment, it calculates the switches or lines that most urgently need upgrades with the goal of maximizing power supply reliability, achieving high efficiency and accuracy.

[0096] All parts not covered in this invention are the same as or implemented using existing technologies.

[0097] The above description, in conjunction with specific embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A discrete distribution network automation switch placement optimization method, characterized in that: including Step 1: Obtain each switch and its switch attributes in the large feeder of the distribution network, and divide them according to the single-line diagram of the large feeder of the distribution network by the minimum power outage unit to obtain the number of users affected by the switch; The switch attributes include switch location, switch type, and switch area level; specifically: Identify the switch location of the switch on each line according to the single-line diagram of the large feeder of the distribution network; Classify the switches based on the automatic switch ledger and the switch location to obtain the switch type; Identify the switch area level of the switch according to the grid ledger; Step 2: Obtain the historical switch fault power outage data to obtain the number of power outages and the power outage duration; Step 3: Based on the historical switch fault power outage data and each attribute factor of the switch attributes in Step 1, calculate the failure rate and failure duration of the switch under each attribute factor, and construct a failure standard table; Step 4: Construct a reliability simulation model according to the failure standard table: According to the switches obtained in Step 1, match the failure standard table and combine the number of users affected by the switch in Step 1 to calculate the annual power outage user-hours of each switch under each line and the total power outage user-hours of each line, so as to obtain the annual average power outage event, and then calculate the reliability simulation value of a single line; Step 5: Compare the reliability simulation value with the preset reliability theoretical target value and calculate the line renovation weight of each line in combination with the grid ledger; Step 6: Calculate the switch renovation weight according to the line renovation weight and the switch attributes, so as to optimize the switches with large switch renovation weights.

2. The discrete-based optimized method for distribution network automation switch placement according to claim 1, wherein: In Step 1, the switch location includes connection, sectioning, branching, and demarcation; the method for identifying the switch location is: According to the line topology path of the single-line diagram of the large feeder of the distribution network, classify the main feeder and branches of the feeder. The switch on the main line is a sectioning switch. If the sectioning switch is connected to another main line, it is a connection switch; the switch on the branch line is a branching switch. If the branching switch is the last stage, that is, located in front of the user, it is a demarcation switch; In Step 1, the switch types include ordinary switches, two-way remote switches, and three-way remote switches; the method for classifying the switch types is: Extract the switch set, match it with the distribution network automation switch ledger, and define the labels for the switch types. The switches that are not matched are ordinary switches, and other switches are divided into two-way remote or three-way remote switches according to the distribution network automation switch ledger; In Step 1, the switch area levels include A level, B level, and C level; the method for identifying the switch area level is: The grid ledger includes the method for dividing the lines to which the switches belong and the method for dividing the grid levels of the grids to which the lines belong. According to the grid level division, the switch area levels are divided into A level, B level, and C level.

3. The discrete-based optimized method for distribution network automation switch placement according to claim 2, characterized in that: In Step 1, the specific method for obtaining the number of users affected by the switch is: According to the topology of the line, perform recursion in the current direction of the grid under normal operation conditions, and divide the topology into N minimum power outage units according to the sectioning switch or branching switch. Simulate the power outage of each switch respectively, and obtain the corresponding number of affected users, which is the number of users affected by the switch.

4. The discrete-based optimized switch placement method for distribution network automation according to claim 2, wherein: In Step 1, the specific method for obtaining the number of users affected by the switch is: Based on the line topology, we first recursively proceed in the direction of the current during normal operation of the power grid, and divide the topology into N smallest power outage units according to the sectional switches or branch switches. We simulate the power outage of each switch and obtain the corresponding number of affected users, which is the number of users affected by the first switch. Meanwhile, considering the situation of interconnected power supply, the current direction of the interconnected operator is recursively followed to obtain the corresponding number of affected users, which is the number of users affected by the second switch. Set the impact coefficient for normal operations and the impact coefficient for communication operations; Calculate the number of users affected by the switch: Number of users affected by the switch = Number of users affected by the first switch * Normal operation impact coefficient + Number of users affected by the second switch * Inter-operation operation impact coefficient.

5. The discrete-based optimization method for distribution network automation switch placement according to claim 1, characterized in that: Step 2 specifically involves: obtaining historical battery outage information, i.e., historical switch failure power outage data. The historical battery outage information includes a main table and a sub-table. The main table includes the outage line, the start time of the outage, the end time of the outage, and the reason for the outage. The sub-table includes the outage equipment, the start time of the outage, and the end time of the outage. Based on the cause of the power outage, obtain the specific power outage equipment and the power outage duration of the corresponding sub-table. The power outage duration is the difference between the power outage end time and the power outage start time. Divide the power outage equipment into the smallest power outage unit, remove the fault data of a single distribution transformer, and use the maximum power outage duration of a single record as the power outage duration of the switch.

6. The optimized method for distributing points of automated switches in a discrete distribution network according to claim 1, characterized in that: Step 3 specifically involves: Step 3.1: Based on the attribute factors of the switch attributes in Step 1, calculate the number of power outages Cs and the power outage duration Sc for each type of switch fault; Step 3.2: Summarize the number of power outages and the duration of all switches to obtain the total number of power outages and the total duration of power outages for each type, and calculate the annual average failure rate and average failure duration; Wherein, the annual average failure rate = total number of power outages / N * total number of switches; N indicates that the selected historical switch failure power outage data is from N years of data; Wherein, average fault duration = total power outage duration / total number of power outages; Step 3.3: Construct a fault standard table based on the annual average failure rate and average failure duration of the switches under each attribute factor.

7. The discrete-based optimized method for distribution network automation switch placement according to claim 1, characterized in that: Step 4 specifically involves: Step 4.1: Based on the switches obtained in Step 1, match them to the fault standard table to obtain the annual average failure rate and average failure duration for each switch; Step 4.2: Iterate through each major feeder and calculate the annual number of users affected by each switch on each feeder based on the number of users affected by the switch. Among them, the number of households affected by power outages per year for each switch = the average annual failure rate of each switch * the number of users affected by the switch * the average duration of the failure; Step 4.3: Summing up the total number of households affected by power outages for each line based on the hierarchical relationship between lines and switches in the line topology path; Step 4.4: Calculate the annual average number of power outage events to obtain the reliability simulation value for each line; The average annual power outage events = total number of households experiencing power outages / total number of users; The reliability simulation value is calculated as 1 - (annual average power outage events / 365 * 24).

8. The discrete-based optimized method for distribution network automation switch placement according to claim 1, characterized in that: Step 5 specifically involves: Step 5.1: Preset the theoretical target value for reliability; Step 5.2: Calculate the target weight for each line; Target weight for each line = Theoretical reliability target value - Simulated reliability value; Step 5.3: Calculate the line renovation weight based on the line area level weight and the line target weight; whereby the line area level weight is a preset value based on the line area level in the grid ledger.

9. The optimization method for the distribution point of the discrete-based distribution network automation switch according to claim 1 is characterized in that: Step 6 specifically involves: Step 6.1: Obtain all ordinary switches and remote control switches for each line; Step 6.2: Calculate and obtain the switch weight coefficient for each switch. Switch weight coefficient = number of households with power outages per year / total number of households with power outages on the current line * line renovation weight; Step 6.3: Calculate the switch modification weight based on the switch position weight and the switch weight coefficient; whereby the switch position weight is a preset value based on the switch positions in the grid ledger.

10. The discrete-based optimized method for distribution network automation switch placement according to claim 1, characterized in that: The optimization method further includes the following steps: Step 7: Construct constraints to modify switches with high modification weights under limited modification cost constraints.

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