Power grid reconstruction site selection method, system, device and medium based on quantification score

Abstract

The application discloses a power grid reconstruction site selection method, system, device and medium based on quantitative scoring, and the method comprises the following steps: acquiring feeder topology structure data, automatic power grid nodes and medium and low voltage user data of a region to be reconstructed in a distribution network; segmenting the feeder with the automatic power grid nodes as endpoints to obtain segmented regions, and then performing power supply safety analysis to obtain qualified sites; calculating the scrap net value and investment cost of power equipment in all qualified sites, and using z-score standardization sigmod conversion scoring to obtain scrap net value scoring and investment cost scoring; performing weighted summation based on the scrap net value scoring and the investment cost scoring, acquiring quantitative scoring of the qualified sites, sorting, and selecting the qualified site with the highest quantitative scoring as the best power grid reconstruction site. The application comprehensively considers the influencing factors when selecting the automatic site, simply and effectively realizes the automatic selection of the power grid reconstruction site, and improves the efficiency of power grid analysis and power grid planning of the power department.

Description

Technical Field

[0001] This invention belongs to the technical field of power grid node transformation, specifically relating to a method, system, equipment, and medium for power grid transformation site selection based on quantitative scoring. Background Technology

[0002] In recent years, with social development and the continuous improvement of people's living standards, the public's requirements for power supply reliability have become increasingly higher. Power outages not only bring various inconveniences to people's lives but also cause huge losses to industrial and agricultural production. One effective means for power supply departments to improve power supply reliability and shorten power outage time is to upgrade and transform substations in the power grid into substations with automated functions. This allows for rapid isolation of faults and restoration of power to non-faulty areas through remote control and other operations after a fault occurs. However, a single area in a city to be upgraded often has thousands of substations, distributed across hundreds or even thousands of 10kV power supply lines (hereinafter referred to as feeders). Upgrading all of these substations at once would require a large amount of funding and would cause large-scale power outages, making it neither economical nor feasible. This raises the question of how to select appropriate substations (also known as grid nodes) on a 10kV feeder for upgrading, i.e., the site selection problem.

[0003] When selecting power grid nodes for upgrades, power grid planners typically begin by manually marking automated substations on the feeder diagram. These substations are then used to divide the feeder into sections. Information such as the number of users within each section is then used to determine which sections require upgrades. Next, based on experience and considering both investment costs and benefits, economically reasonable upgrade sites are selected. However, this method heavily relies on the experience and cognitive level of the planners, making the assessment results less scientific. Furthermore, the complete reliance on manual marking is inefficient. Secondly, this method does not consider all influencing factors comprehensively or with sufficient granularity. For example, regarding power supply security, it focuses more on the distribution of medium-voltage users along the feeder and less on the distribution of low-voltage users. In terms of maximizing investment benefits, power grid planning, while aiming to quickly meet societal demands for reliable power supply, lacks economic analysis and precise investment considerations. Summary of the Invention

[0004] The main objective of this invention is to overcome the shortcomings and deficiencies of existing technologies and provide a method, system, equipment, and medium for power grid renovation site selection based on quantitative scoring. This invention segments existing automated power grid nodes, performs power supply security analysis on the power grid nodes within the segmented areas, initially selects qualified sites, and then quantitatively scores the qualified sites based on two dimensions: net scrap value and investment cost, to screen out the best power grid renovation sites. This invention comprehensively considers the influencing factors during automated site selection, and simply and effectively realizes the automatic selection of power grid renovation nodes, improving the efficiency of power sector power grid analysis and planning.

[0005] To achieve the above objectives, this invention discloses a method for selecting sites for power grid renovation based on quantitative scoring, comprising the following steps:

[0006] In the distribution network, acquire feeder topology data, automated grid nodes, and medium- and low-voltage user data for the area to be upgraded.

[0007] Based on the feeder topology data of the area to be upgraded, the feeder is segmented with the automated grid node as the endpoint to obtain the segmented area. Then, based on the medium and low voltage user data, the power supply safety analysis of the grid node in the segmented area is carried out to obtain qualified selection points.

[0008] Calculate the net scrap value and investment cost of electrical equipment within all eligible selection points, and use z-score to standardize the sigmoid transformation score to obtain the net scrap value score and investment cost score;

[0009] The quantitative score of qualified sites is obtained by weighted summation of the scrap net value score and the investment cost score, and the qualified sites with the highest quantitative scores are selected as the best sites for power grid renovation.

[0010] As a preferred technical solution, the determination of qualified selection points specifically includes:

[0011] On a feeder in the feeder topology data of the area to be upgraded, the feeder is divided into several segmented areas with the automated grid node on the feeder as the endpoint.

[0012] Then, a power supply safety analysis is performed on each segment area, including:

[0013] Based on the data of medium and low voltage users and the grid transformation targets, confirm whether the number of medium voltage users in each segment area is less than m and the number of low voltage users is less than n. If the conditions are not met, the segment area is the segment area that needs to be transformed.

[0014] Traverse the power grid nodes in the segmented area that needs to be modified. If a certain power grid node makes the number of medium-voltage users in the area to the endpoint less than m and the number of low-voltage users less than n, then the power grid node is selected as a qualified point. The segmented area is re-divided with the power grid node as the endpoint. The power supply safety analysis continues until all segmented areas on the feeder meet the power supply safety analysis.

[0015] Calculate the minimum self-healing rate for each segment area. If the set self-healing rate is not met, the segment area is a segment area that needs to be modified. The segment areas are re-divided, and the power supply safety analysis continues until the set self-healing rate is met.

[0016] The minimum self-healing rate = 1 - number of medium-voltage users in the segmented area / total number of medium-voltage users on the feeder;

[0017] Power supply safety analysis was performed on each feeder to obtain all qualified selection points.

[0018] As a preferred technical solution, the service life, original asset value, and asset lifespan of the power equipment within the qualified selection sites are obtained, and the net scrap value of all power equipment within the qualified selection sites is calculated, specifically as follows:

[0019] Suppose there are n qualified selection points on a certain feeder line. After excluding the spare cabinet, there are m types of electrical equipment that need to be modified. Then, the net scrap value z of the i-th electrical equipment is... n The calculation formula is:

[0020]

[0021] Where, x n，i Let y be the number of the i-th type of power equipment in the n-th qualified selection point. n，i p represents the service life of the i-th type of power equipment in the n-th qualified selection site. i For the asset lifecycle of the i-th type of power equipment, q i Let be the original asset value of the i-th type of power equipment; the asset lifecycle and original asset value of each type of power equipment in each qualified selection point are fixed values;

[0022] Therefore, the total net scrap value of the nth qualified selection point on this feeder is:

[0023]

[0024] Calculate the total net scrap value of all qualified selection points on all feeders.

[0025] As the preferred technical solution, the prices of various power equipment in the current year are obtained, and the investment costs of power equipment within all qualified selection points are calculated, specifically as follows:

[0026] Remove all spare cabinets from the qualified selection sites;

[0027] Suppose there are n qualified locations on a feeder line, and after removing the spare cabinets, there are m types of electrical equipment that need to be upgraded. Then, using the price of each type of electrical equipment in that year as the allocation coefficient, the investment cost of the qualified locations is calculated using the following formula:

[0028]

[0029] Among them, M n Let λ be the investment cost of the nth qualified site selection. n，i Let C be the price of the i-th type of electrical equipment in the current year at the n-th qualified selection point. n，i This represents the number of type i electrical equipment in the nth qualified selection site.

[0030] The investment cost of all qualified selection points on all feeders is calculated.

[0031] As a preferred technical solution, after calculating the total net scrap value and investment cost of all nodes, z-score standardization is used for scoring and quantification. Then, the characteristic of the sigmoid function's range being (0, 1) is utilized for mapping to obtain the net scrap value score and investment cost score, specifically:

[0032] Suppose there are n qualified selection points on a certain feeder, and the net scrap value of a qualified selection point is W. n The average net value at disposal is The investment cost for a qualified site selection is M. n The average investment cost is

[0033] The investment cost is quantified by assigning a score based on z-score standardization to obtain the net asset value at risk of default for qualified investment sites. and investment cost quantification The formula is:

[0034]

[0035]

[0036] Where σ is the standard deviation;

[0037] According to the rule that the higher the quantified value, the lower the score, the quantified value of the qualified selection points is determined. and investment cost quantification The scrap net value score V for qualified selection points is obtained by mapping onto the sigmoid function and performing proportional scaling. n And investment cost rating U n The formula is:

[0038]

[0039]

[0040] Among them, Y max For Y n The maximum value, S max For S n The maximum value;

[0041]

[0042]

[0043] Scoring is performed on all qualified selection points on all feeders to obtain the net scrap value score and investment cost score for all qualified selection points.

[0044] As a preferred technical solution, the step of obtaining a quantitative score for qualified selection points and ranking them to select the qualified selection point with the highest quantitative score as the best power grid renovation selection point specifically involves:

[0045] Suppose there are n qualified selection points on a certain feeder. After obtaining the net asset value score and investment cost score, the quantitative score of the qualified selection points is calculated using the following formula:

[0046] C n =λ1U n +λ2V n n = 1, 2, 3, ...

[0047] Where λ1 and λ2 are weighting coefficients, 0 < λ1, λ2 < 1 and λ1 + λ2 = 1;

[0048] The qualified selection points on the feeder are ranked by their quantitative scores, and the qualified selection point with the highest quantitative score is selected as the best power grid renovation selection point on the feeder:

[0049] P = max(C) n ), n = 1, 2, 3, ...

[0050] Quantitatively score the qualified selection points on all feeders to obtain the optimal power grid renovation selection points on each feeder.

[0051] As a preferred technical solution, the method further includes:

[0052] The optimal location for power grid upgrades is visualized on the feeder topology map of the area to be upgraded.

[0053] On the other hand, the present invention provides a power grid renovation site selection system based on quantitative scoring, the system including a data acquisition module, a qualified site selection module, a scoring calculation module and an optimal site selection module;

[0054] The data acquisition module is used to acquire feeder topology data, automated grid nodes, and medium and low voltage user data of the area to be upgraded in the distribution network.

[0055] The qualified site selection module is used to divide the feeder into segments based on the feeder topology data of the area to be upgraded, with the automated power grid nodes as endpoints, to obtain segmented areas. Then, based on the medium and low voltage user data, the power supply safety analysis is performed on the power grid nodes within the segmented areas to obtain qualified sites.

[0056] The scoring calculation module is used to calculate the net scrap value and investment cost of power equipment within all qualified selection points, and uses z-score to standardize the sigmoid transformation score to obtain the net scrap value score and investment cost score.

[0057] The optimal site selection module is used to perform a weighted summation based on the net scrap value score and investment cost score to obtain a quantitative score for qualified sites and sort them to select the qualified sites with the highest quantitative scores as the optimal power grid renovation sites.

[0058] In another aspect, an electronic device is provided, characterized in that the electronic device comprises:

[0059] At least one processor; and,

[0060] A memory communicatively connected to the at least one processor; wherein,

[0061] The memory stores computer program instructions that can be executed by the at least one processor, which enables the at least one processor to perform the above-described method for selecting sites for power grid renovation based on quantitative scoring.

[0062] In one aspect, the present invention provides a computer-readable storage medium storing a program, characterized in that, when the program is executed by a processor, it implements the above-described method for selecting power grid transformation sites based on quantitative scoring.

[0063] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0064] This invention establishes a site selection evaluation model that uses a quantitative weighted scoring method to score the renovation cost, investment benefits, and improvement effect on power supply safety of selected sites. The scores from each dimension are weighted to obtain a comprehensive evaluation, ultimately determining the optimal renovation site. This solves the problems of crude evaluation methods and unscientific site selection results in traditional methods. When establishing the site selection evaluation model, all influencing factors in automated site selection are comprehensively considered, particularly incorporating factors such as the number of low-voltage users, net asset value, and equipment operation and maintenance costs. This addresses the issues of insufficient comprehensiveness and granularity in the influencing factors considered in traditional site selection methods. Simultaneously, it automatically performs power supply safety analysis and site selection according to rules, providing intuitive and efficient visualization, which can greatly improve the efficiency of power departments in power grid analysis and planning. Attached Figure Description

[0065] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0066] Figure 1 This is a flowchart of the power grid renovation site selection method based on quantitative scoring in an embodiment of the present invention;

[0067] Figure 2 This is a block diagram of the power grid renovation site selection system based on quantitative scoring in an embodiment of the present invention;

[0068] Figure 3 This is a schematic diagram of the structure of an electronic device in an embodiment of the present invention. Detailed Implementation

[0069] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative effort are within the scope of protection of the present application.

[0070] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application can be combined with other embodiments.

[0071] like Figure 1 As shown, this embodiment of the invention provides a method for selecting sites for power grid renovation based on quantitative scoring, including the following steps:

[0072] S1. Obtain basic data: Obtain feeder topology data, automated grid nodes, and medium and low voltage user data for the area to be upgraded in the distribution network;

[0073] S2. Power supply safety analysis to determine qualified sites: Based on the feeder topology data of the area to be upgraded, the feeder is segmented with the automated grid node as the endpoint to obtain the segmented area. Then, based on the medium and low voltage user data, the power supply safety analysis is performed on the grid node in the segmented area to determine the qualified sites.

[0074] Furthermore, step S2 specifically involves:

[0075] On a feeder in the feeder topology data of the area to be upgraded, the feeder is divided into several segmented areas with the automated grid node on the feeder as the endpoint.

[0076] Then, a power supply safety analysis is performed on each segment area, including:

[0077] Based on the data of medium and low voltage users and the grid transformation targets, confirm whether the number of medium voltage users in each segment area is less than m and the number of low voltage users is less than n. If the conditions are not met, the segment area is the segment area that needs to be transformed.

[0078] Traverse the power grid nodes in the segmented area that needs to be modified. If a certain power grid node makes the number of medium-voltage users in the area to the endpoint less than m and the number of low-voltage users less than n, then the power grid node is selected as a qualified point. The segmented area is re-divided with the power grid node as the endpoint. The power supply safety analysis continues until all segmented areas on the feeder meet the power supply safety analysis.

[0079] For example, according to the transformation goals of China Southern Power Grid: eliminate Level 4 events, that is, if the number of low-voltage users in a certain segment area exceeds 2,000 or the number of medium-voltage users reaches 10, reaching Level 4 events, then the segment area needs to be transformed; assuming that when performing power supply security analysis on a certain feeder, when traversing to the xth power grid node, the number of low-voltage users in each new segment area of ​​the feeder is less than 2,000 and the number of medium-voltage users is less than 10, then the selected point is a qualified selection point.

[0080] Next, calculate the minimum self-healing rate for each segment area. If the set self-healing rate is not met, the segment area is a segment area that needs to be modified. The segment areas are re-divided, and the power supply safety analysis continues until the set self-healing rate is met.

[0081] Minimum self-healing rate = 1 - number of medium-voltage users in the segmented area / total number of medium-voltage users on the feeder;

[0082] Minimum self-healing rate refers to the ratio of the minimum number of medium-voltage users that can be restored after a single fault occurs at any location on the feeder to the total number of medium-voltage users on that line. Self-healing means that when a line fault occurs, the power grid system restores power supply to users within a very short time (usually a few minutes) through automated means. Currently, the Guangzhou Power Supply Bureau standard requires a minimum self-healing rate of greater than 25%.

[0083] Power supply safety analysis was performed on each feeder to obtain all qualified selection points.

[0084] S3. Calculate the net scrap value and investment cost of all qualified selected power equipment, and use z-score to standardize the sigmoid transformation score to obtain the net scrap value score and investment cost score.

[0085] Furthermore, by obtaining the operating years, original asset value, and asset lifecycle of the power equipment within the qualified selection sites, the net scrap value of all power equipment within the qualified selection sites is calculated, specifically as follows:

[0086] Suppose there are n qualified selection points on a certain feeder line. After excluding the spare cabinet, there are m types of electrical equipment that need to be modified. Then, the net scrap value z of the i-th electrical equipment is... n The calculation formula is:

[0087]

[0088] Where, x n，i Let y be the number of the i-th type of power equipment in the n-th qualified selection point. n，i p represents the service life of the i-th type of power equipment in the n-th qualified selection site. i For the asset lifecycle of the i-th type of power equipment, q i Let be the original asset value of the i-th type of power equipment; the asset lifecycle and original asset value of each type of power equipment in each qualified selection point are fixed values;

[0089] Therefore, the total net scrap value of the nth qualified selection point on this feeder is:

[0090]

[0091] Calculate the total net scrap value of all qualified selection points on all feeders.

[0092] Furthermore, by obtaining the prices of various power equipment in that year as allocation coefficients, the investment cost of power equipment within all eligible selection sites is calculated, specifically as follows:

[0093] Remove all spare cabinets from the qualified selection sites;

[0094] Suppose there are n qualified locations on a feeder line, and after removing the spare cabinets, there are m types of electrical equipment that need to be upgraded. Then, using the price of each type of electrical equipment in that year as the allocation coefficient, the investment cost of the qualified locations is calculated using the following formula:

[0095]

[0096] Among them, M n Let λ be the investment cost of the nth qualified site selection. n，i Let C be the price of the i-th type of electrical equipment in the current year at the n-th qualified selection point. n，i The number of type i electrical equipment in the nth qualified selection point;

[0097] The investment cost of all qualified selection points on all feeders is calculated.

[0098] S4. Based on the net scrap value score and investment cost score, perform a weighted summation to obtain the quantitative score of qualified selection points, and sort them to select the qualified selection point with the highest quantitative score as the best power grid renovation selection point.

[0099] Because the basic min-max normalization feature scaling method is too absolute, when the number of selected points is small and the investment cost differences are small, the scores can easily vary significantly, thus greatly affecting the overall score of the selected points. To avoid the huge score differences caused by the small number of qualified selected points and the small difference in investment costs, this method considers a new feature scaling method. After calculating the total net scrap value and investment cost of all nodes, z-score normalization is used for scoring and quantification. Then, the characteristic of the sigmoid function's value range in (0, 1) is used for mapping (the purpose of mapping is to transform the score values ​​of all qualified selected points into scores in the range of 0 to 100 according to a certain algorithm), to obtain the net scrap value score and investment cost score, specifically:

[0100] Suppose there are n qualified selection points on a certain feeder, and the net scrap value of a qualified selection point is W. n The average net value of scrapped items is The investment cost for a qualified site selection is M. n The average investment cost is

[0101] The investment cost is quantified by assigning a score based on z-score standardization to obtain the net asset value at risk of default for qualified investment sites. and investment cost quantification The formula is:

[0102]

[0103]

[0104] Where σ is the standard deviation;

[0105] According to the rule that the higher the quantified value, the lower the score, the quantified value of the qualified selection points is determined. and investment cost quantification The scrap net value score V for qualified selection points is obtained by mapping onto the sigmoid function and performing proportional scaling. n And investment cost rating U n The formula is:

[0106]

[0107]

[0108] Among them, Y max For Y n The maximum value, S max For S n The maximum value;

[0109]

[0110]

[0111] Scoring is performed on all qualified selection points on all feeders to obtain the net scrap value score and investment cost score for all qualified selection points.

[0112] Furthermore, a quantitative score for qualified sites is obtained and ranked, and the qualified site with the highest quantitative score is selected as the best site for power grid renovation. Specifically:

[0113] Suppose there are n qualified selection points on a certain feeder. After obtaining the net asset value score and investment cost score, the quantitative score of the qualified selection points is calculated using the following formula:

[0114] C n =λ1U n +λ2V n n = 1, 2, 3, ...

[0115] Where λ1 and λ2 are weighting coefficients, 0 < λ1, λ2 < 1 and λ1 + λ2 = 1;

[0116] The qualified selection points on the feeder are ranked by their quantitative scores, and the qualified selection point with the highest quantitative score is selected as the best power grid renovation selection point on the feeder:

[0117] P = max(C) n ), n = 1, 2, 3, ...

[0118] Quantitatively score the qualified selection points on all feeders to obtain the optimal power grid renovation selection points on each feeder.

[0119] Furthermore, to provide a clear and convenient demonstration of the optimal site selection for power grid upgrades, this embodiment of the method also includes the following steps:

[0120] The optimal location for power grid upgrades is visualized on the feeder topology map of the area to be upgraded.

[0121] It should be noted that, for the sake of simplicity, the aforementioned method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously.

[0122] Based on the same idea as the power grid renovation site selection method based on quantitative scoring in the above embodiments, the present invention also provides a power grid renovation site selection system based on quantitative scoring, which can be used to execute the above-described power grid renovation site selection method based on quantitative scoring. For ease of explanation, the structural diagram of the embodiment of the power grid renovation site selection system based on quantitative scoring only shows the parts related to the embodiments of the present invention. Those skilled in the art will understand that the illustrated structure does not constitute a limitation on the device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0123] like Figure 2 As shown, another embodiment of the present invention provides a power grid renovation site selection system based on quantitative scoring, including a data acquisition module, a qualified site selection module, a scoring calculation module, and an optimal site selection module;

[0124] The data acquisition module is used to acquire feeder topology data, automated grid nodes, and medium- and low-voltage user data for the area to be upgraded in the distribution network.

[0125] The qualified site selection module is used to divide the feeder into segments based on the feeder topology data of the area to be upgraded, with the automated grid nodes as endpoints, and then to perform power supply safety analysis on the grid nodes within the segmented areas based on medium and low voltage user data to obtain qualified site selections.

[0126] The scoring calculation module is used to calculate the net scrap value and investment cost of all qualified selected power equipment, and uses z-score to standardize the sigmoid transformation score to obtain the net scrap value score and investment cost score.

[0127] The optimal site selection module is used to perform a weighted summation based on the net scrap value score and investment cost score to obtain a quantitative score for qualified sites and sort them to select the qualified sites with the highest quantitative scores as the optimal sites for power grid renovation.

[0128] It should be noted that the power grid renovation site selection system based on quantitative scoring of the present invention corresponds one-to-one with the power grid renovation site selection method based on quantitative scoring of the present invention. The technical features and beneficial effects described in the above embodiments of the power grid renovation site selection method based on quantitative scoring are applicable to the embodiments of the power grid renovation site selection system based on quantitative scoring. For details, please refer to the description in the embodiments of the method of the present invention, which will not be repeated here.

[0129] Furthermore, in the above embodiments of the power grid renovation site selection system based on quantitative scoring, the logical division of each program module is only an example. In actual applications, the above functions can be assigned to different program modules as needed, for example, for the sake of corresponding hardware configuration requirements or software implementation convenience. That is, the internal structure of the power grid renovation site selection system based on quantitative scoring is divided into different program modules to complete all or part of the functions described above.

[0130] Please see Figure 3 In one embodiment, an electronic device is provided for implementing a grid renovation site selection method based on quantitative scoring. The electronic device may include a first processor, a first memory, and a bus, and may also include a computer program stored in the first memory and executable on the first processor, such as a grid renovation site selection program based on quantitative scoring.

[0131] The first memory includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the first memory can be an internal storage unit of an electronic device, such as a portable hard drive. In other embodiments, the first memory can be an external storage device of the electronic device, such as a plug-in portable hard drive, smart media card (SMC), secure digital card (SD), flash card, etc. Furthermore, the first memory can include both internal and external storage units of the electronic device. The first memory can be used not only to store application software and various types of data installed on the electronic device, such as the code of a power grid renovation site selection program based on quantitative scoring, but also to temporarily store data that has been output or will be output.

[0132] In some embodiments, the first processor may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits packaged with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The first processor is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the first memory (e.g., a power grid renovation site selection program based on quantitative scoring) and calls data stored in the first memory to perform various functions of the electronic device and process data.

[0133] Figure 3 Only electronic devices with components are shown; it will be understood by those skilled in the art that... Figure 3 The structure shown does not constitute a limitation on the electronic device and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0134] The power grid renovation site selection program based on quantitative scoring, stored in the first memory of the electronic device, is a combination of multiple instructions. When run in the first processor, it can achieve the following:

[0135] In the distribution network, acquire feeder topology data, automated grid nodes, and medium- and low-voltage user data for the area to be upgraded.

[0136] Based on the feeder topology data of the area to be upgraded, the feeder is segmented with the automated grid node as the endpoint to obtain the segmented area. Then, based on the medium and low voltage user data, the power supply safety analysis of the grid node in the segmented area is carried out to obtain qualified selection points.

[0137] Calculate the net scrap value and investment cost of electrical equipment within all eligible selection points, and use z-score to standardize the sigmoid transformation score to obtain the net scrap value score and investment cost score;

[0138] The quantitative score of qualified sites is obtained by weighted summation of the scrap net value score and the investment cost score, and the qualified sites with the highest quantitative scores are selected as the best sites for power grid renovation.

[0139] Furthermore, if the modules / units integrated in the electronic device are implemented as software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium. The computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0140] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0141] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0142] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A method for selecting sites for power grid renovation based on quantitative scoring, characterized in that, Includes the following steps: In the distribution network, acquire feeder topology data, automated grid nodes, and medium- and low-voltage user data for the area to be upgraded. Based on the feeder topology data of the area to be upgraded, the feeder is segmented with automated grid nodes as endpoints to obtain segmented areas. Then, based on medium and low voltage user data, power supply safety analysis is performed on the grid nodes within the segmented areas to determine qualified selection points, specifically: On a feeder in the feeder topology data of the area to be upgraded, the feeder is divided into several segmented areas with the automated grid node on the feeder as the endpoint. Then, a power supply safety analysis is performed on each segment area, including: Based on the data of medium and low voltage users and the power grid renovation targets, confirm whether the number of medium voltage users in each segment area is less than m. ’ And is the number of low-voltage users less than n? ’ If the conditions are not met, then the segmented area is the segmented area that needs to be modified. Iterate through the power grid nodes within the segmented area that needs modification. If a certain power grid node results in the number of medium-voltage users in the area leading to its endpoint being less than m... ’ And the number of low-voltage users is less than n ’ If so, the power grid node is selected as a qualified point, and the segmented area is re-divided with the power grid node as the endpoint. The power supply security analysis continues until all segmented areas on the feeder meet the power supply security analysis. Calculate the minimum self-healing rate for each segment area. If the set self-healing rate is not met, the segment area is a segment area that needs to be modified. The segment areas are re-divided, and the power supply safety analysis continues until the set self-healing rate is met. The minimum self-healing rate = 1 - number of medium-voltage users in the segmented area / total number of medium-voltage users on the feeder; A power supply safety analysis was conducted on each feeder to determine all qualified selection points; Calculate the net scrap value and investment cost of all electrical equipment within the eligible selection sites, and use z-score standardized Sigmadox transformation scoring to obtain the net scrap value score and investment cost score; obtain the operating years, original asset value, and asset life cycle of the electrical equipment within the eligible selection sites, and calculate the net scrap value of all electrical equipment within the eligible selection sites, specifically: Suppose there are n qualified selection points on a certain feeder line. After excluding the spare cabinet, there are m types of electrical equipment that need to be modified. Then, the net scrap value z of the i-th electrical equipment is... n,i The calculation formula is: ， Where, x n,i Let y be the number of the i-th type of power equipment in the n-th qualified selection point. n,i p represents the service life of the i-th type of power equipment in the n-th qualified selection site. i For the asset lifecycle of the i-th type of power equipment, q i Let be the original asset value of the i-th type of power equipment; the asset lifecycle and original asset value of each type of power equipment in each qualified selection point are fixed values; Therefore, the total net scrap value of the nth qualified selection point on this feeder is: ， Calculate the total net scrap value of all qualified selection points on all feeders; The quantitative score of qualified sites is obtained by weighted summation of the scrap net value score and the investment cost score, and the qualified sites with the highest quantitative scores are selected as the best sites for power grid renovation.

2. The power grid renovation site selection method based on quantitative scoring according to claim 1, characterized in that, Obtain the prices of various power equipment for the current year, and calculate the investment cost of all power equipment within the qualified site selection area, specifically: Remove all spare cabinets from the qualified selection sites; Suppose there are n qualified locations on a feeder line, and after removing the spare cabinets, there are m types of electrical equipment that need to be upgraded. Then, using the price of each type of electrical equipment in that year as the allocation coefficient, the investment cost of the qualified locations is calculated using the following formula: ， Among them, M n Let λ be the investment cost of the nth qualified site selection. n,i Let C be the price of the i-th type of electrical equipment in the current year at the n-th qualified selection point. n,i This represents the number of type i electrical equipment in the nth qualified selection site. The investment cost of all qualified selection points on all feeders is calculated.

3. The power grid renovation site selection method based on quantitative scoring according to claim 2, characterized in that, After calculating the total net worth and investment cost for all nodes, z-score standardization is used for scoring and quantification. Then, the characteristic of the sigmoid function's range of (0,1) is used for mapping to obtain the net worth score and investment cost score, as follows: Suppose there are n qualified selection points on a certain feeder, and the net scrap value of a qualified selection point is W. n The average net value at disposal is The investment cost for a qualified site selection is M. n The average investment cost is ; The investment cost is quantified by assigning a score based on z-score standardization to obtain the net asset value at risk of default for qualified investment sites. and investment cost quantification The formula is: ， ； According to the rule that the higher the quantified value, the lower the score, the quantified value of the qualified selection points is determined. and investment cost quantification The scrap net value score V for qualified selection points is obtained by mapping onto the sigmoid function and performing proportional scaling. n And investment cost rating U n The formula is: ， ， Among them, Y max For Y n The maximum value, S max For S n The maximum value; ， ， Scoring is performed on all qualified selection points on all feeders to obtain the net scrap value score and investment cost score for all qualified selection points.

4. The power grid renovation site selection method based on quantitative scoring according to claim 3, characterized in that, The process of obtaining quantitative scores for qualified sites and ranking them to select the qualified sites with the highest quantitative scores as the best sites for power grid renovation is as follows: Suppose there are n qualified selection points on a certain feeder. After obtaining the net asset value score and investment cost score, the quantitative score of the qualified selection points is calculated using the following formula: C n = λ1U n + λ2V n ,n=1,2,3,… Where λ1 and λ2 are weighting coefficients, 0 < λ1, λ2 < 1 and λ1+λ2=1; The qualified selection points on the feeder are ranked by their quantitative scores, and the qualified selection point with the highest quantitative score is selected as the best power grid renovation selection point on the feeder: P=max(C n ),n=1,2,3,…, Quantitatively score the qualified selection points on all feeders to obtain the optimal power grid renovation selection points on each feeder.

5. The power grid renovation site selection method based on quantitative scoring according to claim 4, characterized in that, The method further includes: The optimal location for power grid upgrades is visualized on the feeder topology map of the area to be upgraded.

6. A power grid renovation site selection system based on quantitative scoring, characterized in that, The system includes a data acquisition module, a qualified point selection module, a scoring calculation module, and an optimal point selection module. The data acquisition module is used to acquire feeder topology data, automated grid nodes, and medium and low voltage user data of the area to be upgraded in the distribution network. The qualified site selection module is used to segment the feeder into sections based on the feeder topology data of the area to be upgraded, using automated grid nodes as endpoints. Then, based on medium- and low-voltage user data, it performs power supply safety analysis on the grid nodes within each section to determine qualified sites. Specifically: On a feeder in the feeder topology data of the area to be upgraded, the feeder is divided into several segmented areas with the automated grid node on the feeder as the endpoint. Then, a power supply safety analysis is performed on each segment area, including: Based on the data of medium and low voltage users and the power grid renovation targets, confirm whether the number of medium voltage users in each segment area is less than m. ’ And is the number of low-voltage users less than n? ’ If the conditions are not met, then the segmented area is the segmented area that needs to be modified. Iterate through the power grid nodes within the segmented area that needs modification. If a certain power grid node results in the number of medium-voltage users in the area leading to its endpoint being less than m... ’ And the number of low-voltage users is less than n ’ If so, the power grid node is selected as a qualified point, and the segmented area is re-divided with the power grid node as the endpoint. The power supply security analysis continues until all segmented areas on the feeder meet the power supply security analysis. Calculate the minimum self-healing rate for each segment area. If the set self-healing rate is not met, the segment area is a segment area that needs to be modified. The segment areas are re-divided, and the power supply safety analysis continues until the set self-healing rate is met. The minimum self-healing rate = 1 - number of medium-voltage users in the segmented area / total number of medium-voltage users on the feeder; A power supply safety analysis was conducted on each feeder to determine all qualified selection points; The scoring calculation module is used to calculate the net scrap value and investment cost of all qualified power equipment within the selected sites, and uses z-score standardized sigmoid transformation to obtain the net scrap value score and investment cost score; it obtains the operating years, original asset value, and asset life cycle of the power equipment within the qualified sites, and calculates the net scrap value of all qualified power equipment within the selected sites, specifically: Suppose there are n qualified selection points on a certain feeder line. After excluding the spare cabinet, there are m types of electrical equipment that need to be modified. Then, the net scrap value z of the i-th electrical equipment is... n,i The calculation formula is: ， Where, x n,i Let y be the number of the i-th type of power equipment in the n-th qualified selection point. n,i p represents the service life of the i-th type of power equipment in the n-th qualified selection site. i For the asset lifecycle of the i-th type of power equipment, q i Let be the original asset value of the i-th type of power equipment; the asset lifecycle and original asset value of each type of power equipment in each qualified selection point are fixed values; Therefore, the total net scrap value of the nth qualified selection point on this feeder is: ， Calculate the total net scrap value of all qualified selection points on all feeders; The optimal site selection module is used to perform a weighted summation based on the net scrap value score and investment cost score to obtain a quantitative score for qualified sites and sort them to select the qualified sites with the highest quantitative scores as the optimal power grid renovation sites.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores computer program instructions that can be executed by the at least one processor, which enables the at least one processor to perform the power grid renovation site selection method based on quantitative scoring as described in any one of claims 1-5.

8. A computer-readable storage medium storing a program, characterized in that, When the program is executed by the processor, it implements the power grid renovation site selection method based on quantitative scoring as described in any one of claims 1-5.

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