Method and device for determining wiring mode of power distribution network, equipment and medium

Abstract

The embodiment of the invention discloses a method, a device and equipment for determining a wiring mode of a power distribution network and a medium. Comprising the following steps: acquiring electrical load information of each industry in a target power distribution network area; determining predicted load information of the target power distribution network region based on the electrical load information of each industry and set load increase information; evaluating a plurality of wiring modes based on the predicted load information to obtain a wiring evaluation result corresponding to each wiring mode; wherein the wiring evaluation result comprises wiring evaluation sub-results of a plurality of time periods, and each wiring evaluation sub-result is determined based on a plurality of evaluation indexes; and determining a target wiring mode of each time period based on the wiring evaluation result. According to the scheme, the wiring evaluation result corresponding to each wiring mode can be accurately obtained, and the accuracy of the wiring evaluation result is improved, so that the wiring mode of the power distribution network can be accurately determined.

Description

Technical Field

[0001] Embodiments of the present invention relate to the technical field of power distribution networks, and in particular to a method, device, equipment and medium for determining a wiring mode of a power distribution network. Background Art

[0002] At present, an economical, reliable and suitable distribution network connection method for local conditions can bring stable and high-quality electricity to users. Under the condition of uncertain power load growth, clarifying the connection method of the distribution network is of great guiding significance for carrying out distribution network transformation planning and expansion planning. The existing technology does not take into account the uncertainty of load growth and cannot accurately determine the connection method of the distribution network. Summary of the invention

[0003] The embodiments of the present invention provide a method, device, equipment and medium for determining a wiring mode of a distribution network, which can accurately determine the wiring mode of the distribution network.

[0004] In a first aspect, an embodiment of the present invention provides a method for determining a power distribution network connection mode, comprising:

[0005] Obtain the power load information of each industry in the target distribution network area;

[0006] Determine the predicted load information of the target distribution network area based on the power load information of each industry and the set load growth information;

[0007] Evaluate multiple wiring modes based on the predicted load information to obtain wiring evaluation results corresponding to each wiring mode; wherein the wiring evaluation results include wiring evaluation sub-results for multiple time periods, and each wiring evaluation sub-result is determined based on multiple evaluation indicators;

[0008] A target wiring mode for each of the time periods is determined based on the wiring evaluation result.

[0009] In a second aspect, an embodiment of the present invention further provides a device for determining a power distribution network connection mode, the device comprising:

[0010] An information acquisition module is used to obtain the power load information of various industries in the target distribution network area;

[0011] A predicted load information determination module, used to determine the predicted load information of the target distribution network area based on the power load information of each industry and the set load growth information;

[0012] An evaluation result obtaining module, used to evaluate multiple wiring modes based on the predicted load information, and obtain wiring evaluation results corresponding to each wiring mode; wherein the wiring evaluation results include wiring evaluation sub-results of multiple time periods, and each wiring evaluation sub-result is determined based on multiple evaluation indicators;

[0013] The target wiring mode determination module is used to determine the target wiring mode of each time period based on the wiring evaluation result.

[0014] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for determining the connection mode of the distribution network described in the embodiment of the present invention.

[0018] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for determining the connection mode of a distribution network as described in an embodiment of the present invention when executed.

[0019] The embodiment of the present invention discloses a method, device, equipment and medium for determining the wiring mode of a distribution network, including: obtaining the power load information of each industry in the target distribution network area; determining the predicted load information of the target distribution network area based on the power load information of each industry and the set load growth information; evaluating multiple wiring modes based on the predicted load information, and obtaining the wiring evaluation results corresponding to each wiring mode; wherein the wiring evaluation results include wiring evaluation sub-results of multiple time periods, and each wiring evaluation sub-result is determined based on multiple evaluation indicators; determining the target wiring mode for each time period based on the wiring evaluation results. The above technical scheme evaluates multiple wiring modes according to the predicted load information, and can accurately obtain the wiring evaluation results corresponding to each wiring mode, thereby improving the accuracy of the wiring evaluation results; at the same time, the target wiring mode for each time period is determined according to the wiring evaluation results, and the wiring mode of the distribution network can be accurately determined. Compared with the prior art, the technical scheme provided by this embodiment can accurately obtain the wiring evaluation results corresponding to each wiring mode, thereby improving the accuracy of the wiring evaluation results, thereby accurately determining the wiring mode of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flow chart of a method for determining a distribution network wiring mode in Embodiment 1 of the present invention;

[0021] Figure 2 A line graph of the evaluation results provided by an embodiment of the present invention;

[0022] Figure 3 It is a structural schematic diagram of a device for determining a connection mode of a distribution network in Embodiment 2 of the present invention;

[0023] Figure 4 It is a structural schematic diagram of an electronic device in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0024] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0025] Embodiment 1

[0026] Figure 1 This is a flow chart of a method for determining a distribution network connection mode provided in the first embodiment of the present invention. This embodiment is applicable to the case where a distribution network connection mode is determined. The method can be executed by a device for determining a distribution network connection mode. The device can be implemented in the form of software and / or hardware. Optionally, it can be implemented by an electronic device, which can be a mobile terminal, a PC or a server. Specifically, it includes the following steps:

[0027] S110. Obtain power load information of various industries in the target distribution network area.

[0028] In this embodiment, the target distribution network area includes multiple substations, and different wiring methods can be used to connect the substations in the target distribution network area. The wiring methods may include single radial wiring method, hand-in-hand wiring method, N-segment 2-connection wiring method, "2-1" single ring network wiring method, "3-1" transition wiring method, "3-1" single ring network wiring method, two-supply and one-backup wiring method, three-supply and one-backup wiring method, and double-ring network wiring method, etc.

[0029] Optionally, before obtaining the power load information of each industry in the target distribution network area, the method further includes: classifying the power load information in the target distribution network area according to different industries. The industry may include at least one of the industrial industry, commercial industry, residential industry and office industry. The power load information may be understood as power consumption.

[0030] Exemplarily, it is assumed that the industries include industrial industry, commercial industry, residential industry and office industry, wherein the corresponding power load information is a, b, c and d respectively.

[0031] S120. Determine the predicted load information of the target distribution network area based on the power load information of each industry and the set load growth information.

[0032] In this embodiment, the set load growth information can be understood as the natural load growth rate. The set load growth information includes first load growth information, second load growth information and third load growth information. The first load growth information> the second load growth information> the third load growth information.

[0033] In this embodiment, the method of determining the predicted load information of the target distribution network area based on the power load information of each industry and the set load growth information can be described as the following steps:

[0034] a1) For each industry, determine the industry forecast load information based on the set load growth information and power load information;

[0035] For example, taking the industrial sector as an example, assuming that the first load growth information, the second load growth information and the third load growth information in the load growth information are set to be f1%, f2% and f3% respectively. Then the following formula is used to calculate the industry forecast load information corresponding to the industrial sector:

[0036]

[0037]

[0038]

[0039] in, It is expressed as the industry forecast load information under the first load growth information, It is expressed as the industry forecast load information under the second load growth information, Represented as industry forecast load information under the third load growth information.

[0040] Following the above description, for each industry, similar to the above steps, the industry forecast load information corresponding to the industry is obtained. For example, the industry forecast load information corresponding to industry k is recorded as Among them, k = 1, 2, 3, 4. Specifically, k = 1 represents the industrial industry, k = 2 represents the commercial industry, k = 3 represents the residential industry, and k = 4 represents the office industry.

[0041] b1) Determine the forecast load information of the target distribution network area based on the industry forecast load information and its corresponding preset probability information.

[0042] In this embodiment, the preset probability information is a pre-set probability. For example, assuming that the industry forecast load information The corresponding preset probability information is Use set step size Discretize and obtain the probability sequence a corresponding to industry k through the following formula k (i),i=0,,N k .in,

[0043]

[0044] Furthermore, where [x] represents the largest integer not exceeding x, N k is the number of discretized values ​​of industry k. Considering the correlation of load growth among industries, the probability sequences of each industry are convolved and summed to obtain the target probability sequence in, represents the convolution summation operation. Then, through the formula Calculate the expected value of x(i) and obtain the predicted load information E Q ,in,

[0045] Optionally, after determining the forecast load information of the target distribution network area based on the industry forecast load information and its corresponding preset probability information, the following operations should also be performed: obtain the reported power consumption parameters of the target distribution network area; determine the load correction information based on the reported power consumption parameters; correct the forecast load information based on the load correction information to obtain new forecast load information.

[0046] Furthermore, the reported power consumption parameters can be understood as power consumption parameters related to the large user's reporting. Among them, the reported power consumption parameters can include at least one of the reported load capacity, load factor, stage factor and load concurrency rate. Optionally, the method of determining the load correction information based on the reported power consumption parameters can be: multiplying the reported power consumption parameters to obtain the load correction information. Optionally, the method of correcting the predicted load information based on the load correction information to obtain new predicted load information can be: summing the load correction information and the predicted load information to obtain new predicted load information.

[0047] Continuing with the above description, for example, assuming that the reported load capacity, load factor, stage factor and load concurrency are P, α, β and W respectively, the load correction information is Z1 = P*α*β*W. Q Add them together to obtain the new predicted load information Z. Where Z = Z1 + E Q .

[0048] S130. Evaluate multiple wiring modes based on the predicted load information to obtain wiring evaluation results corresponding to each wiring mode.

[0049] In this embodiment, the wiring evaluation result is an evaluation value corresponding to each wiring mode, wherein the wiring evaluation result includes wiring evaluation sub-results of multiple time periods, and each wiring evaluation sub-result is determined based on multiple evaluation indicators.

[0050] Continuing with the above description, the wiring assessment result can be understood as the assessment result in a future time period, such as the assessment result in the next N years. On this basis, the wiring assessment sub-results of multiple time periods can be understood as the wiring assessment sub-results of the first year, the wiring assessment sub-results of the second year, and so on. The wiring assessment sub-results of the Nth year. Optionally, the evaluation indicators may include topological structure indicators, reliability indicators, and economic indicators, wherein the topological structure indicators may include grid transfer capacity indicators, grid connectivity indicators, and comprehensive efficiency indicators; reliability indicators may include average power supply reliability indicators, average power outage frequency indicators, average power outage time indicators, and load loss indicators; economic indicators may include: construction and operation cost indicators, unit load annual cost indicators, and power outage loss cost indicators.

[0051] The calculation methods of each indicator are as follows:

[0052] Topological structure indicators:

[0053] Defining λ TC is the grid transfer capacity indicator. The difference in grid structure makes the λ of different wiring modes TC Different, TC The larger the value, the more load will be transferred when the feeder fails, and the stronger the line load capacity will be. TC As shown in the following formula.

[0054]

[0055] Where P t is the active load that can be transferred from the feeder to other lines under N-1 fault, P z is the total active load carried by the feeder.

[0056] Defining λ NC is the grid connectivity index, λ NC Describes the connectivity of each node in the grid and reflects the degree of topological accessibility. NC The larger the value, the stronger the grid toughness is and the less affected by N-1 failure is. NC As shown in the following formula.

[0057]

[0058] In the formula, φ represents the node type, φ=1, 2, 3 represent the terminal node, ordinary node and cross node respectively. Respectively represent the connectivity and number of nodes of the φth type of node, NB is the total number of nodes.

[0059] Defining λ η is the comprehensive efficiency index, λ η Used to describe the utilization of feeder capacity for various connections, λ η The larger the value, the higher the utilization rate. η As shown in the following formula.

[0060]

[0061] B sc =∑L i

[0062] Where, L i Indicates the load size of the i-th feedback line, B sc To meet the maximum power supply capacity under the N-1 constraint, S i Represents the capacity of the i-th feedback line.

[0063] Economic indicators:

[0064] Economic evaluation is an important part of grid evaluation. In addition to initial investment and labor costs, it also includes construction and operation costs, collectively referred to as total investment cost F. IC The difference in load density leads to different annual unit load costs F in different regions. c Different load densities lead to different power outage losses under the same power outage time. Therefore, the power outage loss cost F SC As another indicator to measure the economy of wiring structure, the calculation formula is shown below.

[0065]

[0066]

[0067] F OC =F line +F equ

[0068] F IC =F T +F OC

[0069]

[0070]

[0071] Where M l 、M ka 、M ktThey represent the newly built line set, the newly built section switch set, and the newly built tie switch set, respectively. l Indicates the length of each new line, N e Indicates the number of switches of various types, K D , K L Represent cables and overhead lines, P cab , P lin are the unit investment costs of cable lines and overhead lines, respectively, box , P swi , P con are the unit construction costs of the automated switchgear, column switch, and tie switch, respectively; Z is the initial investment cost; and F T is the equivalent annual value conversion of the initial investment Z, r is the discount rate, T is the planning period, F line 、F equ are the operation and maintenance costs of the line and equipment respectively. This paper takes a certain proportion of the initial investment based on experience. ENSx is the load loss due to power outage at node x, is the unit power outage loss of node x, N LP is the set of all nodes, P L is the total system load.

[0072] Reliability indicators:

[0073] The average power supply reliability (ASAI), average power outage frequency (SAIFI), average power outage duration (SAIDI), and load loss (ENS) are selected as reliability evaluation indicators. ASAI is used to measure the level of reliable power supply to users, SAIFI is used to measure the average number of power outages due to equipment failures for distribution network users, SAIDI is used to measure the average time of power outages due to equipment failures for distribution network users, and ENS is used to measure the load lost when a line or equipment fails. The calculation formula is as follows.

[0074]

[0075]

[0076]

[0077]

[0078] Where N LP is the set of all nodes, N x is the number of users under node x, U x is the average power outage time of node x per year, α x is the annual average power outage frequency of node x, P x is the load size of node x.

[0079] In this embodiment, multiple wiring modes are evaluated based on the predicted load information, and a method of obtaining a wiring evaluation result corresponding to each wiring mode can be described as the following steps:

[0080] a2) for each wiring mode, determining a plurality of first evaluation index information based on the predicted load information;

[0081] In this embodiment, the first evaluation index information can be understood as an evaluation index value, and the predicted load information is input into the above-mentioned multiple evaluation indexes to obtain the evaluation index value corresponding to each evaluation index, that is, the first evaluation index information.

[0082] b2) determining a plurality of second evaluation index information of the wiring mode in each time period based on the plurality of first evaluation index information;

[0083] In this embodiment, the second evaluation index information is a predicted evaluation index value in a future time period.

[0084] In this embodiment, the method of determining multiple second evaluation index information of the wiring method in each time period based on multiple first evaluation index information can be: based on multiple first evaluation index information, predicting multiple second evaluation index information of the wiring method in each time period by a preset method.

[0085] Continuing with the above description, the preset method may be a Monte Carlo method, and based on the plurality of first evaluation index information, the Monte Carlo method may be used to predict the plurality of second evaluation index information of the wiring method in the future time period. For example, the plurality of second evaluation index information of the first year, the plurality of second evaluation index information of the second year, ..., the plurality of second evaluation index information of the Nth year in the future.

[0086] Among them, the simulation process of the Monte Carlo method can be: according to the predicted load information obtained by prediction, the normal distribution is used for simulation, and the equipment failure rate and power outage time are simulated by Fourier function and gamma distribution respectively. Specifically, first set the number of simulations, randomly select the load value, failure rate value, and power outage time value as input; then, calculate the values ​​of each evaluation index, and obtain the evaluation score of a certain wiring method in a certain year through weighted summation to complete a simulation; then, repeat the above steps until the number of simulations meets the requirements. Finally, the numerical values ​​obtained by simulation are statistically analyzed to obtain the probability distribution of the evaluation score of a certain wiring method in a certain year.

[0087] c2) determining wiring evaluation sub-results in each time period based on the plurality of second evaluation index information, and combining the plurality of wiring evaluation sub-results into a wiring evaluation result corresponding to the wiring mode.

[0088] In this embodiment, the method of determining the wiring evaluation sub-results in each time period based on multiple second evaluation index information can be: for each time period, determine the target weight of each second evaluation index information; based on the target weight, perform weighted summation on multiple second evaluation index information to obtain the wiring evaluation sub-results.

[0089] In this embodiment, the method for determining the target weight of each second evaluation index information can be: determining the first weight of the second evaluation index information according to the anti-entropy weight method; determining the second weight of the second evaluation index information according to the hierarchical analysis method; and fusing the first weight and the second weight to obtain the target weight.

[0090] In this embodiment, the anti-entropy weight method and the Analytic Hierarchy Process (AHP) are both methods for determining weights.

[0091] For example, according to the anti-entropy weight method, the first weights of the second evaluation index information corresponding to the grid transfer capacity index, the grid connectivity index, the comprehensive efficiency index, the average power supply reliability index, the average power outage frequency index, the average power outage time index, the load loss index, the construction and operation cost index, the unit load annual cost index, and the power outage loss cost index are respectively r 1 ,r 2 ,r 3 ,r 4 ,r 5 ,r 6 ,r 7 ,r 8 ,r 9 ,r 10 . Determine the second weight corresponding to the topological structure index, reliability index and economic index according to the hierarchical analysis method and the second weight ω of the second evaluation index information corresponding to the grid transfer capacity index, grid connectivity index, comprehensive efficiency index, average power supply reliability index, average power outage frequency index, average power outage time index, load loss index, construction and operation cost index, unit load annual cost index, and power outage loss cost index 1 ,ω 2 ,ω 3 ,ω 4 ,ω 5 ,ω 6 ,ω 7 ,ω 8 ,ω 9 ,ω 10 .

[0092] Following the above description, the first weight and the second weight are fused using the following formula to obtain the target weight:

[0093] Define the target weights to satisfy:

[0094]

[0095] In the formula, The target weight is calculated as follows:

[0096] (1) Calculate the deviation of each element in the i-th row

[0097]

[0098] (2) Calculate target weight

[0099]

[0100]

[0101] Furthermore, based on the target weight For multiple second evaluation index information c i Perform weighted summation to obtain the wiring evaluation sub-result The wiring evaluation sub-results in each time period are combined into the wiring evaluation results g={g1, g2, g3, ...} corresponding to the wiring mode, wherein g1 represents the wiring evaluation sub-result of the first year, g2 represents the wiring evaluation sub-result of the second year, and so on.

[0102] S140: Determine a target wiring mode for each time period based on the wiring evaluation result.

[0103] In this embodiment, the implementation method of determining the target wiring mode for each time period based on the wiring evaluation result can be described as the following steps:

[0104] a3) Draw lines for the wiring evaluation results corresponding to each wiring mode to obtain a line graph of the evaluation results;

[0105] The evaluation result line graph includes evaluation result lines corresponding to each wiring method.

[0106] For example, taking the single radial wiring method, the hand-in-hand wiring method and the 3-segment 2-connection wiring method as examples, Figure 2 The evaluation result line graph provided by the embodiment of the present invention is as follows: Figure 2 As shown, the horizontal axis represents the time period, and this embodiment takes 10 years as an example, and the vertical axis represents the wiring evaluation result.

[0107] b3) obtaining the intersection of any two evaluation result lines in the evaluation result line graph;

[0108] For example, in Figure 2In the example, the intersection points of any two evaluation result polylines are A, B and C.

[0109] c3) determining a connection transition mode based on two second evaluation index information located before and after the intersection;

[0110] The two second evaluation index information respectively belong to the evaluation index information corresponding to the two intersecting evaluation result polylines;

[0111] In this embodiment, the wiring transition method can be understood as a transition from wiring method 1 to wiring method 2. For example, at the intersection A, the wiring transition method is a transition from a single radial wiring method to a hand-in-hand wiring method or from a hand-in-hand wiring method to a single radial wiring method; at the intersection B, the wiring transition method is a transition from a single radial wiring method to a 3-segment 2-connection wiring method or from a 3-segment 2-connection wiring method to a single radial wiring method; at the intersection C, the wiring transition method is a transition from a hand-in-hand wiring method to a 3-segment 2-connection wiring method or from a 3-segment 2-connection wiring method to a hand-in-hand wiring method.

[0112] In this embodiment, the difference between the second evaluation index information of the two wiring modes before and after the transition is selected as the transition evaluation information of the wiring transition mode, and the transition difficulty index information and the scalability index information are introduced. The transition difficulty index information is used to characterize the transition difficulty between the two wiring modes before and after, and the scalability index information is used to characterize the scalability between the two wiring modes before and after.

[0113] Furthermore, considering the difference between the two wiring methods, the transition difficulty index f1 is used as a measurement index. Generally, the wiring transition between adjacent stages is easier, such as the "2-1" single-ring network and the two-supply and one-backup wiring is simpler than the "2-1" single-ring network and the "3-1" single-ring network. In addition, the scalability f2 between the two wiring methods is also used as a measurement index. Since the transition difficulty index f1 and the scalability index f2 are non-numerical indicators and there is no unified quantitative standard, the expert multi-digit ranking method is used to convert f1 and f2 into numerical values, and the scores are given according to the relative strength. The larger the f1, the more difficult the transition between the two wiring methods, and the larger the f2, the higher the scalability between the two wiring methods.

[0114] Continuing with the above description, the anti-entropy weight method is also used to determine the weights of the transition evaluation information, transition difficulty index information, and scalability index information; the weights of the transition evaluation information, transition difficulty index information, and scalability index information are determined according to the hierarchical analysis method; the above two weights are fused to obtain a comprehensive weight; based on the comprehensive weight, the transition evaluation information, transition difficulty index information, and scalability index information are weighted and summed to obtain the evaluation results of each wiring transition method; the final wiring transition method is obtained according to the evaluation results. Furthermore, the implementation method for obtaining the final wiring transition method according to the evaluation results is: using the idea of ​​controlling variables, first determine a wiring method before the transition, such as Figure 2 For the single radial wiring method, both points A and B can be its transition points. Through the evaluation results, the transition at point A is better than that at point B. Alternatively, a wiring method after the transition can be determined, such as the 3-segment 2-connection wiring method. Both points B and C can be its transition points. Through the evaluation results, the transition at point C is better than that at point B. Therefore, points A and C are selected, and the final wiring transition method is: from the single radial wiring method to the hand-in-hand wiring method, and then to the 3-segment 2-connection wiring method.

[0115] d3) Determine the target wiring mode for each time period based on the wiring transition mode.

[0116] Exemplarily, based on the above-mentioned final wiring transition method, it is determined that the single radial wiring method is used in the first 1-3 years, the hand-in-hand wiring method is used in the third to 5.5 years, and the three-segment two-connection wiring method is used in the fifth to ten years.

[0117] The technical solution of this embodiment obtains the power load information of each industry in the target distribution network area; determines the predicted load information of the target distribution network area based on the power load information of each industry and the set load growth information; evaluates multiple wiring methods based on the predicted load information, and obtains the wiring evaluation results corresponding to each wiring method; determines the target wiring method for each time period based on the wiring evaluation results. The above technical solution evaluates multiple wiring methods according to the predicted load information, and can accurately obtain the wiring evaluation results corresponding to each wiring method, thereby improving the accuracy of the wiring evaluation results; at the same time, the target wiring method for each time period is determined according to the wiring evaluation results, and the wiring method of the distribution network can be accurately determined. The technical solution provided by this embodiment can accurately obtain the wiring evaluation results corresponding to each wiring method, thereby improving the accuracy of the wiring evaluation results, so that the wiring method of the distribution network can be accurately determined.

[0118] Embodiment 2

[0119] Figure 3 A schematic diagram of a structure of a device for determining a connection mode of a power distribution network provided in a second embodiment of the present invention, such as Figure 3 As shown, the device comprises:

[0120] Information acquisition module 210, used to acquire power load information of various industries in the target distribution network area;

[0121] A predicted load information determination module 220, for determining predicted load information of a target distribution network area based on the power load information of each industry and the set load growth information;

[0122] An evaluation result obtaining module 230 is used to evaluate multiple wiring modes based on the predicted load information and obtain a wiring evaluation result corresponding to each wiring mode; wherein the wiring evaluation result includes wiring evaluation sub-results of multiple time periods, and each wiring evaluation sub-result is determined based on multiple evaluation indicators;

[0123] The target wiring mode determination module 240 is used to determine the target wiring mode for each time period based on the wiring evaluation result.

[0124] Optionally, the predicted load information determination module 220 may be specifically used for:

[0125] For each industry, the industry forecast load information is determined based on the set load growth information and the power load information;

[0126] The forecast load information of the target distribution network area is determined based on the industry forecast load information and its corresponding preset probability information.

[0127] Optionally, the device may further include: a predicted load information correction module, configured to, after determining the predicted load information of the target distribution network area based on the industry predicted load information and its corresponding preset probability information:

[0128] Obtaining the reported power consumption parameters of the target distribution network area; wherein the reported power consumption parameters include at least one of the reported load capacity, load factor, stage factor and load simultaneity rate;

[0129] Determine load correction information based on reported power consumption parameters;

[0130] The predicted load information is corrected based on the load correction information to obtain new predicted load information.

[0131] Optionally, the evaluation result obtaining module 230 may specifically include:

[0132] A first evaluation index information determining unit, configured to determine a plurality of first evaluation index information based on the predicted load information for each wiring mode;

[0133] A second evaluation index information determining unit, configured to determine a plurality of second evaluation index information of the wiring mode in each time period based on the plurality of first evaluation index information;

[0134] The wiring evaluation result obtaining unit is used to determine the wiring evaluation sub-results in each time period based on multiple second evaluation index information, and combine the multiple wiring evaluation sub-results into a wiring evaluation result corresponding to the wiring mode.

[0135] Optionally, the second evaluation index information determining unit may be specifically used to:

[0136] Based on the plurality of first evaluation index information, a plurality of second evaluation index information of the wiring mode in each time period is predicted in a preset manner.

[0137] Optionally, the wiring assessment result obtaining unit may specifically include:

[0138] A target weight determination subunit, used to determine the target weight of each second evaluation index information for each time period;

[0139] A wiring evaluation sub-result obtaining sub-unit, used to perform weighted summation on multiple second evaluation index information based on the target weight to obtain a wiring evaluation sub-result;

[0140] The wiring assessment result determination subunit is used to combine multiple wiring assessment sub-results into a wiring assessment result corresponding to the wiring mode.

[0141] Optionally, the target wiring mode determination module 240 may be specifically used for:

[0142] Draw lines for the wiring evaluation results corresponding to each wiring mode to obtain a line graph of the evaluation results; wherein the line graph of the evaluation results includes evaluation result lines corresponding to each wiring mode;

[0143] Get the intersection point of any two evaluation result lines in the evaluation result line graph;

[0144] Determine the connection transition mode based on two second evaluation index information located before and after the intersection; wherein the two second evaluation index information respectively belong to the evaluation index information corresponding to the two intersecting evaluation result polylines;

[0145] The target wiring mode for each time period is determined based on the wiring transition mode.

[0146] Optionally, the target weight determination subunit may be used to:

[0147] Determine a first weight of the second evaluation index information according to an anti-entropy weight method;

[0148] Determine a second weight of the second evaluation indicator information according to the analytic hierarchy process;

[0149] The first weight and the second weight are fused to obtain a target weight.

[0150] The above device can execute the methods provided by all the above embodiments of the present invention, and has the corresponding functional modules and beneficial effects of executing the above methods. For technical details not described in detail in this embodiment, please refer to the methods provided by all the above embodiments of the present invention.

[0151] Embodiment 3

[0152] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0153] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0154] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0155] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a method for determining a distribution network wiring mode.

[0156] In some embodiments, the method for determining the wiring mode of the distribution network may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for determining the wiring mode of the distribution network described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the method for determining the wiring mode of the distribution network by any other appropriate means (e.g., by means of firmware).

[0157] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0158] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0159] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0160] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0161] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0162] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0163] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0164] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for determining a wiring mode of a distribution network, characterized in that: include: Obtain the power load information of each industry in the target distribution network area; Determine the predicted load information of the target distribution network area based on the power load information of each industry and the set load growth information; Evaluate multiple wiring modes based on the predicted load information to obtain wiring evaluation results corresponding to each wiring mode; wherein the wiring evaluation results include wiring evaluation sub-results for multiple time periods, and each wiring evaluation sub-result is determined based on multiple evaluation indicators; A target wiring mode for each of the time periods is determined based on the wiring evaluation result.

2. The method according to claim 1, characterized in that: Determining the predicted load information of the target distribution network area based on the power load information of each industry and the set load growth information includes: For each industry, determining industry forecast load information based on the set load growth information and the power load information; The predicted load information of the target distribution network area is determined based on the industry predicted load information and its corresponding preset probability information.

3. The method according to claim 2, characterized in that After determining the predicted load information of the target distribution network area based on the industry predicted load information and the corresponding preset probability information, the method further includes: Obtaining the reported power consumption parameters of the target distribution network area; wherein the reported power consumption parameters include at least one of the reported load capacity, load factor, stage factor and load simultaneity rate; Determining load correction information based on the reported power consumption parameters; The predicted load information is corrected based on the load correction information to obtain new predicted load information.

4. The method according to claim 1, characterized in that: Based on the predicted load information, multiple wiring modes are evaluated to obtain wiring evaluation results corresponding to each wiring mode, including: For each wiring mode, determining a plurality of first evaluation index information based on the predicted load information; Determine a plurality of second evaluation index information of the wiring mode in each of the time periods based on the plurality of first evaluation index information; Based on the plurality of second evaluation index information, a wiring evaluation sub-result in each of the time periods is determined, and the plurality of wiring evaluation sub-results are combined into a wiring evaluation result corresponding to the wiring mode.

5. The method according to claim 4, characterized in that Determining a plurality of second evaluation index information of the wiring mode in each of the time periods based on the plurality of first evaluation index information includes: Based on the plurality of first evaluation index information, predicting a plurality of second evaluation index information of the wiring mode in each of the time periods in a preset manner; Correspondingly, determining the wiring evaluation sub-results in each of the time periods based on the plurality of second evaluation indicator information includes: For each time period, determining a target weight of each of the second evaluation indicator information; The plurality of second evaluation index information are weightedly summed based on the target weight to obtain a wiring evaluation sub-result.

6. The method according to claim 4, characterized in that Determining a target wiring mode for each time period based on the wiring evaluation result includes: Draw lines for the wiring evaluation results corresponding to each wiring mode to obtain a line graph of the evaluation results; wherein the line graph of the evaluation results includes evaluation result lines corresponding to each wiring mode; Obtain the intersection point of any two evaluation result broken lines in the evaluation result broken line graph; Determine the connection transition mode based on two second evaluation index information located before and after the intersection; wherein the two second evaluation index information respectively belong to the evaluation index information corresponding to the two intersecting evaluation result polylines; A target wiring mode for each of the time periods is determined based on the wiring transition mode.

7. The method according to claim 5, characterized in that Determining a target weight of each of the second evaluation indicator information includes: Determine a first weight of the second evaluation index information according to an anti-entropy weight method; Determine a second weight of the second evaluation index information according to the hierarchical analysis method; The first weight and the second weight are fused to obtain a target weight.

8. A device for determining a connection mode of a distribution network, characterized in that: include: An information acquisition module is used to obtain the power load information of various industries in the target distribution network area; A predicted load information determination module, used to determine the predicted load information of the target distribution network area based on the power load information of each industry and the set load growth information; An evaluation result obtaining module, used to evaluate multiple wiring modes based on the predicted load information, and obtain wiring evaluation results corresponding to each wiring mode; wherein the wiring evaluation results include wiring evaluation sub-results of multiple time periods, and each wiring evaluation sub-result is determined based on multiple evaluation indicators; The target wiring mode determination module is used to determine the target wiring mode of each time period based on the wiring evaluation result.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for determining the connection mode of the distribution network according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for determining the power distribution network connection mode according to any one of claims 1 to 7 when executed.

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