Power distribution system configuration construction method, power distribution system configuration construction system, and power distribution system configuration construction program

Abstract

To partially detail the granularity of a section model according to a tidal flow state (voltage and current) of a branch line of a distribution system in the construction of a specified time-area standard system configuration of the distribution system.SOLUTION: A power distribution system configuration construction system constructs a power distribution system configuration on the basis of a section model that aggregates information on distribution facilities within a section in which a power distribution model with distribution facilities as nodes is partitioned at an arbitrary node. The power distribution system configuration construction system executes a power distribution system configuration construction method. The power distribution system configuration construction system has a main storage device and a processing device. The power distribution system configuration construction system generates a variable granularity section model that aggregates information on power distribution facilities within a section having the possibility of violating an operational constraint at a second granularity that is even more detailed than a first granularity on the basis of a tidal flow state on a branch line of the power distribution system model. Further, the power distribution system configuration construction system executes a tidal current analysis in a specified time period on the basis of the variable granularity section model and constructs a power distribution system configuration on the basis of results obtained by executing the tidal current analysis.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present invention relates to a power distribution system configuration construction method, a power distribution system configuration construction system, and a power distribution system configuration construction program. [Background technology]

[0002] Generally, a power distribution system consisting of multiple distribution lines is divided into multiple sections by switches to prevent the spread of the effects of an accident and ensure the reliability of the power supply, as shown in an example in Figure 1. Each section receives power from a feeder. The distribution line of a certain feeder is connected to the distribution line of another feeder by an interconnection switch that is normally open. Therefore, by operating the on / off state of the switch, the system configuration changes, and the power flow also changes significantly.

[0003] In addition, power distribution systems usually operate according to a standard system configuration (hereinafter referred to as the standard system configuration) that takes into consideration the maintenance of appropriate voltage and smooth system operation during both normal and accidental conditions.

[0004] In recent years, many distributed power sources, including photovoltaic power generation, have been connected to distribution systems. In systems where distributed power sources are not connected, power flows are one-way, from upstream substations to end consumers. However, as the number of distributed power sources connected to the system increases, the power flows within the system have become more complex, including reverse power flows from end distributed power sources. As a result, there is an increased possibility of problems occurring, such as violations of distribution system operational constraints, such as overloads and voltage deviations in bank transformers and distribution lines. Therefore, it is necessary to form a distribution system configuration that satisfies the operational constraints of the distribution system and enables smooth system operation, depending on the power flow state within the system.

[0005] Patent Document 1 describes a method for optimizing a power distribution system configuration that uses an exact solution to calculate a configuration that minimizes power distribution loss in a power distribution network that employs a multi-division, multi-interconnection power system such as a three-division, three-interconnection power distribution system. In the method for optimizing a power distribution system configuration disclosed in Patent Document 1, in order to efficiently narrow down candidates that satisfy the operational constraints, the system is divided into multiple closed partial feeders with less than three interconnections, and all configurations that satisfy the operational constraints are searched for within the partial feeders, thereby making it possible to efficiently narrow down candidates that satisfy the operational constraints. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2006-217689 A Summary of the Invention [Problem to be solved by the invention]

[0007] Since most of the distributed power sources are naturally variable power sources such as photovoltaic power generation, the power generation output changes depending on the time and season, and the current state in the power distribution system changes from moment to moment accordingly. Therefore, it is ideal to change the system configuration at any time according to the current state by using, for example, the distribution system configuration optimization method described in Patent Document 1, and to maintain a state in which the system can always be operated smoothly. However, frequent changes in the system configuration lead to an increase in the number of switchgear operations, which causes problems such as a shortened equipment lifespan, increased maintenance costs, and increased burdens on system operators.

[0008] Therefore, we will consider constructing a reasonable standard system configuration (hereinafter, "standard system configuration for a specified time range") for any specified time range, such as a season (summer, winter, intermediate season) or a period when distribution equipment is not operational (hereinafter, "specified time range").

[0009] However, when constructing a standard system configuration for a specified time region, a large number of system configuration candidates are generated for each time region, and when evaluating the system configuration candidates to select the most appropriate standard system configuration for the specified time region, it is necessary to perform analyses simulating multiple supply and demand scenarios, which increases the amount of calculations.

[0010] In order to deal with the increase in the amount of calculations, a detailed system model (hereinafter, detailed model) is not practical in terms of the amount of calculations, because a distribution system has a huge number of facilities. In general, a distribution system is analyzed using a model (hereinafter, section model) that aggregates data on load and line impedance for each section, as shown in Figure 1. When generating a section model from a detailed model, data on load and line impedance are aggregated as one section, as shown in Figure 2, by aggregating the range surrounded by switches, voltage regulators, and trunk branch points. Distribution lines that branch off from a trunk (hereinafter, branch lines) have a smaller amount of power flow than the trunk, so they are generally considered as loads and aggregated in the trunk. However, when distributed power sources are concentrated at the terminal points of the system, such as branch lines, the amount of power flow in the branch lines also increases. In the past, branch lines were simplified when modeling, which led to the issue of overlooking violations of operational constraints in the branch lines.

[0011] In Patent Document 1, the model used to determine the configuration of a power distribution system considers an area surrounded by switches as one section, and branch lines are simplified, resulting in a similar problem.

[0012] The present invention has been made in consideration of the above points, and aims to provide a technology for partially refining the granularity of a section model according to the power flow conditions (voltage and current) of the branch lines of a power distribution system when constructing a standard system configuration for a specified time range of the power distribution system. [Means for solving the problem]

[0013] In order to solve the above-mentioned problems, the present invention provides a distribution system configuration construction method for constructing a distribution system configuration based on a section model that aggregates information on distribution equipment within sections obtained by dividing a distribution system model, in which the distribution equipment is a node, at any node, and the distribution system configuration construction system having a main memory device and a processing device generates a variable-granularity section model that aggregates information on the distribution equipment within a section where operational constraints may be violated at a second granularity that is finer than a first granularity based on the power flow state at a branch line of the distribution system model, performs a power flow analysis in a specified time range based on the variable-granularity section model, and constructs the distribution system configuration based on the results of the power flow analysis. Effect of the Invention

[0014] According to the present invention, in constructing a standard system configuration for a specified time range of a power distribution system, the granularity of a section model can be partially refined according to the power flow state (voltage and current) of a branch line of the power distribution system. [Brief description of the drawings]

[0015] [Figure 1] A diagram showing a typical power distribution system model. [Diagram 2] A diagram showing a detailed model and section model of a typical power distribution system. [Diagram 3] FIG. 1 is a diagram showing a power distribution system configuration construction system according to an embodiment. [Figure 4] FIG. 1 is a diagram showing the procedure for constructing a standard system configuration for a specified time range. [Diagram 5] FIG. 13 is a diagram showing a processing procedure for generating a granularity variable section model. [Figure 6] FIG. 2 is a diagram showing an example of a power distribution system model. [Figure 7] FIG. 13 is a diagram showing a process image in which the state of a switch that is not the object of operation is reflected in a detailed model. [Figure 8] FIG. 4 is a diagram showing a procedure for generating a tentative section model. [Figure 9] FIG. 13 is a diagram showing an example of a provisional section model. [Figure 10] FIG. 13 is a diagram showing a process image of calculating a node power flow state in a branch line section. [Figure 11]FIG. 13 is a diagram showing an example of a power flow state calculation result at a branch line section node. [Figure 12] FIG. 13 is a diagram showing an example of a granularity variable section model for each voltage error allowable threshold value. [Figure 13] FIG. 13 is a graph showing the relationship between the voltage error tolerance threshold and the number of interval nodes of a granularity variable interval model. [Figure 14] FIG. 13 is a diagram showing an example of a granularity variable section model. [Figure 15] FIG. 13 is a diagram showing a processing procedure for generating standard system configuration candidates for a specified time range. [Figure 16] FIG. 13 is a diagram showing an example of a severe cross section extraction table. [Figure 17] FIG. 13 is a diagram showing an example of a comparison and evaluation screen for standard system configuration candidates for a specified time range. [Figure 18] A diagram showing computer hardware. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] Hereinafter, the embodiments of the present application will be described with reference to the drawings. Note that the embodiments described below, including the drawings, are merely examples and do not limit the invention according to the claims. In addition, not all of the elements and combinations thereof described in the embodiments are necessarily essential to the solution of the invention. In addition, illustrations and descriptions of configurations that are essential to the configuration of the invention but are well known may be omitted.

[0017] In the following description, when elements of the same type are described without distinction, reference signs (or common signs among reference signs) may be used, and when elements of the same type are described with distinction, identification numbers (or reference signs) of the elements may be used. Furthermore, the number of elements shown in each figure is an example and is not limited to the number shown in the figures.

[0018] In the following description, various information may be described using expressions such as "xxx table" or "xxx table", but the various information may be expressed in a data structure other than a table. Since the various information does not depend on the data structure, the "xxx table" or "xxx table" can be called "xxx information".

[0019] In the following description, a "section" refers to each part of a power distribution system divided by a switch, a voltage regulator, etc. Also, a "section model" is a model of a "section" by appropriately simplifying or detailing nodes such as branches and power distribution equipment within the "section" in order to reduce the calculation load of power flow analysis in a power distribution system. EXAMPLES

[0020] <Outline of the Example> The power distribution system configuration construction system in this embodiment is a system that constructs a new standard system configuration for a specified time range by optimization calculation using a "variable granularity section model" in which the granularity of the model is partially refined from a first granularity to a second granularity according to the power flow state of the power distribution system when constructing a standard system for a specified time range. Also, the "granularity of the model" refers to the degree to which the nodes in the "section" are simplified or detailed when modeling the "section."

[0021] <Configuration of the power distribution system configuration construction system> 3 shows a power distribution system configuration construction system according to the present embodiment. The power distribution system configuration construction system 1 includes a granularity variable section model generation unit 10, a specified time range standard system configuration construction unit 20, a power distribution system database 30, an input device 40, and an output device 50.

[0022] The granularity variable section model generation unit 10 includes a modeling condition setting unit 11 for setting the generation conditions of the detailed model and the section model, a detailed model generation unit 12 for generating a detailed model of the target power distribution system from the power distribution facility data, a provisional section model generation unit 13 for generating a section model (hereinafter, provisional section model) in which a section is provisionally divided at all branch points in the specified facility and the detailed model, a branch line section node power flow state calculation unit 14 for calculating the power flow state in a specified time range of a section node (hereinafter, branch line section node) belonging to a branch line in the provisional section model, a model granularity refining condition setting unit 15 for setting the condition for partially refining the granularity of the model according to the power flow state of the provisional section model, and a section model granularity adjustment unit 16 for adjusting the granularity of the provisional section model according to the power flow state. The details of each processing function of the granularity variable section model generation unit 10 will be described later.

[0023] The specified time range standard system configuration constructing unit 20 includes an optimization calculation target load cross section selector 21, an optimal configuration problem calculator 22, a system configuration candidate power flow analyzer 23, and a system configuration candidate multiple cross section evaluator 24. Details of each processing function of the specified time range standard system configuration constructing unit 20 will be described later.

[0024] The power distribution system database 30 according to this embodiment includes power distribution facility data 31, facility status data 32, and load / power generation forecast scenario 33. Moreover, the power distribution system database 30 is realized by a storage device. The power distribution facility data 31, facility status data 32, and load / power generation forecast scenario 33 are examples of data stored in the power distribution system database 30, and data other than these may also be stored.

[0025] The input device 40 is implemented by including at least one of a keyboard, a pointing device such as a mouse, a touch panel, and a voice instruction device.

[0026] The output device 50 is a display device, a printer, an audio output device, or the like, and is realized by including at least one of them.

[0027] The power distribution system configuration construction system 1 is implemented on a circuit, a printed circuit board, a server, an information processing device, etc., including a controller such as a CPU (Central Processing Unit) or a microprocessor, a storage device such as a memory, a hard disk, or an SSD (Solid State Drive), and a communication device. The power distribution system configuration construction system 1 may be realized by software in which a controller performs processing according to various programs stored in the storage device, or may be realized by hardware such as a circuit, or may be realized by software that performs processing on the cloud.

[0028] <Procedure for constructing standard system configuration for a specified time range> Fig. 4 shows the procedure for constructing a standard system configuration for a specified time range according to this embodiment. This procedure starts when a request for constructing a standard system configuration for a specified time range is received from the input device 40 in the power distribution system configuration construction system 1, and the process ends when the standard system configuration for a specified time range is output to the display device. In the following, an overview of the procedure for creating a standard system configuration for a specified time range will be described based on the flowchart in Fig. 4.

[0029] First, in step S401, the designated time range standard system configuration constructing unit 20 accepts the setting of the designated time range. The designated time range may be inputted as a period via the input device 40, or may be read as a period previously set, for example, by season (summer, winter, intermediate season, etc.).

[0030] Next, in step S402, the variable-granularity section model generation unit 10 calculates the power flow state of the branch line in the specified time range from the detailed model, and generates a variable-granularity section model in which the points where there is a high possibility of violating operational constraints are partially detailed.

[0031] In step S403, the optimization calculation target load cross-section selection unit 21 and the optimal configuration problem calculation unit 22 use the granularity-variable section model generated in step S402 to generate standard system configuration candidates for the specified time range through combinatorial optimization calculations, and extract multiple top candidates (hereinafter, system configuration candidates) with high objective function scores.

[0032] In the following step S404, system configuration candidate power flow analyzer 23 performs a power flow analysis in a specified time range for the system configuration candidates generated in step S403.

[0033] In step S405, the system configuration candidate power flow analysis unit 23 checks the operational constraints of the power flow analysis results. If there is a violation of the operational constraints in the specified time range, the optimal configuration problem calculation unit 22 adds the violating section to the target section of the optimization calculation in step S403 and generates system configuration candidates again. If there is no violation of the operational constraints, in step S406, the system configuration candidate multi-section evaluation unit 24 performs a multi-section evaluation for each system configuration candidate based on the analysis results in step S404.

[0034] In step S407, the system configuration candidate multi-view evaluation unit 24 finally determines the designated time range standard system configuration based on the multi-view evaluation result in step S406.

[0035] <Processing procedure for generating variable granularity interval models> 5 shows the procedure for generating a granularity-variable section model in step S402. Hereinafter, the procedure for generating a granularity-variable section model will be described in detail using a detailed model example 600 shown in FIG.

[0036] In step S501, the modeling condition setting unit 11 sets a section division node and a switch to be operated. The section division node indicates a node (power distribution equipment and connection node) that is a reference for dividing a section when generating a section model. Usually, the power distribution equipment that is the target of section division is a switch and an SVR (Step Voltage Regulator). Furthermore, a connection node (hereinafter, a trunk branch connection node) that is a branch point of a trunk line is also a section division node.

[0037] In addition, a connection node at a branch point of a distribution line, not limited to a trunk line, is referred to as a branch connection node, and among all the branch connection nodes, a branch point of a trunk line is particularly referred to as a trunk branch connection node, and hereinafter, the branch connection nodes are distinguished. In addition, other distribution facilities and connection nodes may be additionally designated as section division nodes by the input device 40. For example, a location where the power flow state is to be monitored with priority, such as a connection node to a high-voltage consumer with a certain capacity or more, is designated.

[0038] In the detailed model example shown in FIG. 6, the equipment to be divided into sections are switches 601, 602, 604, and SVR 603. In addition, in the setting of the switch to be operated, switches that can be operated to open or close in the system configuration construction are extracted. For example, there are cases in which only remote control switches that can be remotely operated from a power distribution automation system or the like are set as the operation target, and manual switches that require on-site work are set as the non-operation target (the current open / close state is maintained). Note that the switch to be operated is set as the section division target, and the non-target switch maintains the current open / close state, and is used to express the connection relationship of the system when generating a detailed model described later. The setting of the switch to be operated may be set uniformly in advance using the switch attributes (remote control and manual, etc.), or may be set for each switch by the input device 40.

[0039] In step S502, the detailed model generation unit 12 generates a detailed model of the target system of the specified time range standard system configuration based on the power distribution equipment data 31. As shown in the detailed model example 600, the detailed model is a graph model in which nodes correspond to power distribution equipment and connection nodes, and edges indicate the relationship between the power distribution equipment and the connection nodes. In this embodiment, the model structure is such that the connection relationship between the power distribution equipment is via the connection nodes. This model structure is a structure conforming to the Common Information Model (CIM), an international standard in the power distribution sector. Note that this model structure is merely an example, and any other model structure may be used as long as it is possible to grasp the connection relationship of the power distribution equipment.

[0040] Reflection of the switch state not subject to operation set in step S501 in the detailed model will now be described with reference to Fig. 7 as an example. Fig. 7 shows an example in which only remote control switches are subject to operation and the open / closed state of manual switches is reflected in the detailed model. First, the current open / closed state of the manual switch is acquired in detailed model 701 before switch state reflection. Next, based on the open / closed state of the manual switch, normally open switches are converted to a non-connected state 711 and normally closed switches are converted to a connected state 712, as in detailed model 702 after open / closed state reflection. Through the above procedure, the switch state not subject to operation set in step S501 is reflected in the detailed model.

[0041] In step S503, the provisional section model generating unit 13 generates a provisional section model based on the detailed model. As described above, the provisional section model refers to a section model in which a section is provisionally divided for each section division node and all branch connection nodes in the detailed model. Details of this process are shown in FIG. 8, and will be described below for the detailed model example 600.

[0042] First, in step S801, the provisional section model generating unit 13 sets section division nodes. The section division nodes include connection nodes that connect to the section division equipment set in step S602 and connection nodes that correspond to branch points of the trunk line. In the detailed model example 600, connection nodes 611, 613, 614, 615, and 617 that connect to the section division equipment and connection node 612 that corresponds to the branch point of the trunk line are set as section division nodes.

[0043] Next, in step S802, the provisional section model generating unit 13 specifies trunk lines and extracts all branch connection nodes in the detailed model. The trunk lines are specified by searching for routes connecting the section division nodes in the detailed model. In addition, the route from the branch connection node of the trunk line route to the model end corresponds to the branch line. The route search can be realized by using a general graph search method. In addition, the branch connection node can be extracted by identifying a connection node where the distribution line route branches into two or more. In the detailed model example 600, the route from the switch 601 to 602 and the route from the switch 601 to 604 correspond to the trunk line, and the routes 621, 622, 623, and 624 correspond to the branch lines. In addition, the connection nodes 611, 612, 613, 615, and 616 correspond to the branch connection nodes. In addition, the branch connection nodes may overlap with the section division nodes.

[0044] Next, in step S803, section node aggregation is performed based on the branch connection node and section division node extracted in step S802 to generate a provisional section model. The section node aggregation method searches for all routes from the section division node as the starting point to other section division nodes, and aggregates the facility node groups and connection node groups on the routes into one section node. After section node aggregation at the branch connection node is complete, it is output as a provisional section model and this process ends.

[0045] Fig. 9 shows an example of a provisional section model corresponding to the detailed model example 600. In the detailed model example 600, connection nodes 611-617 correspond to section division nodes in the provisional section model, and step S803 generates a provisional section model having section nodes for all 10 sections shown in Fig. 9. Note that hereinafter, section nodes belonging to main lines are distinguished as main line section nodes (corresponding to A1, B1, C1, and D1 in Fig. 9), and section nodes belonging to branch lines are distinguished as branch line section nodes (corresponding to A2, B2, B3, D2, D3, and D4 in Fig. 9).

[0046] After the provisional section model is generated, in step S504, the branch line section node power flow state calculation unit 14 calculates the power flow state for the specified time range of the branch line section node in the provisional section model. As described above, in the conventional section model, the load of the branch line is uniformly aggregated to the main line, and the operational constraints on the branch line cannot be adequately monitored. Therefore, in the branch line, the points where the operational constraint violation is highly likely must be detailed when the section model is generated (the granularity of the section model must be increased).

[0047] Therefore, in step S504, information on the load and power generation in the branch line section node and the line impedance of the distribution line is collected, and the line passing current and voltage fluctuation are calculated. The line passing current is a value required for monitoring the line current capacity constraint, and the voltage fluctuation is a value required for monitoring the voltage upper and lower limit constraint. Hereinafter, the calculation procedure will be explained with reference to FIG. 10, taking the section nodes D1 to D4 of the provisional section model in FIG. 9 as an example.

[0048] First, the load, power output, and line impedance values ​​are found for each section node from the information on the power distribution equipment in the section node. Since one section node includes the load, power output, and line impedance, it can be expressed by a bus-branch model in which the load and power output correspond to the bus, and the line impedance corresponds to the branch, as shown in Figure 10. In other words, the power flow state at the branch line section node is calculated for the route from bus B1 to buses B2, B3, and B4.

[0049] Next, the time series data of the load and power output in the specified time range (hereinafter, load cross section) is read from the load / power generation forecast scenario 33 and linked to the corresponding load / power source node. After that, the load and power output in the branch line section node are added up for each cross section in the load cross section. For distribution lines, the impedance of the distribution line node in the branch line section node is calculated as a weighted average of the line length to calculate the line impedance.

[0050] The method for calculating the line current is explained below. First, the current consumed within the section node (hereinafter, section consumption current) is calculated from the load and power node information within the section node. There are multiple procedures for calculating the section consumption current, as shown below, depending on the data items held by the load and power node.

[0051] (1) When the current value data itself is available If the load and power supply nodes have current value data, the section current consumption can be calculated by directly adding up the current values.

[0052] (2) When active and reactive power data is available If the load-power node has active power and reactive power data, the section current consumption can be calculated using the following formula.

[0053]

number

[0054] Taking the branch line section node D4 in FIG. 10 as an example, the section consumption current in a certain load cross section is expressed by the following equation.

[0055]

number

[0056] (3) When data on active power and power factor, or active power only, is available If the load-power node has data on active power and power factor, or only active power, the section current consumption can be calculated using the following formula.

[0057]

number

[0058] Taking the branch line section node D4 in FIG. 10 as an example, the section consumption current in a certain load cross section can be expressed by the following equation.

[0059]

number

[0060] After calculating the section current consumption, the line current passing through the section is calculated by adding up the section current consumption values ​​starting from the branch line section node at the end. That is, the line current passing through a certain branch line section node can be calculated using the following formula.

[0061]

number

[0062] Next, the voltage fluctuation within the section is calculated using the following formula based on the line impedance value, which is the weighted average of the line current and the line length.

[0063]

number

[0064] After calculating the voltage fluctuation within the section, the voltage fluctuations of each branch line section node on the path from the branch line section node to the trunk line are added together to determine the voltage fluctuation from the trunk line to the branch line section node. In other words, the voltage fluctuation from the trunk line at a branch line section node can be calculated using the following formula.

[0065]

number

[0066] Using the above calculation method, the line passing current and voltage fluctuation from the trunk line at a branch connection node in a certain load cross section are calculated. By performing similar calculations for all load cross sections in a specified time range, time series data of the line passing current and voltage fluctuation from the trunk line for each branch connection node is obtained.

[0067] Next, a decision is made to aggregate the branch line section nodes into main line section nodes based on the line passing current at the branch connection node and the voltage fluctuation from the main line, and a granularity variable section model is generated. First, in step S505, a line current capacity condition and a voltage error tolerance condition are set as the aggregation decision of the section node, i.e., the granularity refinement condition of the section model.

[0068] The line current capacity condition corresponds to the current capacity constraint, and is a condition that determines not to aggregate a branch line section node when the ratio of the line current passing through it to the current capacity (normal capacity) of the distribution line at the branch line section node (hereinafter, the line current passing ratio) is equal to or greater than a threshold value. This condition is intended to refine the model granularity, because if the line current passing ratio is equal to or greater than a certain level, there is a high possibility of violating the current capacity constraint.

[0069] The voltage error tolerance condition corresponds to the upper and lower voltage limit constraints, and is a condition for determining not to aggregate the branch connection node if the voltage fluctuation from the trunk line is equal to or greater than a threshold value. In conventional section models, the load and power generation output of the branch lines are uniformly aggregated to the trunk line, so the voltage fluctuation of the branch lines could not be taken into consideration. Therefore, even if it is determined that the upper and lower voltage limit constraints are satisfied on the trunk line, if the voltage fluctuation of the branch line is large, the constraint may be violated on the branch line. Therefore, a process is applied in which a tolerance threshold value is set for the voltage fluctuation from the trunk line at the branch line section node, i.e., the voltage error caused by aggregating the branch connection node, and branch line section nodes with voltage fluctuations equal to or greater than the threshold value are left detailed.

[0070] In step S505, the model granularity refining condition setting unit 15 sets the line current capacity condition threshold and the voltage error allowable threshold. However, since the voltage error allowable threshold cannot be expressed as a capacity ratio like the threshold of the line current capacity condition, in this embodiment, the voltage error allowable threshold is determined by sensitivity analysis. Therefore, the change range and the change width of the voltage error allowable threshold are set. For example, the voltage error allowable threshold is set to change from 0.005 pu to 0.020 pu in increments of 0.005 pu.

[0071] Next, in step S506, the section model granularity adjustment unit 16 adjusts the granularity of the section model based on the line current capacity condition threshold and the voltage error tolerance threshold set in step S505, to generate a granularity variable section model. Here, Fig. 11 shows an example 1100 of a power flow state calculation result at a branch line section node in the provisional section model in Fig. 9. Note that for the line passing current and the voltage fluctuation from the main line, the maximum value in a specified time range is used to determine the granularity refinement condition of the section model.

[0072] As an example, assume that the line current capacity condition threshold is set to 75% and the voltage error tolerance threshold is set to 0.005 pu to 0.020 pu in increments of 0.005 pu. Here, examples of granularity variable section models generated when the voltage error tolerance threshold is set to 0.005 pu, 0.010 pu, and 0.020 pu based on the provisional section model in Fig. 9 are shown in Fig. 12(a) to (c).

[0073] First, under the line current capacity condition (=75%), only D2 exceeds the threshold at 80% according to the line passing current ratio value in power flow analysis example 1100, so D2 is excluded from the aggregation judgment target, and the other branch line section nodes are aggregation judgment targets. Next, under the voltage error tolerance condition, in the case of (a) 0.005 pu, A2 and B3 are below the threshold value according to the maximum voltage fluctuation value from the trunk in power flow state calculation result example 1100, so A2 is aggregated as a load to trunk section node A1, and B3 is aggregated as a load to trunk section node B1. As for B2, D3, and D4, their maximum voltage fluctuation values ​​are above the threshold value, so they are maintained in a detailed state. By the above processing, a granularity variable section model can be generated.

[0074] Similarly, (b) when the voltage error tolerance threshold is 0.010 pu, in addition to A1 and B3, D4 is also subject to aggregation. D4 is aggregated as a load to D2, one line away. (c) When the voltage error tolerance threshold is 0.020 pu, D3 also becomes a subject to aggregation, and is aggregated together with D4 as a load to D2. As described above, the granularity of the section model is adjusted based on the line current capacity conditions and voltage error tolerance, and a variable-granularity section model is generated.

[0075] Next, in step S507, one of the voltage error allowable thresholds set in step S506 is determined by sensitivity analysis.

[0076] Figure 13 is an example of a graph plotting the relationship between the voltage error tolerance threshold and the number of section nodes in the generated granularity variable section model. As the voltage error tolerance threshold is increased, the range of voltage fluctuations from the main line at the branch line section node is allowed to expand, and the number of branch line section nodes to be aggregated increases, so the total number of section nodes in the granularity variable section model decreases.

[0077] Here, the voltage error allowable threshold at which the number of section nodes converges is automatically extracted from the sensitivity analysis graph and determined as the final voltage error allowable threshold. In the example of Fig. 13, the number of section nodes nearly converges at the voltage error allowable threshold 1300, so this value is determined as the final voltage error allowable threshold. Note that as a method of determining the voltage error allowable threshold, the sensitivity analysis graph may be output to the output device 50, and the user may determine the voltage error allowable threshold based on the sensitivity analysis results.

[0078] Finally, in step S508, the granularity variable section model for the voltage error allowable threshold determined in step S507 is output. Also, as in a granularity variable section model example 1400 shown in Fig. 14, the finally determined granularity variable section model is output to the output device 50 so that the user can confirm the model structure. In the granularity variable section model example 1400, sections 13, 7, and 16 are detailed in steps S504 to S507. In addition, as in a section node expansion diagram 1401 in the granularity variable section model example 1400, the configuration contents of one section node may be expanded and displayed.

[0079] By refining as in the section node expansion diagram 1401, when a section aggregated near a threshold or an important load (such as PV (Plug-in electric vehicle)) is connected, the contents can be confirmed. In the section node expansion diagram 1401, the power flow analysis result of the branch line section node calculated in step S504 may also be displayed, and the model granularity may be adjusted by the input device 40. In addition, in response to a user instruction, as in the section node expansion diagram 1401, a section displayed on the output device 50 at the first granularity so as to be able to be detailed and displayed at a second granularity (number of nodes) that is more detailed than the first granularity (number of nodes) may be re-aggregated at the second granularity to regenerate a granularity variable section model. In this way, the user can visually determine the granularity of the granularity variable section model, and generate a granularity variable section model at the determined granularity.

[0080] By performing steps S501 to S508 above, a granularity-variable section model can be generated, and the generated granularity-variable section model is input as a section model used for the subsequent construction of a specified time range standard system configuration.

[0081] <Construction and evaluation of standard system configuration candidates for specified time range> In this embodiment, an optimal configuration is constructed by optimizing the combination of the open / closed states of switches. The optimal configuration problem of a distribution system is a calculation with a high computational load. Therefore, first, a single objective function (minimizing distribution loss in this embodiment) is set for a certain low-load section, and system configuration candidates are generated. Then, a power flow analysis is performed in a specified time range for each system configuration candidate, and a multi-sectional evaluation is performed on multiple items including distribution loss, and the final standard system configuration for the specified time range is determined. Each process will be described in detail below.

[0082] FIG. 15 shows the procedure for generating standard system configuration candidates for the specified time range in step S403.

[0083] First, in step S1501, the load cross section selection unit 21 for optimization calculation selects a load cross section to be the target of the optimal configuration problem from among the load cross sections in the specified time range. The optimal configuration problem in a power distribution system is a combinatorial optimization of switch states. In the case of a power distribution system of a general scale, the number of combinations of switch states becomes very large, resulting in an optimization calculation with a high calculation load. Ideally, it is preferable to input all load cross sections in the specified time range as the load and power generation output patterns (load cross sections) that serve as input data when formulating, but this is not practical from the viewpoint of the amount of calculation.

[0084] Therefore, the load cross section targeted in the optimal configuration problem needs to be narrowed down to a single cross section or a few small cross sections. As the target load cross section, for example, the cross section where the substation bank load is at its maximum (maximum load cross section), which is generally used in the design standards for facility planning of power distribution systems, is selected. When there are few distributed power sources, the maximum load cross section is the most severe in terms of operational constraints, and so it was appropriate as the target load cross section for the optimal configuration.

[0085] However, when there are many distributed power sources, the most severe load cross section may be a cross section other than the maximum load cross section when reverse power flow is taken into consideration. Therefore, in this embodiment, the most severe cross section is extracted from the power flow state calculation result of the branch line section node calculated in step S504, and selected as the target load cross section for the optimal configuration.

[0086] The method of extracting the severe cross sections will be described with reference to the severe cross section extraction table example 1600 in FIG. 16. First, among all the branch line section nodes in the granularity variable section model, the number of sections (column 1602) in which the line passing current is at the maximum value and the number of sections (column 1603) in which the voltage fluctuation from the trunk line is at the maximum value are calculated in the load cross section t (column 1601). Then, ranking is performed by the total number 1604 of 1602 and 1603. A load cross section with a high ranking is a severe cross section that is likely to deviate from the operational constraints, and is therefore a load cross section that should be the target of the optimization configuration. Therefore, the top single cross section or the top small cross section is selected as the load cross section to be optimized. Note that the maximum load cross section may be selected as the load cross section to be optimized, or any load cross section may be selected from the input device 40.

[0087] Next, in step S1502, the optimum configuration problem calculation unit 22 formulates an optimum configuration problem based on the input data of the granularity variable section model and the load cross section to be optimized. In this embodiment, an optimum configuration problem is set with the objective of minimizing distribution loss. The objective function for minimizing distribution loss is expressed by the following equation.

[0088]

number

[0089] In this embodiment, taking into consideration the calculation load of the optimal configuration problem, a single objective function is set as an evaluation item that prioritizes distribution loss. However, multi-objective optimization may be used that includes objectives other than minimizing distribution loss.

[0090] The constraints include a radial configuration constraint, a line current capacity constraint, and an upper and lower voltage limit constraint, which are formulated as follows:

[0091]

number

[0092]

number

[0093]

number

[0094] As described above, after the optimum configuration problem is formulated, in step S1503, the optimum configuration problem calculation unit 22 executes an optimization calculation and extracts system configuration candidates.

[0095] In this embodiment, the solution method for the optimal configuration problem is not limited. For example, as in Patent Document 1, an exact solution method incorporating a method for efficiently searching for a solution by focusing on the characteristics of the distribution system configuration may be used. Also, as in JP 2004-129404 A, a metaheuristic solution method such as a genetic algorithm may be used. After performing the optimization calculation, the exact solution method or metaheuristic solution method can generate multiple system configuration candidates along with a configuration with minimum distribution loss. This optimal configuration problem is an optimal configuration candidate for the low load section selected in step S1501, and is not necessarily an optimal system configuration throughout the specified time range. Therefore, the top system configuration candidates with the lowest distribution loss, for example the top 10 candidates, are extracted, and a multi-section evaluation is performed in the subsequent specified time range.

[0096] The power flow analysis of the designated time range standard system configuration candidate in step S404 will be described in detail. System configuration candidate power flow analysis unit 23 performs power flow analysis in the designated time range for each designated time range standard system configuration candidate extracted in step S403. The power flow analysis calculates the section line passing current and section voltage for each section. The section line passing current is calculated using Equation 1, Equation 3, and Equation 5. The section voltage is calculated by calculating the voltage fluctuation for each section using Equation 6 and subtracting it from the feeder sending voltage to the feeder end in order as shown in Equation 12.

[0097]

number

[0098] The above calculations are used to perform a power flow analysis in a specified time range. Note that the power flow analysis may be performed using a strict power flow calculation such as the Newton-Raphson method.

[0099] Next, in step S405, the system configuration candidate power flow analysis unit 23 performs an operational constraint check of the power flow analysis result of the standard system configuration candidate for the specified time region. It is confirmed that the line current capacity constraint and the voltage upper and lower limit constraint are satisfied in all sections as operational constraints, and the total load amount of each feeder does not exceed the capacity of the bank transformer. If there is a system configuration candidate that violates the operational constraints, the corresponding system configuration candidate is excluded from the multi-sectional evaluation. If an operational constraint violation occurs in all system configuration candidates, the load section where the constraint violation occurs is added to the load section to be optimized, and step S403 is re-executed. Note that the condition for re-executing the system configuration candidate generation is not limited to the occurrence of an operational constraint violation in all system configuration candidates, and may be an arbitrary ratio, for example, a condition that an operational constraint violation occurs in 50% or more of the system configuration candidates.

[0100] Next, in step S406, the system configuration candidate multi-faceted evaluation unit 24 performs a multi-faceted evaluation for each system configuration candidate based on the analysis results in step S404. The items for the multi-faceted evaluation are the total distribution loss, voltage deviation, and reserve supply capacity. In addition to the multi-faceted evaluation items, the system switching workload is also calculated as an evaluation item. Note that the evaluation items are not limited to the example items, and may include evaluation items other than the example items.

[0101] The total distribution loss is the sum of the power losses for each section in a specified time period, and can be calculated using the following formula:

[0102]

number

[0103] The voltage deviation is calculated by the following formula, with the average value of the voltage fluctuation from the feeder point for each section being the evaluation value. In designing the distribution system, it is desirable to have a system configuration in which the voltage fluctuation within the system is small, i.e., the voltage deviation is small.

[0104]

number

[0105] When an accident occurs in a power distribution system, power must be supplied from an adjacent section to the affected section in order to restore power to the affected section. The reserve capacity is an evaluation value that indicates the available capacity of the distribution line within a section, and is calculated using the following formula. The reserve capacity indicates the capacity to transfer power to an adjacent section, so a larger value is desirable.

[0106]

number

[0107] The system switching workload is an evaluation value indicating the switch switching workload required to change from the current system configuration to the candidate system configuration, and is calculated using the following formula.

[0108]

number

[0109] In formula 16, when the open / closed state of a switch changes, the amount of system switching work is expressed by adding up the switching work time of that switch. The switching work time for each switch varies depending on the type of switch. For example, in the case of a remote control switch, the work time is only a few minutes because it can be remotely controlled by an automated power distribution system. On the other hand, in the case of a manual switch, a worker must be dispatched to the site to perform the switching work, so the work time is significantly longer than that of a remote control switch.

[0110] Finally, in step S407, the system configuration candidate multi-facet evaluation unit 24 determines a standard system configuration for the designated time range based on the multi-facet evaluation value for each system configuration candidate calculated in step S406. In order to determine the standard system configuration for the designated time range, the evaluation values ​​for the evaluation items for each system configuration candidate, namely, power distribution loss, voltage deviation, reserve supply capacity, and system switching workload, are normalized to a value between 0 and 1, with the minimum and maximum values ​​being 0 and 1, respectively, and the norm shown in the following formula is calculated as a comprehensive evaluation index.

[0111]

number

[0112] It is desirable for the values ​​of items other than reserve supply capacity to be small, and it is desirable for the reserve supply capacity to have a large value. Therefore, since the system configuration candidate with the smallest overall evaluation index E can be said to be the appropriate system configuration, the system configuration with the smallest overall evaluation index E is finally determined as the standard system for the designated time range. The overall evaluation index E can be calculated by including one or more of the evaluation items, and if there is a prioritized evaluation item, it can be weighted to calculate the overall evaluation index.

[0113] An example of a screen displaying a comparative evaluation of system configuration candidates, including a comprehensive evaluation index, is shown in Fig. 17. A comparative evaluation screen example 1700 is made up of a comprehensive evaluation index display section 1701 that displays a comprehensive evaluation index for each system configuration candidate, a comprehensive evaluation index radar chart section 1702 that displays the values ​​of each evaluation item of the comprehensive evaluation index, and a system configuration display section 1703.

[0114] The overall evaluation index display unit 1701 displays the system configuration candidates in ascending order of the objective function value in step S403, and displays the overall evaluation index E for each system configuration candidate. The overall evaluation index display unit 1701 also allows the selection of evaluation items to be included in the overall evaluation index E and the weighting of the evaluation items. The overall evaluation index radar chart unit 1702 displays the values ​​of each evaluation item of the overall evaluation index E of the system configuration candidate selected in the overall evaluation index display unit 1701 in a radar chart. In automatic processing, the system configuration candidate with the smallest overall evaluation index E is selected, but the system configuration candidates may be compared with each other in the overall evaluation index radar chart, and the user may comprehensively judge the numerical values ​​of the evaluation items to determine the standard system configuration for the specified time range. The system configuration display unit 1703 displays the system configuration including the switch state of the selected system configuration candidate.

[0115] In this embodiment, the power distribution system configuration construction system 1 is a computer that does not directly control the system but supports the operation planner in constructing the power distribution system configuration. However, the present invention is not limited to this, and the power distribution system configuration construction system 1 may collect and accumulate only the equipment status data 32 from the system and directly control the switches of the system based on the constructed power distribution system configuration.

[0116] In recent years, distributed power sources have been concentrated at terminal locations such as branch lines of power distribution systems, and the amount of power flow at branch lines has increased. In conventional section models of power distribution systems, the branch lines are simplified during modeling, which can lead to the problem of overlooking violations of operational constraints at the branch lines.

[0117] However, according to the power distribution system configuration construction method of the present embodiment, a granularity-variable section model is generated in which information on the power distribution equipment in a section where there is a possibility of violating operational constraints is aggregated at a second granularity that is more detailed than the first granularity, based on the power flow state in the branch line of the power distribution system model. Then, a power flow analysis is performed in a specified time range based on the granularity-variable section model, and a power distribution system configuration is constructed based on the results of the power flow analysis.

[0118] In this way, by partially refining the granularity of the section model according to the current state of the branch line of the distribution system, it is possible to generate a granularity-variable section model capable of monitoring in detail the locations where there is a high possibility of violating the operational constraints. In addition, using the granularity-variable section model, a candidate distribution system configuration can be generated by solving an optimization problem, and based on the results of a multi-faceted evaluation and comparative evaluation of the candidate distribution system configuration with respect to multiple evaluation items, it is possible to construct an optimal standard system configuration for a specified time range without overlooking violations of the operational constraints in the branch line. In addition, by switching the distribution system configuration, it is possible to avoid violations of the operational constraints without expanding the facilities, and it is expected to have the effect of suppressing facility costs.

[0119] (Computer 1000 Hardware) 18 is a hardware diagram showing a configuration example of the computer 1000. For example, a part or the whole of the power distribution system configuration construction system 1 is realized by the computer 1000.

[0120] The computer 1000 comprises a processor 1001 including a CPU, a main memory device 1002, an auxiliary memory device 1003, a network interface 1004, an input device 40, and an output device 50, all of which are interconnected via an internal communication line 1009 such as a bus.

[0121] The processor 1001 controls the overall operation of the computer 1000. The main memory device 1002 is composed of, for example, a volatile semiconductor memory, and is used as a work memory for the processor 1001. The auxiliary memory device 1003 is composed of a large-capacity nonvolatile memory device such as a hard disk device, a solid state drive (SSD), or a flash memory, and is used to store various programs and data for long periods of time.

[0122] An executable program 1100 stored in the auxiliary memory device 1003 is loaded into the main memory device 1002 when the computer 1000 is started up or when needed, and the aforementioned device that performs various processes is realized by the processor 1001 executing the executable program 1100 loaded into the main memory device 1002.

[0123] The executable program 1100 may be recorded on a non-transitory recording medium, read from the non-transitory recording medium by a media reading device, and loaded into the primary storage device 1002. Alternatively, the executable program 1100 may be obtained from an external computer via a network, and loaded into the primary storage device 1002.

[0124] The network interface 1004 is an interface device for connecting the computer 1000 to each network in the system or for communicating with other computers. The network interface 1004 is, for example, configured with a NIC (Network Interface Card) for a wired LAN (Local Area Network) or a wireless LAN.

[0125] The input device 40 is composed of a keyboard, a pointing device such as a mouse, and the like, and is used by the user to input various instructions and information to the computer 1000. The output device 50 is composed of a display device such as a liquid crystal display or an organic EL (Electro Luminescence) display, and an audio output device such as a speaker, and is used to present necessary information to the user when necessary.

[0126] As described above, according to this embodiment, by refining the granularity of the section model according to the power flow state of the branch line of the power distribution system, it is possible to generate a granularity-variable section model that can monitor in detail the locations where there is a high possibility of violating the operational constraints. In addition, using the granularity-variable section model, it is possible to generate system configuration candidates by optimization calculation, perform multi-sectional evaluation and comparative evaluation of the system configuration candidates for multiple items, and construct a standard system configuration for a specified time range.

[0127] The present invention is not limited to the above-described embodiment, but includes various modified examples. For example, the above-described embodiment has been described in detail to easily explain the present invention, and the present invention is not necessarily limited to the embodiment having all of the described configurations. [Explanation of symbols]

[0128] 1: power distribution system configuration construction system, 1000: computer, 1001: processor (processing device), 1002: main storage device

Claims

1. A method for constructing a distribution system configuration based on a section model that aggregates information on distribution facilities in sections obtained by dividing a distribution system model having distribution facilities as nodes at any node, the method comprising the steps of: A power distribution system configuration construction system having a main memory device and a processing device, generating a variable granularity section model in which information on the power distribution equipment in a section in which an operational constraint violation may occur is aggregated at a second granularity that is finer than the first granularity based on a power flow state in a branch line of the power distribution system model; Executing a power flow analysis in a specified time range based on the granularity variable section model; The power distribution system configuration is constructed based on the results of the power flow analysis. A method for constructing a power distribution system configuration comprising:

2. The method for constructing a power distribution system configuration according to claim 1, The power distribution system configuration construction system includes: When generating the variable granularity interval model, Calculating a line passing current and a voltage fluctuation in a branch line of the power distribution system model; determining the second granularity based on a sensitivity analysis of the number of nodes of the granularity variable section model when the allowable threshold value of the voltage fluctuation is changed; generating the granularity variable section model at the second granularity according to the line passing current; A method for constructing a power distribution system configuration comprising:

3. The method for constructing a power distribution system configuration according to claim 1, The power distribution system configuration construction system comprises: The intervals aggregated at the first granularity of the granularity variable interval model are displayed on a display device in a granularity variable manner at the second granularity. A method for constructing a power distribution system configuration comprising:

4. The method for constructing a power distribution system configuration according to claim 3, The power distribution system configuration construction system includes: In response to a user instruction, the intervals displayed on the display device in a granularity-variable manner at the second granularity are re-aggregated at the second granularity to regenerate the granularity-variable interval model. A method for constructing a power distribution system configuration comprising:

5. The method for constructing a power distribution system configuration according to claim 2, The power distribution system configuration construction system comprises: Generate a detailed model of the power distribution system based on the power distribution equipment data, generating provisional section models by provisionally dividing the sections for each of the division nodes that are boundaries dividing the power distribution system into sections and all of the branch connection nodes in the detailed model based on the detailed model; A power flow analysis is performed on the provisional section model in a specified time range; The granularity variable section model is generated based on the results of a power flow analysis performed on the provisional section model. A method for constructing a power distribution system configuration, comprising the steps of:

6. The method for constructing a power distribution system configuration according to claim 1, The power distribution system configuration construction system comprises: Formulating an optimization problem for determining an optimal configuration of the power distribution system configuration using the variable granularity section model; extracting a top predetermined number of candidates for the power distribution system configuration having a top score of an objective function of the optimization problem by calculating the optimization problem; performing a power flow analysis for the candidate power distribution system configuration in a specified time range; Based on the power flow analysis result of the candidate power distribution system configuration, a multi-sectional evaluation is performed in a specified time range for a plurality of evaluation items; Calculating a comprehensive evaluation index based on the plurality of evaluation items; The power distribution system configuration in the specified time range is determined based on the comprehensive evaluation index. A method for constructing a power distribution system configuration comprising:

7. The method for constructing a power distribution system configuration according to claim 6, The power distribution system configuration construction system comprises: A load cross section that maximizes the line current passing through the branch line and the voltage fluctuation is input to the optimization problem to extract candidates for the power distribution system configuration. A method for constructing a power distribution system configuration comprising:

8. The method for constructing a power distribution system configuration according to claim 6, The plurality of evaluation items include at least one of a total distribution loss, a voltage deviation, a supply reserve, and a system switching workload; The comprehensive evaluation index is a normalized norm of the plurality of evaluation items. A method for constructing a power distribution system configuration comprising:

9. The method for constructing a power distribution system configuration according to claim 8, The power distribution system configuration construction system comprises: At least one of the plurality of evaluation items and the comprehensive evaluation index is displayed on a display device. A method for constructing a power distribution system configuration comprising:

10. A power distribution system configuration construction system that constructs a power distribution system configuration based on a section model that aggregates information on the power distribution facilities in sections obtained by dividing a power distribution system model having power distribution facilities as nodes at any node, A power distribution system configuration construction system having a main memory device and a processing device, a granularity variable section model generation unit that generates a granularity variable section model in which information of the power distribution equipment in a section in which an operational constraint violation may occur is aggregated at a second granularity that is finer than the first granularity, based on a power flow state in a branch line of the power distribution system model; a standard system construction unit that executes a power flow analysis in a specified time range based on the granularity-variable section model and constructs the power distribution system configuration based on the execution result of the power flow analysis; A power distribution system configuration construction system comprising:

11. The power distribution system configuration construction system according to claim 10, The granularity variable section model generation unit When generating the variable granularity interval model, Calculating a line passing current and a voltage fluctuation in a branch line of the power distribution system model; determining the second granularity based on a sensitivity analysis of the number of nodes of the granularity variable section model when the allowable threshold value of the voltage fluctuation is changed; generating the granularity variable section model at the second granularity according to the line passing current; A power distribution system configuration construction system comprising:

12. The power distribution system configuration construction system according to claim 11, The granularity variable section model generation unit a detailed model generation unit that generates a detailed model of the power distribution system based on the power distribution facility data; a provisional section model generation unit that generates provisional section models by provisionally dividing the section for each dividing node that is a boundary for dividing the power distribution system into sections and each branch connection node in the detailed model based on the detailed model; a power flow state calculation unit that executes a power flow analysis in a specified time region for the tentative section model; a section model granularity adjustment unit that adjusts the second granularity based on a result of execution of a power flow analysis on the provisional section model to generate the granularity variable section model; A power distribution system configuration construction system comprising:

13. The power distribution system configuration construction system according to claim 10, The standard system construction unit includes: an optimal configuration problem calculation unit that uses the granularity-variable section model to formulate an optimization problem for obtaining an optimal configuration of the power distribution system configuration, and extracts a predetermined number of candidates for the power distribution system configuration that have a top score of an objective function of the optimization problem by calculating the optimization problem; a power flow analysis unit that executes a power flow analysis in a specified time range for the candidate power distribution system configuration; a system configuration candidate multi-faceted evaluation unit that performs a multi-faceted evaluation of a plurality of evaluation items in a specified time range based on a power flow analysis result of the candidate power distribution system configuration, calculates a comprehensive evaluation index based on the plurality of evaluation items, and determines the power distribution system configuration in the specified time range based on the comprehensive evaluation index; A power distribution system configuration construction system comprising:

14. The power distribution system configuration construction system according to claim 13, The optimal configuration problem calculation unit includes: A load cross section that maximizes the line current passing through the branch line and the voltage fluctuation is input to the optimization problem to extract candidates for the power distribution system configuration. A power distribution system configuration construction system comprising:

15. A power distribution system configuration construction program for causing a computer to function as a power distribution system configuration construction system that constructs a power distribution system configuration based on a section model that aggregates information on the power distribution equipment in a section obtained by dividing a power distribution system model having power distribution equipment as nodes at any node, The computer, a granularity variable section model generation unit that generates a granularity variable section model in which information of the power distribution equipment in a section in which there is a possibility of violating an operational constraint is aggregated at a second granularity that is more detailed than the first granularity, based on a power flow state in a branch line of the power distribution system model; A standard system construction unit that executes a power flow analysis in a specified time range based on the granularity-variable section model and constructs the power distribution system configuration based on the execution result of the power flow analysis. A distribution system configuration construction program to function as a

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