Facility planning system, facility planning method, and program

Abstract

To create an efficient facility plan which reduces costs in facility investment and maintenance management of a facility in total.SOLUTION: A facility planning system for creating a facility plan for a facility group, comprises: a calculation unit that executes calculation processing; and a storage unit that can be accessed by the calculation unit. The facility planning system comprises: a risk evaluation unit in which transition of a risk of the facility group is evaluated by the calculation unit; a congestion situation evaluation unit in which transition of a congestion level of the facility group is evaluated by the calculation unit; and a planning unit in which the facility plan for the facility group is created from the transition of the risk of the facility group and the transition of the congestion level of the facility group by the calculation unit. The planning unit creates a facility plan that reduces a total cost so that a risk of each facility and a congestion level of each facility do not exceed allowable values, respectively, a total amount of construction in a predetermined period does not exceed an upper limit of construction capacity, and a total risk in the predetermined period does not exceed a total risk allowable value.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an equipment planning system, an equipment planning method, and an equipment planning program for planning the implementation details and implementation timing of construction work such as updating and repairing a group of facilities. [Background technology]

[0002] Devices are used as facilities in a variety of fields. Equipment groups made up of such devices require work such as updating and repairing the equipment groups. Patent Document 1 is a background technology in this technical field. Patent Document 1 discloses a power distribution equipment maintenance support device in which an overhaul plan determination unit uses prerequisites stored in a condition storage unit and an amount of supply disruption power calculated by a supply disruption power amount calculation unit to create an overhaul plan that minimizes the average annual cost while keeping the expected value of the amount of supply disruption power below a certain level over the lifecycle, and a determined plan display unit displays the overhaul plan, LCRG, etc. created by the overhaul plan determination unit. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2010-027044 Summary of the Invention [Problem to be solved by the invention]

[0004] Traditionally, maintenance methods have been limited to overhauling the same type of equipment. Medium- to long-term maintenance requires consideration of multiple factors, including not only the risk of failure but also fluctuations in demand and the level of equipment congestion due to the increase in renewable energy. Failure to take these factors into account when planning appropriate equipment measures, such as repair, replacement, expansion, and streamlining, leads to inefficient equipment planning, making it difficult to reduce total costs, including capital expenditures (CAPEX) and operational expenditures (OPEX). For example, when replacing equipment with a high risk of failure, if utilization is expected to remain low, replacing the equipment with a smaller one can reduce equipment costs. However, if demand is expected to grow, replacing the equipment with the same size will require expansion soon, potentially resulting in wasted investment.

[0005] The present invention has been made in consideration of the above-mentioned problems, and aims to provide an equipment planning system, an equipment planning method, and an equipment planning program that take into account multiple factors such as the risks of equipment groups and changes in usage status to create efficient equipment plans that reduce the total costs of equipment investment and maintenance. [Means for solving the problem]

[0006] A representative example of the means for solving the problem of the present invention is as follows: That is, an equipment planning system for creating an equipment plan for a group of facilities, comprising a calculation unit that executes calculation processing and a storage unit that can be accessed by the calculation unit, wherein the calculation unit: Based on the failure probability of the equipment group a risk assessment unit that assesses a transition in risk of the facility group; a congestion assessment unit that assesses a transition in congestion of the facility group; and a risk assessment unit that assesses a transition in risk of the facility group and a transition in congestion of the facility group. The objective function representing the total cost is reduced based on a planning unit that creates an equipment plan for the group of facilities, and the planning unit is configured to By setting a construction pattern that does not exceed the upper limit of the construction capacity, and changing the setting of the construction pattern, the total amount of work, which is the sum of the amount of work required to implement the construction pattern in a predetermined period of time, does not exceed the upper limit of the construction capacity, the total risk, which is the sum of the risks of the equipment group in the predetermined period of time, does not exceed the total risk tolerance, and the objective function representing the total cost is The feature of this method is to develop equipment plans that reduce this. [Effects of the Invention]

[0007] According to one embodiment of the present invention, it is possible to formulate an efficient facility plan that reduces the total cost of facility investment and maintenance. Problems, configurations, and effects other than those described above will become apparent from the following description of the preferred embodiment of the present invention. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram showing an example of the overall configuration of a facility planning system including its surrounding environment. [Figure 2] FIG. 2 is a diagram showing an example of the data configuration of facility / load data. [Figure 3(a)] FIG. 3 is a diagram showing an example of the data configuration of power distribution line section data. [Figure 3(b)] FIG. 2 is a diagram showing an example of a data configuration of power distribution line system data. [Figure 3(c)] FIG. 2 is a diagram showing an example of the data configuration of smart meter data. [Figure 4] FIG. 2 is a diagram showing an example of a data configuration of consumer data. [Figure 5] FIG. 3 is a diagram showing an example of a data configuration of area data. [Figure 6] FIG. 3 is a diagram showing an example of a data configuration of energy resource data. [Figure 7] FIG. 4 is a diagram showing an example of the data configuration of area demand data. [Figure 8] FIG. 4 is a diagram showing an example of the data configuration of area power generation amount data. [Figure 9] FIG. 10 is a diagram showing an example of a data configuration of resource introduction ratio data. [Figure 10] FIG. 3 is a diagram showing an example of the data configuration of meteorological data. [Figure 11] FIG. 3 is a diagram showing an example of the data configuration of risk data. [Figure 12] FIG. 4 is a diagram showing an example of the data configuration of congestion status data. [Figure 13] FIG. 2 is a diagram showing an example of a data configuration of facility plan data. [Figure 14] FIG. 10 is a diagram showing an example of a data configuration of countermeasure master data. [Figure 15] FIG. 2 is a diagram showing an example of a data configuration of cost master data. [Figure 16] FIG. 4 is a diagram showing an example of the data configuration of cost data. [Figure 17] 1 is a flowchart showing an example of the overall processing of a facility planning system. [Figure 18] 10 is a flowchart showing an example of processing by a risk assessment unit. [Figure 19] 10 is a flowchart showing an example of processing by a demand transition evaluation unit. [Figure 20] 10 is a flowchart showing an example of processing by a resource introduction amount / power generation amount transition evaluation unit. [Figure 21(a)] 10 is a flowchart showing an example of processing by a congestion status evaluation unit. [Figure 21(b)] FIG. 10 is a conceptual diagram of the processing of the congestion status evaluation unit. [Figure 22] 10 is a flowchart showing an example of processing by a planning unit. [Figure 23] 1 is a conceptual diagram of the process of the planning section. [Figure 24] FIG. 10 is a diagram showing an example of a user interface screen image. DETAILED DESCRIPTION OF THE INVENTION

[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described below with reference to the accompanying drawings.

[0010] In this embodiment, as an example of an equipment planning system that plans the implementation details and implementation timing of construction work such as updating and repairing a group of facilities, i.e., an equipment planning system that plans an equipment plan for a group of facilities, an example will be described in which the system is applied to a group of facilities such as electric power distribution facilities (electric poles, electric wires, pole-mounted transformers, switchgear, etc.). Such a group of facilities may be electric power transmission and distribution facilities that wheel electric power.

[0011] FIG. 1 is a block diagram showing an example of the overall configuration including the surrounding environment of a facility planning system 100 according to this embodiment. The overall configuration including the surrounding environment of the facility planning system 100 may be, for example, such that the facility planning system 100 and a user terminal 127 used by a planner at an electricity transmission and distribution company that maintains and manages power distribution facilities are connected via a network 126. The network 126 is a LAN (Local Area Network) or a WAN (Wide Area Network). The network 126 may be a wireless network or a wired network. The components of this system will be described below.

[0012] The facility planning system 100 may be realized using a general-purpose PC (Personal Computer) or server. The facility planning system 100 may include a processor 101 as a computing unit for overall control, a communication unit 104 for connecting to other devices, an input unit 103 such as a keyboard or mouse for user input, a display unit 102 for displaying processing results and logs, a storage unit accessible by the computing unit, a memory 105 as a nonvolatile storage device, and a database 111 for managing necessary data. Although not shown, the system may include a memory configured with volatile storage elements such as RAM, and each component may be connected to a data bus. The memory 105, the database 111, and the RAM may be included in the aforementioned storage unit. The memory 105 stores programs for a risk assessment unit 106, a demand trend assessment unit 107, a resource introduction amount / power generation amount trend assessment unit 108, a congestion status assessment unit 109, and a planning unit 110, and these processes may be executed by the processor 101. The database 111 may store equipment and load data 112, consumer data 113, area data 114, energy resource data 115, cost master data 116, area demand data 117, area power generation amount data 118, resource introduction ratio data 119, weather data 120, risk data 121, congestion status data 122, equipment plan data 123, cost data 124, and countermeasure master data 125. In Fig. 1, the names of these data stored in the database 111 are written without the word "data."

[0013] Furthermore, for example, the user terminal 127 used by a planner at an electricity transmission and distribution company who maintains and manages electricity distribution facilities may be a general-purpose PC (Personal Computer), tablet terminal, smartphone, etc. Although not shown here, it may be composed of a processor, a memory which is a nonvolatile storage device, a communication unit for connecting to other devices, an input unit such as a keyboard, mouse, or touch panel for user input, a display unit for displaying the results of processing, etc., each of which may be connected to a data bus.

[0014] In this embodiment, for example, a planner can access the equipment planning system 100 using a user terminal 127 and use various data held by the equipment planning system 100 to plan the details and timing of construction work such as updating and repairing a group of distribution equipment.

[0015] Next, an example of the configuration of various data in the facility planning system 100 in FIG. 1 will be described with reference to FIGS.

[0016] 2 and 3 are diagrams showing an example of the configuration of the facility / load data 112. In FIG. 2, (a) shows an example of the configuration of utility pole data, (b) shows an example of the configuration of transformer data, and (c) shows an example of the configuration of switchgear data. FIG. 3(a) shows an example of the configuration of distribution line section data, FIG. 3(b) shows an example of the configuration of distribution line system data, and FIG. 3(c) shows an example of the configuration of smart meter data. Transformers, switches, distribution lines, etc. are installed on utility poles, which are distribution facilities, and distribution lines may be managed in units of sections between one utility pole and another utility pole, or a collection of multiple sections may be managed in units called a system.

[0017] In FIG. 2, (a) is an example of the configuration of utility pole data, and information about utility poles, which are power distribution facilities, may be stored. The utility pole data may include, for example, a utility pole ID 201, which is a name identifying the utility pole; an installation location 202, which indicates the location where the utility pole is installed; a section ID 203, which indicates the section to which the utility pole belongs; and a system ID, which indicates the system to which the utility pole belongs. Furthermore, the data may include an age 205, which indicates the number of years that have passed since the utility pole was manufactured; a repair year 206, which indicates the year in the Gregorian calendar that the utility pole was most recently repaired; a model number 207, which is the model number of the utility pole; etc. However, the data is not limited to these, and data may be added or deleted as necessary. The IDs of the section and system to which each utility pole belongs may be stored, allowing association with the section data and system data. The content of the installation location 202 may be "(latitude, longitude)."

[0018] In Fig. 2, (b) shows an example of the configuration of transformer data, in which information about a transformer, which is a power distribution facility, is stored. The transformer data may include, for example, an equipment ID 208, which is a name that identifies the transformer, and a utility pole ID 209 that identifies the utility pole on which the transformer is installed. Furthermore, the data may include an age 210 that is the number of years that have passed since the transformer was manufactured, a model number 211 that is the model number of the transformer, a capacity 212 that is the capacity of the transformer, and the like. However, the data is not limited to these, and data may be added or removed as necessary.

[0019] 2, (c) is an example of the configuration of switch data, and information about switches, which are power distribution equipment, may be stored. The switch data may include, for example, a device ID 213 that is a name identifying the switch, a utility pole ID 214 that identifies the utility pole on which the switch is installed, age 215 that is the number of years that have passed since the switch was manufactured, and model number 216 that is the model number of the switch. However, the data is not limited to these, and data may be added or deleted as necessary.

[0020] FIG. 3(a) shows an example of the configuration of distribution line section data. In the distribution line section data, distribution lines may be managed in units of sections between a certain utility pole and another utility pole, and information about the sections may be stored. The distribution line section data may include, for example, a section ID 301 indicating the section to which the distribution line belongs, a utility pole ID 302 indicating the utility pole that is the starting point of the distribution line section, a utility pole ID 303 indicating the utility pole that is the end point of the distribution line section, and an age 304 indicating the number of years that have passed since the construction of the distribution line section. The distribution line section data may also include a current allowable value 305 indicating the current allowable value of the distribution line in the distribution line section, a section length 306 indicating the length of the distribution line in the distribution line section, and a model number 307 indicating the model number of the distribution line in the distribution line section. The distribution line section data may also include a timestamp (actual) 308 recording the timing up to the present for the distribution line section, and a load (actual) 309 chronologically arranging the load of the distribution line in the distribution line section. Furthermore, the data may include a timestamp (forecast) 310 that records future timing for the distribution line section, a load (forecast) 311 that arranges future predicted loads of the distribution line in the distribution line section in time series, and the like. However, the data is not limited to these, and data may be added or deleted as necessary. The timestamp (actual) 308 may arrange actual timings in time series, and the load (actual) 309 may store the actual trends in the values ​​of currents that flowed through the distribution line section corresponding to the timings recorded in the timestamp (actual) 308. The timestamp (forecast) 310 may arrange future timings in time series, and the load (forecast) 311 may store the trends in predicted values ​​of currents that flow through the distribution line section corresponding to the timings recorded in the timestamp (forecast) 310.

[0021] Figure 3(b) shows an example of the configuration of distribution line system data. A collection of sections is managed as a unit called a system, and the distribution line system data may store information about this system. For example, it may include a system ID 312, a section 313 which is a collection of sections belonging to that system, etc., but is not limited to this, and data may be added or deleted as necessary.

[0022] FIG. 3(c) shows an example of the configuration of smart meter data, which may store data related to a smart meter installed to measure the power usage of each consumer. For example, the smart meter data may include an ID 314, which is a name identifying the smart meter, and an equipment ID 315, which is a name identifying the transformer from which the smart meter receives power. Furthermore, the smart meter data may include a timestamp 316, which chronologically records the timing of the smart meter, and an amount of power 317, which records the amount of power used via the smart meter corresponding to the timing recorded in the timestamp. However, the smart meter data is not limited to these, and data may be added or deleted as needed. In other words, the smart meter data may store data related to the amount of power usage obtained from the smart meter over time. In the present invention, unless otherwise specified, the term "consumer" refers to a consumer of power.

[0023] 4 shows an example of the configuration of consumer data 113, which may store information related to an electricity contract with a consumer. For example, the data may include a consumer ID 401, which is a name identifying the consumer, an address 402 indicating the address of the consumer, a contracted power 403 indicating the power contracted by the consumer, and a meter ID 404, which is a name identifying a smart meter corresponding to the consumer. However, the data is not limited to these, and data may be added or deleted as necessary.

[0024] FIG. 5 shows an example of the configuration of area data 114. In the distribution of electricity, for example, power supply areas are managed by administrative district and associated with the grid supplying the area. The area data 114 may include, for example, an area ID 501, which is a name identifying the area, an address 502 indicating the location of the area, a section 503, a grid ID 504 indicating the grid supplying electricity to the area, a consumer count 505 indicating the number of consumers included in the area, and a power outage impact cost 506. However, the data is not limited to these, and data may be added or deleted as necessary. The section 503 is data indicating the range of an area on a map, and the area may be represented by a set of points p indicated by latitude and longitude. Therefore, an area may be defined by the section 503. The power outage impact cost 506 may indicate the impact cost per kWh if a power outage occurs in that area, and may be obtained, for example, by dividing the annual GDP of the supply area by the actual annual power consumption in the supply area to convert the impact of the power outage into a monetary value.

[0025] FIG. 6 shows an example of the configuration of the energy resource data 115. The energy resource data 115 may store information about photovoltaic (PV) renewable energy sources installed by a consumer and storage batteries that store the generated power. For example, the data may include a consumer ID 601, which is a name identifying the consumer, and a PV output 602, which indicates the output of the PV installed by the consumer. The data may also include a storage battery capacity 603, which indicates the capacity of the storage battery installed by the consumer, a timestamp 604, which chronologically records the timing for the consumer, and a power generation record 605, which indicates the actual power generated by the PV. However, the data is not limited to this, and data may be added or deleted as necessary. The power generation record 605 may store the actual amount of power generated corresponding to the timing recorded in the timestamp 604.

[0026] FIG. 7 shows an example of the configuration of the area demand data 117. The area demand data 117 may store actual and forecast trends in the total demand for electricity in each area. For example, the area demand data 117 may include an area ID 701, which is a name identifying the area; a timestamp (actual) 702 recording the timing up to the present for the area; and an actual demand value 703, which is a chronological arrangement of actual values ​​of electricity demand in the area. The area demand data 117 may further include a timestamp (forecast) 704 recording the future timing for the area in chronological order; and a demand forecast value 705 recording the future forecasted electricity demand for the area in chronological order. However, the data is not limited to these, and data may be added or deleted as necessary. The actual demand value 703 may store actual values ​​of electricity demand corresponding to the timing recorded in the timestamp (actual) 702. The demand forecast value 705 may store future forecast values ​​of electricity demand corresponding to the timing recorded in the timestamp (forecast) 704.

[0027] 8 shows an example of the configuration of the area power generation amount data 118. The area power generation amount data 118 may include, for example, an area ID 801, which is a name identifying the area; a timestamp (actual) 802, which is a chronological arrangement of timings up to the present for the area; a demand actual value 803, which is a chronological arrangement of actual values ​​of power generation amounts in the area; a timestamp (forecast) 804, which is a chronological arrangement of future timings for the area; and a demand forecast value 805, which is a chronological arrangement of future forecasted power generation amounts for the area. However, the data is not limited to these, and data may be added or deleted as necessary. The demand actual value 803 may store a demand actual value corresponding to the timing recorded in the timestamp (actual) 802. The demand forecast value 805 may store a demand forecast value corresponding to the timing recorded in the timestamp (forecast) 804.

[0028] FIG. 9 shows an example of the configuration of the resource introduction rate data 119. The resource introduction rate data 119 may indicate the expected future trend in the penetration status of renewable energy (PV) for each area, expressed as a percentage. For example, the data may include an area ID 901, which is a name identifying a certain area; a timestamp 902, which chronologically records future timing for that area; and an introduction rate 903, which indicates the expected future rate at which renewable energy will be introduced for that area. However, the data is not limited to these, and data may be added or deleted as needed. The resource introduction rate data 119 may store an expected PV introduction rate for each year for each area, indicating the rate at which consumers in each area will introduce PV. The introduction rate 903 may store a future forecast value for PV introduction corresponding to the timing recorded in the timestamp 902. The resource introduction rate data 119 may incorporate publicly available national statistical information, such as renewable energy introduction forecasts and penetration targets.

[0029] FIG. 10 shows an example of the configuration of weather data 120. Weather data 120 may store actual and forecast weather values ​​for each area. For example, area ID 1001, which is a name identifying the area, and weather-related items 1002 for the area, such as average temperature, average precipitation, average solar radiation, and weather, may be stored. For the area, timestamps, which are a chronological arrangement of current and future times, and actual values ​​1003 and forecast values ​​1004, which are a chronological arrangement of the aforementioned weather-related items, corresponding to each timestamp, may be stored. Weather-related items 1002 are not limited to these, and data may be added or removed as needed. Weather data published by the Japan Meteorological Agency and the like may be incorporated and utilized in weather data 120.

[0030] FIG. 11 shows an example of the configuration of risk data 121. The risk data 121 may store a device ID 1101, which is a name that identifies the device, and a risk value 1102, which is the risk value of the device for each year. In the table shown in FIG. 11, reference numeral 1102 may represent the risk value, but the first row of this table represents the calendar year. By listing the risk values ​​of devices for each year in this way, it may be possible to manage the transition of risk values ​​for devices over time. This device ID 1101 may include all of the utility poles, transformers, switchgears, and distribution line sections of the power distribution facility. The data items stored in the risk data 121 are not limited to these, and data may be added or removed as necessary.

[0031] FIG. 12 shows an example of the configuration of the congestion status data 122. The congestion status data 122 stores the yearly change in congestion level, which indicates the load on equipment through which current flows, such as transformers and power distribution line sections. The congestion status data 122 may store a yearly congestion level 1202 for each equipment ID 1201. However, the data items are not limited to these, and data may be added or deleted as necessary. In the table shown in FIG. 12, reference numeral 1202 may represent the congestion level, but the first row of this table represents the calendar year. In this embodiment, for example, the degree of current flowing relative to the current capacity of equipment identified by the equipment ID is treated as the congestion level. A method for calculating this congestion level will be described later. In addition to current, the congestion level may also be determined by, for example, fluctuations in the allowable voltage range. Note that the yearly congestion levels shown in FIG. 12 are an example expressed in percentage (%).

[0032] 13 shows an example of the configuration of the equipment plan data 123. The equipment plan data 123 may store information about the equipment plan formulated by the equipment plan formulation system 100, i.e., the implementation details and planned year of construction work such as updating and repairing a group of power distribution equipment, and actual results. That is, the data may include, for example, an equipment ID 1301 that is a name identifying the equipment, a planned year 1302 that indicates the year in which the equipment is counted as equipment and installed, a countermeasure pattern ID 1303 that indicates the implementation details of the construction work to install the equipment, and an implementation year and month 1304 when the equipment was actually installed. However, the data is not limited to these, and data may be added or removed as necessary.

[0033] 14 shows an example of the configuration of the countermeasure master data 125. The countermeasure master data 125 may store information about the pattern of work to be performed on equipment, such as updating or repairing the equipment, for each piece of equipment. That is, for example, the data may include a countermeasure pattern ID 1401, which is a name that identifies the pattern of the countermeasure, a countermeasure name 1402, which is a name that identifies the content of the countermeasure, an equipment type 1403, which indicates the equipment for which the countermeasure is to be performed, a capacity increase / decrease 1404, a failure probability 1405, and CAPEX / OPEX 1406. However, the data is not limited to these, and data may be added or deleted as necessary.

[0034] In this embodiment, the following five patterns are used as construction patterns for facility planning. These may be "repair" (improving functionality), "replacement" (replacing equipment with the same equipment), "augmentation" (replacing equipment with a larger capacity), "slimming" (replacing equipment with a smaller capacity), and "external resource utilization" (reducing congestion by utilizing storage batteries installed by consumers in system operation). The number and content of these patterns may be changed as needed. In FIG. 14, the measure name 1402 has a number added after the name, such as "repair," but this number may be added to distinguish between measures with the same name.

[0035] The patterns may be further subdivided for each piece of equipment that is the target of the measures (utility poles, transformers, switches, and distribution line sections).

[0036] The capacity increase / decrease 1404 may indicate a capacity value that increases or decreases as a result of taking a countermeasure. The failure probability 1405 may indicate the amount of change in the failure probability as a result of taking a countermeasure. The failure probability 1405 illustrated in FIG. 14 is an example expressed in percentage (%). In the failure probability 1405 column, for example, "-10" may mean "a 10% decrease," and "→0" may mean "return to 0."

[0037] In the case of "repairs" that improve functionality, for example, the failure probability is reduced by 10% from the current state, and in the case of "replacement" that replaces equipment, the equipment is replaced with new equipment, so the failure probability can be reset to zero.

[0038] CAPEX / OPEX 1406 is data for identifying whether the costs of measures fall under capital investment costs (CAPEX) or maintenance and management costs (OPEX). For example, "repairs" are recorded as OPEX, while replacing equipment is considered capital investment and therefore CAPEX, and is recorded as a cost through depreciation of the investment costs. In CAPEX / OPEX 1406 shown in Figure 14, "C" indicates CAPEX and "O" indicates OPEX.

[0039] FIG. 15 shows an example of the configuration of the cost master data 116. The cost master data 116 may store information related to equipment costs, such as equipment costs, construction costs, and useful life for each equipment model number. For example, the cost master data 116 may include equipment type 1501, which indicates the type of equipment for which cost information is being referenced; model number 1502, which indicates the model number for that equipment type; equipment cost (CAPEX) 1503, which indicates the equipment cost corresponding to the model number for that equipment type; and construction cost (OPEX) 1504, which indicates the construction cost corresponding to the model number for that equipment type. Furthermore, the cost master data 116 may include useful life 1505, which indicates the useful life corresponding to the model number for that equipment type; capacity 1506, which indicates the electrical capacity of the equipment corresponding to the model number for that equipment type; etc. However, the cost master data 116 is not limited to these, and data may be added or deleted as necessary.

[0040] FIG. 16 shows an example of the configuration of the cost data 124. The cost data 124 may store information such as the total cost and total risk for each year, which constitute a summary of the capital investment plan prepared by the capital investment planning system 100. For example, the cost data 124 may include a year 1601 representing the calendar, a total risk upper limit 1602 indicating the upper limit of the capital investment risk for that year, and an upper limit of the amount of work that can be performed for that year. The cost data 124 may also include a congestion level upper limit 1604 indicating the upper limit of the congestion level for that year, a total cost 1605 indicating the total cost that can be performed for that year, a total risk 1606 indicating the total risk that can be performed for that year, and a total amount of work that can be performed for that year. However, the cost data 124 is not limited to this, and data may be added or deleted as necessary. The units of the total risk upper limit 1602, the amount of work that can be performed 1603, the total cost 1605, the total risk 1606, and the total amount of work that can be performed for that year may each be monetary. The congestion level upper limit 1604 may be expressed in percentage (%).

[0041] Specific processing of the equipment planning system 100 in this embodiment with the above-described configuration will be described with reference to the database 111 described above and Figures 17 to 24. In this embodiment, an example will be described in which a planner accesses the equipment planning system 100 using a user terminal 127 and plans the implementation details and implementation timing of construction work such as updating and repairing a group of power distribution facilities using various data held by the equipment planning system 100. The memory 105 stores programs for a risk assessment unit 106, a demand transition assessment unit 107, a resource introduction amount / power generation amount transition assessment unit 108, a congestion status assessment unit 109, and a plan formulation unit 110, and these processes are executed by the processor 101.

[0042] Fig. 17 is an example of a flowchart showing the overall processing of the equipment planning system 100. Specific processing of the equipment planning system 100 will be described mainly with reference to Fig. 17. The processing of the equipment planning system 100 may be broadly composed of five processing steps. That is, each step may correspond to processing by the demand transition evaluation unit 107, the risk evaluation unit 106, the resource introduction amount / power generation amount transition evaluation unit 108, the congestion status evaluation unit 109, and the plan formulation unit 110, respectively.

[0043] The demand transition evaluation unit 107 may predict the power demand in the area where the equipment group is installed. First, the demand transition evaluation unit 107 may predict the transition of power demand in the area to be predicted (S1701). Next, the risk evaluation unit 106 may evaluate the transition of the risk of the equipment group (S1702). Next, the resource introduction amount / power generation amount transition evaluation unit 108 may predict the introduction amount of energy resources in the area where the equipment group is installed, i.e., the transition of the introduction status and the power generation amount. Next, the congestion status evaluation unit 109 may evaluate the transition of the congestion status of the equipment based on the equipment capacity, power demand, and power generation amount, i.e., the transition of the congestion degree of the equipment group (S1704). Finally, the plan formulation unit 110 may formulate an equipment plan (S1705). Below, detailed processing of each processing unit will be described.

[0044] 19 is an example of a flowchart showing details of the process S1701 in the demand transition evaluation unit 107. First, an area to be evaluated for the demand transition may be set (S1901). Next, in S1901, an area to be evaluated may be set from the areas stored in the area data 114.

[0045] In S1902, the weather and demand records for the target area are read. An area ID may be stored in the weather data 120 and the area demand data 117. The area ID may be used to search for and obtain the weather data 120 and area demand data 117 that correspond to the target area.

[0046] In S1903, a demand transition in the area may be predicted. In the demand prediction, for example, a future transition of the demand in the area may be predicted by multiple regression analysis using the actual values ​​of the weather data 120 and the actual values ​​of the area demand data 117 as explanatory variables.

[0047] In S1904, the predicted value calculated in S1903 may be stored in the time stamp (prediction) 704 and the demand forecast value 705, which are predicted values ​​of the area demand data 117.

[0048] In S1905, the load of the distribution line section may be calculated from the area demand and stored. Data on the distribution line system and data on the distribution line section belonging to the target area may be acquired from the facility and load data 112. Using this data, the area demand may be calculated proportionally by system and section, converted into a load for each distribution line section, and stored in the timestamp (forecast) 310 and load (A) (forecast) 311 of the distribution line section data exemplified in FIG. 3(a).

[0049] The above-described steps S1901 to S1905 may be repeated until all areas are processed (S1906).

[0050] Next, the process S1702 in the risk assessment unit 106 will be described. Fig. 18 is an example of a flowchart showing the details of the process S1702 in the risk assessment unit 106. First, the equipment to be the target of risk assessment may be set, and data related to that equipment may be read from the equipment / load data 112 (S1801). The equipment and devices to be the target of risk assessment may be utility poles, transformers, switches, and distribution line sections. In S1801, data on the target equipment may be read from Figs. 2(a), (b), and (c) and Fig. 3(a) in the equipment / load data 112.

[0051] Next, the failure probability of the target equipment may be calculated (S1802). The model number in the loaded equipment / load data 112 may be referenced to search for the useful life in the cost master data 116 shown in Fig. 15, and the failure probability may be calculated by, for example, performing a Weibull analysis based on the age of the equipment / load data 112.

[0052] After calculating the failure probability, the failure impact may be calculated (S1803). The failure impact may be calculated, for example, as a monetary value representing the impact on society of a power outage that occurs when a certain facility fails. From the facility / load data 112, the system ID 312 of the distribution line to which the facility belongs may be traced back to the distribution line section ID 301, and the area ID 501 to which the facility belongs may be identified from the area data 114. The area data 114 may hold a power outage impact cost 506 for each area. The power outage impact cost 506 indicates the impact cost per kWh in the event of a power outage in the area, and may be obtained, for example, by dividing the annual GDP of the supply area by the annual power consumption in the supply area to convert the impact of the power outage into a monetary value. Note that the GDP here may be the total production in the area. The load (actual) 309 and load (forecast) 311 of the distribution line section to which the target facility belongs can be used to calculate the power outage power (kW) in the event of a power outage, that is, the power that would have been consumed if there had been no power outage, and the level of failure impact, which is a monetary value of the impact on society due to a power outage that occurs when the facility breaks down, can be calculated by multiplying the power outage power by the standard power outage duration (for example, 24 hours) in the event of a power outage and the unit cost of power outage impact.

[0053] Next, in S1804, the risk may be calculated based on the failure probability and the failure impact. The failure impact may be, for example, a value obtained by converting the impact on society of a power outage that occurs when a certain piece of equipment fails into a monetary value. By multiplying this failure impact by the failure probability calculated in S1802, the expected value of the monetary impact on society due to a power outage can be calculated, and this value may be used as the risk value for the target equipment.

[0054] S1802, S1803, and S1804 may calculate not only the current but also future transitions in risk values. Specifically, S1802, which calculates the failure probability, may increment the value over time from the current value to calculate the value of the failure probability for each year. S1803, which calculates the failure impact, may calculate the failure impact for each year by using the predicted value of the distribution line section, i.e., the load (predicted) 311. S1804 may calculate the risk for each year by multiplying the failure probability for each year by the failure impact.

[0055] The risk calculation results for the target equipment for each year may be stored in the risk data 121 shown in Fig. 11. The above-mentioned steps S1801 to S1805 are repeated until they are performed for all equipment (S1806). In this way, the risk assessment unit 106 assesses the transition of the risk of the equipment group.

[0056] Next, the process S1703 in the resource introduction amount / power generation amount transition evaluation unit 108 will be described. Fig. 20 is an example of a flowchart showing details of the process S1703 in the resource introduction amount / power generation amount transition evaluation unit 108. First, an area to be evaluated is set (S2001). In S2001, the area to be evaluated may be set from the areas stored in the area data 114.

[0057] S2002 may read weather data 120, energy resource data 115, area power generation data 118, consumer data 113, and resource introduction ratio data 119 for the target area. Since the weather data 120, area power generation data 118, and resource introduction ratio data 119 contain area IDs, information corresponding to the area to be evaluated may be searched for and acquired from these data using the area ID. With regard to the energy resource data 115, it may be determined whether the address 402 contained in the consumer data 113 is included within the range of the target area in the area data 114, and data related to the energy resources owned by the consumer may be extracted by referring to the consumer IDs of the consumers included in the target area.

[0058] In S2003, the current resource introduction amount and power generation amount of the target area may be calculated. All power generation results 605 of the energy resource data belonging to the target area acquired in S2002 are added up, and a timestamp (actual result) related to the results is added up in the area power generation amount data 118. 802 and actual demand value 803.

[0059] S2004 may predict future resource deployment and power generation trends based on the resource deployment rate. First, the transition of power generation of deployed resources is predicted. For example, the power generation rate may be predicted by multiple regression analysis using the actual values ​​of weather data 120 and the actual values ​​of area power generation data 118 as explanatory variables. It is also possible that new PV systems will be installed among consumers in the future. The value obtained by subtracting the number of consumers who have already installed resources from the number of consumers in area data 114 may represent the future resource deployment potential. The resource deployment rate data 119 stores the estimated PV deployment rate for each year for the area corresponding to the area ID, indicating the rate at which consumers in each area will install PV. Based on this rate, the total power generation amount for each year of newly installed PV systems may be calculated, assuming that consumers who have not yet installed PV systems will install standard-scale PV systems. The estimated power generation amount for the target area can be calculated by adding up the estimated power generation amounts for the newly installed and existing installed systems.

[0060] In S2005, the calculated predicted value can be stored in the time stamp (prediction) 804 and the demand prediction value 805 related to the prediction of the area power generation amount data 118.

[0061] The above-mentioned steps S2001 to S2005 may be repeated until all areas are processed (S2006).

[0062] Next, the processing S1704 in the congestion status evaluation unit 109 will be described. Fig. 21(a) is an example of a flowchart showing the processing in the congestion status evaluation unit 109, i.e., details of S1704 in Fig. 17. Fig. 21(b) is a conceptual diagram illustrating the congestion status evaluation processing. The congestion status evaluation unit 109 may evaluate the yearly change in the congestion degree, which indicates the load on equipment through which current flows, such as transformers and distribution line sections.

[0063] In S2101, a facility to be evaluated for congestion status may be set, and data on the facility may be read from the facility / load data 112. Here, an example will be described in which the evaluation targets are a transformer and a distribution line section.

[0064] S2102 may associate the facility with the demand and the area power generation amount. If the facility to be evaluated is a distribution line section, the distribution line section data may store actual and predicted load values ​​corresponding to the demand. If the facility to be evaluated is a transformer, the transformers belonging to the distribution line section may be identified via the utility pole IDs corresponding to the distribution line section, and the load may be allocated proportionally by the number of transformers, thereby associating the load with the transformer facility. Regarding the area power generation amount, the area data 114, the distribution line system data, and the distribution line section data may be associated, the distribution line section belonging to the target area may be identified, and the area power generation amount data 118 may be allocated proportionally, thereby associating the target facility with the PV power generation amount. In this way, the congestion status evaluation unit 109 may calculate the trend in the current value flowing through the facility group from the trend in power demand and the trend in the introduction of resources such as PV power generation amount.

[0065] In S2103, the transition of the congestion status of the facility may be evaluated based on the capacity of the facility, the load corresponding to the demand, and the amount of power generated. Since a certain amount of PV power is consumed by the consumer himself, and the amount not consumed flows back to the grid, the amount of power flowing back to the distribution line section may be, for example, a value obtained by multiplying the amount of power generated corresponding to the distribution line section by a predetermined coefficient. In other words, the load on the facility is the sum of the demand amount and the amount of PV back flow (a value obtained by multiplying the amount of power generated corresponding to the distribution line section by a predetermined coefficient). As an example of the transition of the congestion status of the facility, Figure 21(b) shows an example of the transition of the load on this facility as an expected current I(t) against cumulative time. In this figure, the cumulative time is t all In other words, it is a diagram called a duration curve that shows the distribution of current flow for one year of operation time 2004 (8760 hours). In this diagram, I(t) is the current expected current 2002, I upper limitThat is, the allowable current value 2001 of the equipment, Imax, i.e., maximum current value 2005, which is the maximum value of the assumed current, and tover, i.e., current overload time 2003, which is the time during which the assumed current exceeds the allowable current value, are shown. At this time, the congestion degree of the equipment is calculated by the formula (1). The congestion degree is calculated by the maximum current congestion degree I , capacity congestion c and time congestion t If the maximum current congestion degree is the first congestion degree, the capacity congestion degree is the first congestion degree, and the time congestion degree is the third congestion degree, the congestion degree of the equipment may be calculated by the product of the first congestion degree, the first congestion degree, and the third congestion degree.

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[0070] Maximum current congestion I The capacity congestion degree may indicate the margin for the allowable current value, that is, the ratio of the maximum current to the allowable current. c The time congestion degree may indicate the degree of margin for capacity on the time axis of current, that is, the ratio of the sum of current values ​​over a certain period to the sum of allowable current values ​​over a certain period. tThe congestion level may indicate the degree to which the current exceeds the allowable value over time, i.e., the percentage of time during which the current value exceeds the allowable current value over a certain period of time. These congestion levels may be calculated on an annual basis. The certain period here can be set as needed, but may also be a predetermined period, as described below.

[0071] In S2104, the congestion degree for each year of the target facility calculated in S2103 may be stored in the congestion status data 122. The congestion status data 122 shown in Fig. 12 may store the calculation results of the congestion degree for each year for each device.

[0072] The above-described processes S2101 to S2104 may be repeated until all the target facilities have been processed (S2105). In this way, the congestion status evaluation unit 109 may evaluate the transition of the congestion degree of the facility group.

[0073] Next, a description will be given of the process S1705 in the planning unit 110. Fig. 22 is an example of a flowchart showing details of the process S1705 in the planning unit 110, and Fig. 23 is an example of a conceptual diagram of the process in the planning unit.

[0074] The planning unit 110 may plan the implementation details and timing of construction work such as renewal and repair for a group of power distribution facilities. Furthermore, the planning unit 110 may plan a construction plan for a group of facilities, i.e., an equipment plan, based on the transition of the risk of the group of facilities and the transition of the degree of congestion of the group of facilities. This will be explained below.

[0075] In the planning of the facility plan, the execution flag x of the countermeasure pattern m for the facility i in the year y is i,y,m ={1,0} (a flag of 1 or 0) as the objective variable, formulas (5) to (8) may be used to create a plan to minimize the total cost of capital investment and maintenance. Formulas (9) to (11) may be constraints.

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[0083] Equation (5) represents the total sum of the capital investment cost for each specified period, the operating cost of the equipment for each specified period, and the sum of the variance of the construction volume for each specified period. m can be called the construction cost of countermeasure pattern m. In other words, in formula (5), ucost, which is the first term when the sum symbol Σ is removed, m , that is, equation (6) is the OPEX cost uocost of countermeasure pattern m m , i.e., the capital investment cost and the CAPEX cost of countermeasure pattern m m, that is, the sum of the operating costs of the equipment divided by the useful life ylife. OPEX costs, CAPEX costs, and useful life may be stored in the cost master data 116. CAPEX costs are usually recorded as capital investment costs, so the initial investment amount divided by the useful life is recorded as depreciation expenses each year. Therefore, the construction costs per year can be calculated using formula (6). In formula (7), uconst m is the amount of work required for measure pattern m, and the OPEX cost of measure pattern m is m and CAPEX cost of countermeasure pattern m m It can be calculated by multiplying the sum of these factors by coefficient A. Coefficient A is a coefficient that links costs and labor volume, and can be used, for example, to adjust labor costs between the construction client and contractor. In formula (5), the second term when the sum symbol Σ is removed can represent the sum of the variations in labor volume for each specified period. Formula (5) can mean calculating an equipment plan that minimizes the total cost of measures for a group of equipment over a specific period, such as 20 years, and the sum of the standard deviation of annual labor volume. Note that in formula (5), "Minimize" applies to the entire formula (5) that follows Minimize. Therefore, it can be understood that the entire part after Minimize is enclosed in parentheses "()".

[0084] Formula (8) expresses the upper limit of the total annual production volume. const This may be a constraint that the total amount of work falls within the upper limit (manufacturing volume upper limit value 1603 in the cost data 124), i.e., that the plan is made so as not to exceed this upper limit. For example, since the construction capacity of a construction company is often set annually, this can be used as a constraint when making a plan so as not to exceed that capacity. In other words, the processing of formulating an equipment plan may be performed so that the total amount of work does not exceed the upper limit of manufactur- ing volume for a predetermined period, for example, each year, and so as not to exceed the construction capacity.

[0085] Risk in Equation (9) i,ymay be the risk value of the facility i in year y, and may correspond to the risk value stored in the risk data 121. i,y may change by implementing a measure pattern m. The measure pattern may correspond to the pattern indicated in the measure pattern ID 1401 stored in the measure master data 125, and the failure probability 1405 may correspond to the change in risk that changes by implementing a measure pattern m. Formula (9) expresses that the sum of the risks of the equipment each year, i.e., the total risk, is the upper limit value of the total risk limit risk This may be a constraint that the plan is made so as to fall within the total risk upper limit value 1602 in the cost data 124. In other words, the process of formulating an equipment plan may be performed so that the total risk in a predetermined period, for example, year y, does not exceed the total risk upper limit value, i.e., the total risk tolerance value.

[0086] Congestion in Equation (10) i,y may indicate the congestion status of facility i in year y, and corresponds to the congestion degree 1202 stored in the congestion status data 122. i,y may change depending on the implementation of the countermeasure pattern m. As shown in the capacity increase / decrease 1404 stored in the countermeasure master data 125, the capacity of the equipment may change depending on the countermeasure pattern, so the congestion status may also change. Formula (10) expresses the congestion level of each piece of equipment as the congestion level upper limit limit congestiom This may be a constraint that the plan is made to fit within the congestion level upper limit 1604 in the cost data 124.

[0087] Equation (11) may be a constraint on the selection of measure m for facility i, and may be a constraint that prevents construction work as multiple measures from being carried out on the same facility in the same year.

[0088] To solve this optimization problem, a plan may be drawn up according to the processing flow example shown in FIG.

[0089] First, in S2201, the initial setting of the countermeasure pattern may be performed based on the transition of risk and the transition of congestion for each piece of equipment. In other words, the initial setting of the countermeasure pattern may be performed based on the transition of risk for a group of equipment and the transition of congestion for the group of equipment.

[0090] In S2201, for example, when the risk of a facility exceeds a predetermined tolerance value in the time-series risk transition and the facility age is 80% or more of its useful life, "replacement" may be selected from the countermeasure master data 125, and when the facility age is less than 80% of its useful life, "repair" may be selected from the countermeasure master data 125. Furthermore, if the facility is a transformer or a distribution line section, when the congestion level exceeds an upper limit in the time-series transition of the congestion level, an "augmentation" pattern, which involves replacing the facility with an appropriate device with a larger capacity, may be selected from the countermeasure master data 125 based on the future increase in the congestion level. In this case, if an expansion is necessary and a consumer near the installation location of the facility has installed a storage battery, "external resource utilization" may be selected to utilize the storage battery in system operation to reduce the congestion level by referencing the energy resource data 115 and the consumer data 113. Alternatively, in the case where the congestion level is expected to decrease by a certain amount in the future, an appropriate "slimming" pattern can be selected from the countermeasure master data 125.

[0091] Here, once a countermeasure pattern is selected, a risk assessment and a congestion assessment may be performed on the target facility, and the risk value and congestion degree may be updated. Here, the congestion assessment may be performed when the target facility is a transformer or a distribution line in a distribution line section, and when "reinforcement" or "streamlining" is selected.

[0092] The risk assessment may be performed by performing the processing flow of the risk assessment unit 106 in FIG. 18 only on the target equipment. The congestion assessment may be performed by performing the processing flow of the congestion assessment unit 109 in FIG. 21(a) only on the target equipment. The congestion assessment may calculate the congestion level based on the increase or decrease in the capacity value shown in the capacity increase / decrease 1404 of the "enhancement" or "slimming" pattern selected from the countermeasure master data 125. The calculated time series transition of the risk and the time series transition of the congestion level may be stored in the risk data 121 and the congestion status data 122.

[0093] An image of the processing of S2201 is shown in FIG. 23 as a conceptual diagram of the processing of the planning unit 110. The configuration of FIG. 23 will be explained. Of the five diagrams shown in FIG. 23, the top three diagrams relate to S2201. The bottom two relate to S2202 and S2206, respectively. The bottom two will be explained later. Here, the top three diagrams relating to S2201 will be explained first. These three diagrams will be called the top graph, middle graph, and bottom graph, respectively.

[0094] The graph in the top row shows the change in congestion level over time for facility B. The thick solid curve in this graph is a prediction of the change in congestion level for facility B in the initial plan. The thin dashed line extending horizontally represents the acceptable congestion threshold for facility B. The thick dashed line extending from the middle of the thick solid curve is a prediction of the change in congestion level after construction work is carried out for facility B.

[0095] The graph in the middle shows the change in risk over time for facility B. The thick solid line, thin dashed line, and thick dashed line in this graph each represent the risk substituted for the congestion levels mentioned above.

[0096] The graph in the lower part shows the planned construction work and the timing of the work for facilities A, B, and C. The construction work corresponds to the explanation of the symbols shown in the bottom part of Figure 23.

[0097] In these three graphs, the top and middle graphs show how the congestion and risk of facility B will change when construction work is carried out on facility B, as shown in the bottom graph. That is, when facility B exceeds the preset risk tolerance threshold, as shown in the middle graph, replacement, as shown by the black circle in the bottom graph, is selected. Furthermore, when facility B exceeds the congestion tolerance threshold, as shown in the top graph, reinforcement, as shown by the black triangle in the bottom graph, is selected. The risk value and congestion level are also recalculated at each construction timing. As a result, as shown in the middle graph, when facility B is replaced, the risk curve shifts from the thick solid line to the thick dashed line, and the risk value is predicted to decrease to 0 (zero) and then gradually increase. Further, as time passes and equipment B is upgraded, the congestion curve changes from a thick solid line to a thick thin line, as shown in the top graph, and the congestion value decreases and then gradually increases, and at the same time, as shown in the middle graph, the thick dashed risk curve is predicted to decrease to 0 (zero) again and then gradually increase. Note that in both the congestion and risk graphs, the thick solid lines after replacement and upgrade represent the changes in congestion and risk if replacement and upgrade were not carried out.

[0098] Similar processing may be used to select the timing of construction work as a countermeasure for facility A and facility C.

[0099] As described above, the planning unit 110 may be able to perform processing for planning an equipment plan without the risk of each piece of equipment and the degree of congestion of each piece of equipment exceeding the allowable value.

[0100] Next, in S2202, after processing S2201, a search is performed for cases in which multiple construction projects are selected for the same equipment in adjacent years, and the plans for these multiple construction projects are integrated. This may be the case, for example, for equipment B in Figure 23. In this example, as shown in the lower graph in Figure 23, as a result of processing S2201, equipment B will undergo "augmentation" two years after "replacement." In this case, two years after "replacement," equipment will be replaced with a new one through "augmentation," which is inefficient. Therefore, in S2202, for example, the "augmentation" may be advanced by two years, and "augmentation" may be performed instead of "replacement." This concept of advancing the implementation is shown in the graph corresponding to S2202 in Figure 23. That is, for equipment B, the construction project indicated by the white triangle, which was originally planned as an expansion project, is advanced as shown by the thick arrow, and is integrated with the construction project originally scheduled for replacement, and the expansion project is carried out. This allows multiple construction projects to be integrated and costs reduced without exceeding the allowable thresholds for risk and congestion. In this way, after processing S2201, cases where multiple construction projects have been selected as countermeasures for the same equipment in adjacent years may be searched for, and these multiple plans may be integrated. The number of years defined as adjacent years can be set appropriately by the user of this equipment planning system. The adjacent years do not necessarily have to be years, but may be shorter than one year. In S2202, risk values ​​and congestion levels may also be recalculated at the timing of the integrated construction projects. Risk assessment may be performed using the processing flow of the risk assessment unit 106 in FIG. 18 for only the target equipment. Congestion assessment may be performed using the processing flow of the congestion assessment unit 109 in FIG. 21(a) for only the target equipment. In congestion assessment, congestion levels may be calculated based on the increase or decrease in capacity indicated in the capacity increase / decrease 1404 corresponding to the "enhancement" or "downsizing" pattern selected from the countermeasure master data 125. The calculated time series transition of the risk and the time series transition of the congestion degree may be stored in the risk data 121 and the congestion status data 122.

[0101] In S2203, the value of the objective function may be calculated after the processing of S2202. The objective function may be the sum of the total costs of construction work as a countermeasure for a group of facilities in a specific period, as shown in formula (5), and the sum of the annual variations in the amount of work, for example, the standard deviation. In other words, the objective function may be one that minimizes the total value of the capital investment costs for each specified period, the operating costs for each specified period, and the sum of the variations in the amount of construction work for each specified period, for example, the sum of the standard deviation. The countermeasure pattern in the countermeasure master data 125 may indicate CAPEX / OPEX 1406. Therefore, it may be possible to determine whether the cost should be recorded as OPEX or CAPEX depending on the countermeasure. Based on this flag CAPEX / OPEX 1406 and the model number of each piece of equipment stored in the equipment / load data, the equipment to be constructed can be identified by referencing the cost master data 116, the cost can be calculated using the equipment cost (CAPEX) 1503 and the construction cost (OPEX) 1504, and the objective function can be calculated by carrying out the integration process in equation (5). The value of equation (5) becomes the total cost.

[0102] As mentioned above, the objective function may be Equation (5). However, the objective function may be other than Equation (5). For example, the objective function may be obtained by replacing the standard deviation in Equation (5) with the variance. Variance may also be a way of expressing variability. When using this variance, the objective function no longer has monetary dimensions, making calculation of the total cost a challenge. However, when calculating the total cost, the value obtained by replacing the variance with the standard deviation can be used. Furthermore, in addition to Equation (5), the objective function may be any one of three elements: capital investment cost per specified period, equipment operating cost per specified period, and the sum of the variances in the construction volume per specified period. Furthermore, in addition to Equation (5), the objective function may be any two elements: capital investment cost per specified period, equipment operating cost per specified period, and the sum of the variances in the construction volume per specified period. Even when these are used as the objective function, although the results are smaller than when formula (5) is used, the effect of formulating an efficient facility plan may be achieved.

[0103] In S2204, an evaluation value is calculated for each target facility. The evaluation value may indicate the extent of the decrease in the objective function when the timing of the construction work currently selected for each facility is advanced or advanced over the next few years, i.e., when the construction work is advanced or advanced. When the countermeasure pattern is "replacement," "enhancement," "repair," or "external resource utilization," the risk value and congestion level are on an increasing trend, so it may be possible to advance the implementation to reduce the risk of an increasing trend. Furthermore, for "slimming down," it may be possible to postpone the implementation if the congestion level is on a decreasing trend, or it may be possible to advance the implementation if, for example, there is room for improvement in the congestion level.

[0104] When advancing or delaying construction work within a few years, i.e., within a time-related vicinity, it may be possible to attempt to integrate construction work selected as different measures within the same few years, as performed in S2202. Furthermore, when advancing or delaying construction work, if construction work is to be performed simultaneously on multiple pieces of equipment whose installation locations are within a certain distance, i.e., spatially close, it may be possible to perform construction work on multiple pieces of equipment simultaneously (this may be called synchronized construction work) rather than performing construction work on each piece of equipment individually. In such cases, construction costs can be reduced by, for example, 20%, and synchronized construction work can also reduce construction costs. The distance between the multiple pieces of equipment may be calculated from the installation locations 202 stored in the equipment / load data 112. In this way, it may be possible to explore whether integration of construction work or synchronized construction of nearby equipment is possible when the implementation timing of the construction work currently selected for each piece of equipment is advanced or advanced within a few years, and calculate an evaluation value based on the extent to which the objective function can be reduced. Here, even if costs can be reduced by integrating construction work or synchronous construction work on nearby facilities, if this violates the constraints of formulas (8) to (11), the construction timing may not be advanced or delayed. In this way, the planning unit 110 may be able to formulate an equipment plan by grouping together construction work for multiple facilities whose construction work is planned to be performed in close proximity in time and / or space.

[0105] The number of years that constitute the aforementioned "several adjacent years" can be set as appropriate by the user of this equipment planning system. Furthermore, the "several adjacent years" does not necessarily have to be years, but may be a period shorter than a year. For multiple pieces of equipment whose installation locations are within a certain distance, in other words, spatially close to each other, the certain distance can be set as appropriate by the user of this equipment planning system. These settings are the same as those in the description of this embodiment.

[0106] S2205 may search for the equipment with the highest evaluation value, that is, the equipment that will have the greatest effect in reducing the objective function when the timing of the construction work currently selected as a measure is shifted back and forth over the next few years, based on the evaluation value for each piece of equipment calculated in S2204.

[0107] In S2206, for the capital plan with the highest evaluation value found in S2205, the timing of construction work as the currently selected measure may be shifted forward or backward over the course of several years, and the construction work may be integrated and synchronized with construction work on facilities planned in nearby locations, i.e., the capital plan may be set. In other words, in S2206, capital plans may be created by shifting the construction work timing forward or backward in order of the facilities with the highest evaluation value, or by combining construction work on multiple facilities for which construction work is planned to be nearby in time and / or space.

[0108] An example of S2206 is shown in the graph corresponding to S2206 in Figure 23. That is, the originally planned "slimming" construction for facility C may be brought forward by one year, and when the construction is brought forward, it may be carried out in sync with facility B, which is physically located nearby. By doing this, construction costs can be reduced by, for example, 20%.

[0109] In S2207, the risk value and congestion level may be updated for the equipment whose plan was updated in S2206. In S2208, the objective function may be updated because the updated capital plan reduces the objective function compared to before the capital plan was updated. In S2209, the evaluation value may be updated for the installation location of the equipment whose plan was updated or for equipment whose construction is planned near the year the capital plan was updated. These steps S2205 to S2209 may be repeated to update the plan until the maximum evaluation value is equal to or less than zero, that is, until the objective function cannot be further reduced, and a final capital plan may be obtained (S2210). This processing may enable the development of an capital plan that reduces the total cost expressed by Equation (5). As a result of the capital plan development, the time series trends of the final equipment risk may be stored in risk data 121, and the time series trends of the congestion level may be stored in congestion status data 122. The details and timing of the planned construction work, such as renewal and repair of the power distribution equipment, may be stored in capital plan data 123. For the entire plan, the total cost, total risk, and total effort for each year may be stored in the total cost 1605, total risk 1606, and total effort 1607 of the cost data 124. These storage processes may be performed in S2210.

[0110] The planning unit 110 may create an equipment plan that reduces total costs so that the risk of individual equipment and the congestion level of individual equipment do not exceed their respective tolerance values, and so that the upper limit of construction capacity for a specified period and the total risk tolerance value for a specified period do not exceed their respective tolerance values.

[0111] As described above, the equipment planning system 100 of an embodiment of the present invention comprises a calculation unit that executes calculation processing and a memory unit accessible by the calculation unit, a risk assessment unit 106 that evaluates the transition in risk of the equipment group, a congestion status assessment unit 109 that evaluates the transition in congestion level of the equipment group, and a planning unit 110 that formulates an equipment plan for the equipment group based on the transition in risk of the equipment group and the transition in congestion level of the equipment group, and the planning unit 110 formulates an equipment plan that reduces total costs so that the risk of each piece of equipment and the congestion level of each piece of equipment do not exceed their tolerance values, so that the total amount of work in a specified period does not exceed the upper limit of construction capacity, and so that the total risk in a specified period does not exceed the total risk tolerance value, thereby making it possible to formulate an efficient equipment plan that reduces costs overall for equipment investment and maintenance.

[0112] The drawn up facility plan may be presented to the planner by the display unit 102 of the facility planning system 100. FIG. 24 is an example of a screen image of a user interface displaying the processing results of the planning unit. A user interface 2401 displaying the processing results of the planning unit displays information before planning 2402 and information after planning 2403, and the information before planning 2402 may display a total risk amount for each year 2404 and a congestion degree distribution for each year 2405. The information after planning 2403 may display a total risk amount for each year 2406 and a congestion degree distribution for each year 2407. The total risk amount for each year may be displayed using the total risk for each year stored in the cost data 124. The congestion degree distribution may be displayed as a frequency distribution of congestion degrees, with the overall being 100%, and may be displayed using the congestion status data 122. Before planning, the total risk gradually increased and exceeded the capacity, and the proportion of equipment with high congestion levels gradually increased, showing that equipment capacity was becoming strained. However, as a result of optimization, appropriate equipment measures were implemented to prevent the total risk from exceeding the capacity, and the number of equipment with extremely high and low congestion levels was reduced, showing that overall equipment utilization rates could be maintained at a moderately high level. Furthermore, as a result of the capital planning by the capital planning system, the total annual labor volume 2408 and total annual cost 2409 can be displayed. It can be seen that as a result of optimization, an efficient capital plan was created that reduces the total cost of capital investment and maintenance without causing the total labor volume to exceed the annual capacity.

[0113] As described above, the equipment planning system of this embodiment can take into account multiple factors such as the risks of the equipment group and changes in usage status, and can create efficient equipment plans that reduce the total costs of equipment investment and maintenance.

[0114] In this embodiment, an example of an equipment planning system that plans the implementation details and timing of construction work such as updating and repairing equipment groups has been explained using power distribution equipment (utility poles, electric wires, pole-mounted transformers, switches, etc.) as an example, but the application field is not limited to this, and it goes without saying that the system can be widely applied to a wide range of subjects for which the implementation details and timing of construction work such as updating and repairing equipment groups are planned, such as wide-area infrastructure equipment similar to power distribution equipment (water, gas, communications, roads, etc.).

[0115] Although the present invention has been described in detail above with reference to the accompanying drawings, the present invention is not limited to such specific configurations, but includes various modifications and equivalent configurations within the spirit and scope of the appended claims.

[0116] The present invention is not limited to the above-described embodiment, and the components can be modified and embodied in practice without departing from the spirit of the invention.

[0117] The present invention is not limited to the above-described embodiments, but includes various modifications and equivalent configurations within the spirit and scope of the appended claims. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to configurations including all of the described configurations. Furthermore, part of the configuration of one embodiment may be replaced with the configuration of another embodiment. Furthermore, the configuration of another embodiment may be added to the configuration of one embodiment. Furthermore, part of the configuration of each embodiment may be added, deleted, or replaced with other configurations.

[0118] Furthermore, the aforementioned configurations, functions, processing units, processing means, etc. may be realized in part or in whole in hardware, for example by designing them as integrated circuits, or may be realized in software by having a processor interpret and execute a program that realizes each function.

[0119] Information such as programs, tables, and files that realize each function can be stored in a storage device such as a memory, a hard disk, or an SSD (Solid State Drive), or in a recording medium such as an IC card, an SD card, or a DVD.

[0120] In addition, the control lines and information lines shown are those that are considered necessary for explanation, and do not necessarily represent all the control lines and information lines that are necessary for implementation. In reality, it can be assumed that almost all components are interconnected. [Explanation of symbols]

[0121] 100 Facility Planning System 101 processors 102 Display section 103 Input section 104 Communications Department 105 memory 106 Risk Assessment Department 107 Demand Trend Evaluation Department 108 Resource Introduction and Power Generation Trend Evaluation Section 109 Congestion Assessment Department 110 Planning Department 111 Database 112 Equipment and Load Data 113 Consumer Data 114 Area Data 115 Energy Resource Data 116 Cost Master Data 117 Area Demand Data 118 Area Power Generation Data 119 Resource Introduction Rate Data 120 Weather Data 121 Risk Data 122 Congestion data 123 Facility Planning Data 124 Cost Data 125 Countermeasure Master Data 126 Network 127 terminals

Claims

1. An equipment planning system that creates equipment plans for a group of facilities, a computing unit that executes computation processing and a storage unit that can be accessed by the computing unit; The memory unit stores an upper limit of construction capacity and a total risk tolerance value, The facility planning system includes: a risk assessment unit configured to assess a transition of risk of the equipment group based on a failure probability of the equipment group; a congestion status evaluation unit that evaluates a transition in the congestion level of the facility group based on a transition in the value of current flowing through the facility group; the calculation unit comprises a planning unit that formulates an equipment plan for the facility group that reduces an objective function that represents a total cost based on a transition in risk of the facility group and a transition in congestion level of the facility group; The planning unit sets a construction pattern in which the risk of each piece of equipment and the congestion level of each piece of equipment do not exceed their respective tolerances, and by changing the settings of the construction pattern, creates an equipment plan in which the total amount of work, which is the sum of the amount of work required to carry out the construction pattern over a specified period of time, does not exceed the upper limit of the construction capacity, the total risk, which is the sum of the risks of the group of equipment over the specified period of time, does not exceed the total risk tolerance, and an objective function representing the total cost is reduced.

2. The facility planning system according to claim 1, The storage unit further stores installation locations of the individual pieces of equipment, The equipment planning system is characterized in that the planning unit prepares an equipment plan by moving the construction implementation timing, which is the timing for implementing the construction pattern, forward or backward, or by consolidating construction work for multiple pieces of equipment for which construction work is planned near at least one of the construction implementation timing and the installation location.

3. 3. The facility planning system according to claim 2, the planning unit prepares an equipment plan by shifting the timing of construction work for equipment in descending order of the amount of reduction in the total value of at least one of the equipment investment costs for each specified period, the operating costs for each specified period, and the sum of the variations in the amount of construction work for each specified period, or by combining construction work for multiple pieces of equipment for which construction work is planned to be done near at least one of the timing of construction work and the installation location.

4. The facility planning system according to claim 1, The facility group is a power transmission and distribution facility that transmits electric power, the storage unit further stores weather, actual demand, energy resources, power generation amount, and resource introduction ratio; The facility planning system includes: a demand transition evaluation unit that predicts a transition of power demand in an area where the facility group is installed based on the weather and the demand record; a resource introduction amount / power generation amount transition evaluation unit that predicts the transition of the resource introduction amount and power generation amount in the area where the equipment group is installed based on the weather, the energy resources, the power generation amount, and the resource introduction rate; an equipment planning system characterized in that the congestion status evaluation unit calculates the trend in the current value flowing through the equipment group by correlating the trend in the power demand and the trend in the amount of resource introduction and power generation with the equipment group, and calculates the congestion level of the equipment as the product of a first congestion level which is the ratio of the maximum current to the allowable current, a second congestion level which is the ratio of the sum of the current values ​​over a certain period of time to the sum of the allowable current values ​​over a certain period of time, and a third congestion level which is the proportion of time during which the current value exceeds the allowable current value over a certain period of time.

5. 5. The facility planning system according to claim 4, The storage unit further stores installation locations of the individual pieces of equipment, The planning unit advances or rearranges the construction work execution timing, which is the timing for carrying out the construction pattern, in order of the equipment that has the largest reduction in the total value of at least one of the equipment investment cost for each specified period, the operating cost for each specified period, and the sum of the variation in the construction volume for each specified period, or prepares an equipment plan by aggregating construction work for multiple pieces of equipment for which construction work is planned near at least one of the construction work execution timing and the installation location.

6. 1. An equipment planning method executed by an equipment planning system to create an equipment plan for a group of facilities, comprising: The facility planning system includes a calculation unit that executes calculation processing and a storage unit that is accessible by the calculation unit, The memory unit stores an upper limit of construction capacity and a total risk tolerance value, The facility planning method includes: a risk assessment step in which the calculation unit assesses a transition of risk of the equipment group based on the failure probability of the equipment group; a congestion status evaluation step in which the calculation unit evaluates a transition in the congestion level of the equipment group based on a transition in the value of current flowing through the equipment group; a planning step in which the calculation unit formulates an equipment plan for the facility group that reduces an objective function representing a total cost based on a transition in risk of the facility group and a transition in congestion level of the facility group, the planning step includes a step in which the calculation unit sets a construction pattern in which the risk of each piece of equipment and the degree of congestion of each piece of equipment do not exceed tolerances, and by changing the settings of the construction pattern, creates an equipment plan in which the total amount of work, which is the sum of the amount of work required to carry out the construction pattern over a specified period of time, does not exceed the upper limit of the construction capacity, and the total risk, which is the sum of the risks of the group of equipment over the specified period of time, does not exceed the total risk tolerance, and in which an objective function representing the total cost is reduced.

7. An equipment planning program for a computer to create an equipment plan for a group of facilities, comprising: a risk assessment function for assessing a transition of risk of the equipment group based on the failure probability of the equipment group; a congestion status evaluation function that evaluates a transition in the congestion level of the equipment group based on a transition in the value of current flowing through the equipment group; a planning function of formulating an equipment plan for the facility group that reduces an objective function representing a total cost based on a transition in risk of the facility group and a transition in congestion level of the facility group, A program for realizing the planning function, which sets a construction pattern in which the risk of individual equipment and the congestion level of individual equipment do not exceed the tolerance values, and by changing the settings of the construction pattern, creates an equipment plan in which the total amount of work, which is the sum of the amount of work required to carry out the construction pattern over a specified period of time, does not exceed the upper limit of construction capacity stored in the memory device of the computer, the total risk, which is the sum of the risks of the group of equipment over the specified period of time, does not exceed the total risk tolerance value stored in the memory device of the computer, and the objective function representing the total cost is reduced.

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