Facility-combination type optimizing device, facility-combination type optimizing method and facility-combination type optimizing program

Abstract

To enable a short-time search for an optimal facility configuration, and a planning of operation of an optimal facility in the optimal facility configuration.SOLUTION: A facility-combination type optimizing device 10 includes: a convertible type facility condition generating unit 11 which takes an input-output resource amount as a decision variable with respect to each convertible type facility of a system accomplished by combining the convertible type facilities or accumulation type facilities, and which generates a constraint condition that is the relation of the decision variables; an accumulation type facility condition generating unit 12 which takes an input-output resource amount as a decision variable with respect to each accumulation type facility, and which generates a constraint condition where an accumulation resource amount obtained by adding the difference between the decision variables with the accumulation resource amount is higher than or equal to a given lower limit value and is lower than or equal to an upper limit value; a network condition generating unit 13 that generates the constraint condition of the network; an objective function generating unit 14 that generates an objective function relating to an important performance evaluation index for calculating the input-output resource amount; and an optimized plan making unit 15 that calculates the input-output resource amount per time.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] The present invention relates to a facility combination type optimization device, a facility combination type optimization method, and a facility combination type optimization program.

Background Art

[0002] It is desired to provide customers with energy equipment such as generators, storage batteries, electric vehicles, and chargers in an optimal configuration. In providing such a system, it is necessary to achieve good performance evaluation indicators (KPIs: Key Performance Indicators) that customers value.

[0003] Patent Document 1 describes an invention of a distributed energy system control device that can create an optimal operation plan even when there are changes in device characteristics due to temperature, water temperature, or device deterioration.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] It has been difficult to search for an optimal facility configuration that achieves any important performance evaluation indicator and to quickly formulate an optimal operation plan for the optimal facility. Therefore, an object of the present invention is to search for an optimal facility configuration in a short time and to formulate an optimal operation plan for the optimal facility in that configuration.

Means for Solving the Problems

[0006] To solve the above problems, the equipment combination type optimization device of the present invention is a system that combines a conversion type equipment that takes one or more types of resources as input and outputs one or more types of resources, or an accumulation type equipment that takes one or more types of resources as input, outputs the same type of resources, and accumulates the difference. For each of the above conversion type equipment, at least the input resource amount and output resource amount for each time are used as decision variables, and a conversion type equipment condition generation unit that generates the relationship between the input resource amount and the output resource amount as a constraint condition; for each of the above accumulation type equipment, at least the input resource amount and output resource amount for each time are used as decision variables, and the accumulation resource amount, which is the sum of the difference between the input resource amount and the output resource amount and the accumulated resource amount at the time, is greater than or equal to a given lower limit value and less than or equal to an upper limit value as a constraint condition. An accumulation type equipment condition generation unit that generates; a network condition generation unit that generates, as a constraint condition of the network, that the sum of the output resource amounts of the same type from the conversion type equipment or the accumulation type equipment, and the sum of the input resource amounts of the same type to other conversion type equipment or other accumulation type equipment are equal, or the input resource amount is larger; an objective function generation unit that generates an objective function related to an important performance evaluation index using one or more values among the input resource amount or the output resource amount; the decision variables and constraint conditions of 0 or more of the conversion type equipment generated by the conversion type equipment condition generation unit, and the decision variables and constraint conditions of 0 or more of the accumulation type equipment generated by the accumulation type equipment condition generation unit, one or more of the network constraint conditions generated by the network condition generation unit, and the objective function generated by the objective function generation unit are used to calculate the input resource amount and output resource amount for each time of the conversion type equipment and the accumulation type equipment. It is characterized by comprising an optimal planning department.

[0007] The equipment combination type optimization method of the present invention is for a system combined with a conversion type equipment that takes one or more types of resources as input and outputs one or more types of resources, or an accumulation type equipment that takes one or more types of resources as input, outputs the same type of resources, and accumulates the difference. For each of the conversion type equipment, a conversion type equipment condition generation unit generates, with at least the input resource amount and the output resource amount per time as decision variables, and the relationship between the input resource amount and the output resource amount as a constraint condition; for each of the accumulation type equipment, an accumulation type equipment condition generation unit generates, with at least the input resource amount and the output resource amount per time as decision variables, and the constraint condition that the accumulation resource amount, which is the sum of the difference between the input resource amount and the output resource amount and the accumulated resource amount at the time, is not less than a given lower limit value and not more than a given upper limit value; a network condition generation unit generates, as a network constraint condition, that the sum of the output resource amounts of the same type from the conversion type equipment or the accumulation type equipment, and the sum of the input resource amounts of the same type to other conversion type equipment or other accumulation type equipment are equal, or the input resource amount is larger; an objective function generation unit generates an objective function related to an important performance evaluation index using one or more values among the input resource amount or the output resource amount; and an optimal plan formulation unit calculates the input resource amount and the output resource amount per time of the conversion type equipment and the accumulation type equipment using the decision variables and constraint conditions of 0 or more of the conversion type equipment generated by the conversion type equipment condition generation unit, the decision variables and constraint conditions of 0 or more of the accumulation type equipment generated by the accumulation type equipment condition generation unit, 1 or more of the network constraint conditions generated by the network condition generation unit, and the objective function generated by the objective function generation unit.

[0008] The equipment combination type optimization program of the present invention is for a system that combines a conversion type equipment that inputs one or more types of resources to a computer and outputs one or more types of resources, or an accumulation type equipment that inputs one or more types of resources and outputs the same type of resources and accumulates the difference. Regarding each of the conversion type equipment, a procedure for generating at least the input resource amount and output resource amount for each time as decision variables and using the relationship between the input resource amount and the output resource amount as a constraint condition; regarding each of the accumulation type equipment, at least the input resource amount and output resource amount for each time are used as decision variables, and a procedure for generating a constraint condition that the accumulated resource amount, which is the sum of the difference between the input resource amount and the output resource amount and the accumulated resource amount at that time, is equal to or greater than a lower limit value and equal to or less than an upper limit value; the sum of the output resource amounts of the same type from the conversion type equipment or the accumulation type equipment, and a procedure for generating, as a network constraint condition, that the sum of the input resource amounts of the same type to other conversion type equipment or other accumulation type equipment is equal or the input resource amount is larger; a procedure for generating an objective function related to an important performance evaluation index using one or more values among the input resource amount or the output resource amount; using the generated decision variables and constraint conditions of 0 or more of the conversion type equipment, the generated decision variables and constraint conditions of 0 or more of the accumulation type equipment, the generated 1 or more network constraint conditions, and the generated objective function, to calculate the input resource amount and output resource amount for each time of the conversion type equipment and the accumulation type equipment. Other means will be described in the mode for carrying out the invention.

Effects of the Invention

[0009] According to the present invention, it is possible to search for an optimal equipment configuration in a short time, and further to formulate an optimal operation plan for the equipment in the optimal equipment configuration.

Brief Description of the Drawings

[0010]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Embodiments for Carrying Out the Invention

[0011] Hereinafter, embodiments for carrying out the present invention will be described in detail with reference to the respective drawings. FIG. 1 is a logical configuration diagram of the equipment combination type optimization device 10 according to the present embodiment. The equipment combination type optimization device 10 includes, as functional units, a conversion type equipment condition generation unit 11, an accumulation type equipment condition generation unit 12, a network condition generation unit 13, an objective function generation unit 14, an optimal plan formulation unit 15, an optimal equipment configuration selection support unit 16, an optimal equipment configuration selection unit 19, an equipment configuration generation unit 17, and a power rate conversion unit 18. The equipment combination type optimization device 10 further stores an equipment catalog group 21, a system template group 22, and an equipment combination type optimization program 23. This equipment combination type optimization device 10 virtually generates a system in which a plurality of conversion type equipment and accumulation type equipment are connected, and creates a plan for optimizing the important performance evaluation index of the generated system. Here, the conversion type equipment is equipment that converts energy, such as a solar power generation panel, a thermal power generator, a gas turbine generator, a gas cogeneration, a wind power generator, etc. Here, the accumulation type equipment selectively performs energy storage and release, such as a storage battery or a gas tank. The important performance evaluation index of the system is, for example, the cost of purchasing electricity, the procurement cost of gas, the CO2 emission amount, etc. Here, the resource is electric power [kWh], gas [m 3, costs such as power purchase cost and gas procurement cost [yen], CO2 emissions [m 3 etc., having quantities related to power, energy, and others. When inputting to equipment, it is an input resource, and when outputting from equipment, it is an output resource.

[0012] The equipment catalog group 21 stores the specifications of a plurality of conversion-type equipment and the specifications of a plurality of storage-type equipment.

[0013] The system template group 22 stores a plurality of system templates in which the interconnection relationship of equipment is defined. Here, a system template is a template for constructing a system by fitting either the conversion-type equipment or the storage-type equipment whose specifications are stored in the equipment catalog group 21.

[0014] The equipment configuration generation unit 17 virtually generates a system configured by network-connecting conversion-type equipment or storage-type equipment by referring to the system template group 22 and the equipment catalog group 21. The conversion-type equipment condition generation unit 11 generates decision variables and constraint conditions indicating the behavior of the conversion-type equipment. Here, a decision variable is a controllable variable. A constraint condition is a condition that gives the range of values that a decision variable can take.

[0015] The storage-type equipment condition generation unit 12 generates decision variables and constraint conditions indicating the behavior of the storage-type equipment. The network condition generation unit 13 generates network constraint conditions, and generates network conditions with the constraint that the sum of the inputs and outputs of the conversion-type equipment and the storage-type equipment is equal.

[0016] The objective function generation unit 14 generates an objective function related to the key performance evaluation index using one or more values among the input / output resource amounts of the conversion-type equipment and the storage-type equipment. The optimal plan formulation unit 15 formulates an optimal plan by calculating the configuration of one or more facilities and the input / output of the network from the decision variables and constraint conditions of the conversion-type facilities or the decision variables and constraint conditions of the accumulation-type facilities, and the constraint conditions and objective function of the network. The optimal plan formulation unit 15 calculates an optimized plan from the decision variables, constraint conditions, and objective function by mathematical optimization. Here, the optimized plan refers to the amount of input / output resources for each time period, as shown in FIG. 8, or the operating parameters of the facilities such as the load factor for each time period that results in the amount of input / output resources.

[0017] The optimal facility configuration selection support unit 16 displays, in a comparable form, a plurality of important performance evaluation indicators calculated by the optimal plan formulation unit 15 for each facility configuration of the plurality of systems generated by the facility configuration generation unit 17. This supports the selection of the optimal facility configuration. Note that the optimal facility configuration selection support unit 16 is not essential and may be omitted.

[0018] The optimal facility configuration selection unit 19 compares the important performance evaluation indicators calculated by the optimal plan formulation unit 15 for each facility configuration of the plurality of systems generated by the facility configuration generation unit 17, and selects the facility configuration for which the most excellent important performance evaluation indicator is calculated. In FIG. 1, the optimal facility configuration selection unit 19 is provided after the optimal facility configuration selection support unit 16, but the reverse configuration may also be used. The power rate conversion unit 18 calculates the relationship between power and the rate, where the power rate varies by time period. When any of the input resources and output resources of the conversion-type facilities, and the input resources and output resources of the accumulation-type facilities are power, the power rate conversion unit 18 calculates the relationship between power and the rate. By implementing the power rate conversion unit 18 as an add-in, it becomes possible to easily consider various rate plans showing the relationship between power and the rate.

[0019] FIG. 2 is a hardware configuration diagram of the facility combination type optimization device 10. The equipment combination type optimization device 10 optimizes a system configured by combining equipment. The equipment combination type optimization device 10 is a computer equipped with a CPU (Central Processing Unit) 101, a ROM (Read Only Memory) 102, and a RAM (Random Access Memory) 103. The equipment combination type optimization device 10 formulates an optimal plan in the equipment combination type and searches for an optimal equipment configuration in a short time. Here, the optimal equipment configuration refers to, for example, an equipment configuration capable of achieving the performance evaluation index specified by the customer. Note that the expression "optimization" may include not only an optimal equipment configuration but also an equipment configuration that optimizes and optimizes so that important performance evaluation indicators satisfy predetermined conditions.

[0020] The CPU 101 is a central processing unit that realizes each functional unit by executing a program and accessing data stored in the ROM 102 or the RAM 103. The ROM 102 is a non-volatile read-only memory in which various data and BIOS (Basic I / O System) and the like are stored. The RAM 103 is a volatile read-write memory in which various data and programs are temporarily stored.

[0021] The equipment combination type optimization device 10 further includes an input unit 104, a communication unit 105, a display unit 106, and a storage unit 107. The input unit 104 is, for example, a keyboard, a mouse, a touch panel, etc., and is a part for the user to operate the equipment combination type optimization device 10 to input data.

[0022] The communication unit 105 is, for example, a network interface card and is a part for communicating with other devices and an on-demand ordering platform via a network. The display unit 106 is, for example, a liquid crystal display, etc., and displays characters, graphics, images, etc.

[0023] The storage unit 107 is, for example, a hard disk drive or an SSD (Solid State Drive), and stores relatively large-capacity data and programs. The storage unit 107 stores the equipment catalog group 21, the system template group 22, and the equipment combination type optimization program 23. By executing the equipment combination type optimization program 23 by the CPU 101, various functional units shown in FIG. 1 are realized.

[0024] FIG. 3 is a diagram showing the operation of the equipment combination type optimization device 10. The equipment catalog group 21 provides the equipment configuration generation unit 17 with the specification information of a plurality of conversion type equipment and a plurality of storage type equipment. The system template group 22 provides the equipment configuration generation unit 17 with any one of the system templates in which the interconnection relationship of the equipment is defined. The system template is for fitting any conversion type equipment or any storage type equipment. By preparing the system template in advance by the designer and fitting the equipment thereto, a system with a suitable equipment configuration can be generated in a short time.

[0025] The equipment configuration generation unit 17 virtually generates the equipment configuration of a system in which the conversion type equipment or the storage type equipment of the equipment catalog group 21 is fitted into the system template and the conversion type equipment or the storage type equipment is network-connected. The equipment configuration generation unit 17 outputs the parameters of the conversion type equipment to the conversion type equipment condition generation unit 11, outputs the parameters of the storage type equipment to the storage type equipment condition generation unit 12, outputs the system configuration to the network condition generation unit 13, and outputs the types of decision variables to the objective function generation unit 14.

[0026] The conversion type equipment condition generation unit 11 generates decision variables and constraint conditions indicating the behavior of the conversion type equipment based on the parameters of the conversion type equipment, and outputs them to the optimal planning department 15. That is, for each conversion type equipment that takes one or more types of resources as input and outputs one or more types of resources, the conversion type equipment condition generation unit 11 uses at least the input resource amount and the output resource amount for each time as decision variables, and generates the relationship between the input resource amount and the output resource amount as a constraint condition.

[0027] The conversion-type equipment condition generation unit 11 receives an input of a piecewise-linear conversion map that converts the input resource amount of the conversion-type equipment into an output resource amount. Thereby, the output resources of the conversion-type equipment can be calculated more quickly. The conversion-type equipment takes one or more types of energy resources as inputs and outputs one or more types of resources. For example, a gas cogeneration (generator) that converts gas as an input resource into an output resource of electric power, a power conditioner that converts DC power as an input resource into an output resource of AC power, a solar power generation panel that converts sunlight as an input resource into an output resource of DC power, and the like.

[0028] The storage-type equipment condition generation unit 12 generates a decision variable and a constraint condition indicating the behavior of the storage-type equipment based on the parameters of the storage-type equipment, and outputs them to the optimal planning unit 15. That is, for each storage-type equipment that takes one or more types of resources as inputs, outputs the same type of resources, and accumulates the difference therebetween, the storage-type equipment condition generation unit 12 sets at least the input resource amount and the output resource amount for each time as decision variables, and generates, as a constraint condition, that the storage resource amount, which is the sum of the difference between the input resource amount and the output resource amount and the storage resource amount at each time, is equal to or greater than a given lower limit value and equal to or less than an upper limit value. Here, the storage-type equipment is, for example, a storage battery when electric power is used as the input and output resources, a high-pressure steam tank when steam is used as the input and output resources, and the like.

[0029] The network condition generation unit 13 generates network constraint conditions based on the system configuration and outputs them to the optimal planning unit 15. The network condition generation unit 13 has a unit conversion function between the input resource amount and the output resource amount of the conversion-type equipment. The objective function generation unit 14 generates an objective function for calculating the input / output resource amounts of the conversion-type equipment or the accumulation-type equipment from the decision variables. That is, the network condition generation unit 13 generates, for a network combining the conversion-type equipment or the accumulation-type equipment, as a constraint condition, that the sum of the output resource amounts of the same type from the conversion-type equipment or the accumulation-type equipment and the sum of the input resource amounts of the same type to other conversion-type equipment or other accumulation-type equipment are equal, or that the input resource amount is larger.

[0030] The optimal plan formulation unit 15 formulates an optimal plan for operating each piece of equipment from the decision variables and constraint conditions of the conversion-type equipment or the decision variables and constraint conditions of the accumulation-type equipment, the constraint conditions of the network, and the objective function, and calculates the configuration of one or more pieces of equipment and the input / output of the network. That is, the optimal plan formulation unit 15 uses the decision variables and constraint conditions of zero or more conversion-type equipment generated by the conversion-type equipment condition generation unit 11, the decision variables and constraint conditions of zero or more accumulation-type equipment generated by the accumulation-type equipment condition generation unit 12, the decision variables and constraint conditions of one or more networks generated by the network condition generation unit 13, and the objective function generated by the objective function generation unit 14, and by mathematical optimization, calculates the input resource amounts and output resource amounts of the conversion-type equipment and the accumulation-type equipment for each time period that maximize or minimize the objective function.

[0031] The equipment configuration evaluation unit 16 calculates the input / output of each piece of equipment in the equipment configuration generated by the equipment configuration generation unit 17 and the input / output of the network for each time period, and evaluates them using important performance evaluation indicators. If the important performance evaluation indicators satisfy a predetermined condition, the equipment configuration evaluation unit 16 proposes that equipment configuration to the user. If the important performance evaluation indicators do not satisfy the predetermined condition, the equipment configuration evaluation unit 16 causes the equipment configuration generation unit 17 to generate a system of another equipment configuration. As a result, an optimal equipment configuration system that satisfies the predetermined condition of the important performance evaluation indicators can be searched for in a short time.

[0032] FIG. 4 is a diagram showing an example of the system 3 combining equipment. System 3 includes, as a power supply network, a power selling facility 30, a solar power generation panel 32, a solar power generation panel power conditioner 33, a storage battery 36, and storage battery power conditioners 34 and 35, and supplies power to a power demand 31. In the drawings, the power conditioner is abbreviated as "PCS", and the solar power generation panel is abbreviated as "PV". In the power supply network of System 3, there are a power node 301, a power node 302, a power node 304, and a power node 305. The user defines or inputs in advance the power demand amount for each time period as the power demand 31.

[0033] Among these facilities, the power selling facility 30, the solar power generation panel 32, the solar power generation panel power conditioner 33, and the storage battery power conditioners 34 and 35 are conversion-type facilities that take one or more types of resources as inputs and output one or more types of resources. The storage battery 36 is an accumulation-type facility that takes one or more types of resources as inputs, outputs the same type of resources, and accumulates the difference.

[0034] The power node 301 bundles the purchased power from the power selling facility 30, the generated power output by the solar power generation panel power conditioner 33, and the discharged power output by the storage battery power conditioner 35, supplies power to the power demand 31, and outputs power to the storage battery power conditioner 34.

[0035] Purchased power is supplied to the power selling facility 30, and the purchased power is output to the power node 301, and at the same time, the power selling cost and the CO2 emission amount are output. When sunlight is input to the solar power generation panel 32, DC power is supplied to the solar power generation panel power conditioner 33 via the power node 302. The solar power generation panel power conditioner 33 converts the DC power into AC power and supplies this AC power to the power node 301.

[0036] The battery power conditioner 34 converts AC power into DC power and supplies it to the battery 36 via the power node 304. Then, the DC power output from the battery 36 is supplied to the battery power conditioner 35 via the power node 305. The battery power conditioner 35 converts the DC power into AC power and supplies it to the power node 301.

[0037] The system 3 further includes a gas purchasing facility 40, a gas cogeneration unit 41, and a gas boiler 42 as a gas supply network, and supplies steam to the steam demand 43 via a steam supply network. There is a gas node 401 in the gas supply network of the system 3. There is a steam node 402 in the steam supply network of the system 3. The gas purchasing facility 40, the gas cogeneration unit 41, and the gas boiler 42 are conversion-type facilities that take one or more types of resources as inputs and output one or more types of resources. The user predefines or inputs the above demand amounts for each time period as the steam demand 43.

[0038] The gas purchased by the gas purchasing facility 40 is input to the gas node 401 and supplies gas to the gas cogeneration unit 41 and the gas boiler 42. The gas cogeneration unit 41 takes the supplied gas and auxiliary power as inputs, supplies the generated power to the power node 301, supplies the steam heat to the steam node 402, supplies steam to the steam demand 43, and further discharges hot water heat and CO2.

[0039] The gas boiler 42 takes the supplied gas and auxiliary power as inputs, supplies steam heat to the steam node 402, and further discharges CO2. The steam heat supplied to the steam node 402 is finally supplied to the steam demand 43.

[0040] The system composed of these power supply network, gas supply network, and steam supply network is stored in a system template. By fitting conversion-type facilities or storage-type facilities to these system templates, the equipment configuration of the system can be generated.

[0041] Figure 5 is an example of a piecewise linear graph. The horizontal axis of the graph represents power. The vertical axis of the graph represents the cost of power. When the power is less than or equal to P0, the power cost is a linear function with respect to power. When the power exceeds P0, the power cost is also a linear function with respect to power, but the rate of change is greater than when the power is less than or equal to P0. And when the power is P0, the power cost is C1. When the power is 0, the power cost is C0.

[0042] Such a piecewise linear function requires less computational effort than a high-order polynomial and can preferably approximate a high-order polynomial.

[0043] Figure 6 is an example of a piecewise linear graph. The horizontal axis of the graph represents the amount of gas. The vertical axis of the graph represents power. When the amount of gas is greater than or equal to L0 and less than or equal to L1, the power is a linear function with respect to the amount of gas. When the amount of gas is greater than or equal to L1 and less than or equal to L2, the power is a linear function with respect to the amount of gas, but the rate of change is smaller than when the amount of gas is greater than or equal to L0 and less than or equal to L1. And when the amount of gas is greater than or equal to L2, the power is a linear function with respect to the amount of gas, but the rate of change is smaller than when the amount of gas is greater than or equal to L0 and less than or equal to L1 or when the amount of gas is greater than or equal to L1 and less than or equal to L2.

[0044] Figure 7 is a scatter diagram showing the relationship between cost and CO2 emissions. Among CAPEX + OPEX on the horizontal axis of the scatter diagram, CAPEX is Capital Expenditure, which refers to equipment investment and initial costs. OPEX is an abbreviation of Operating Expense or Operating Expenditure, which is a general term for the expenses continuously required for business operation. The sum of CAPEX and OPEX represents the overall cost. The vertical axis of the scatter diagram represents the CO2 emissions. This scatter plot in Figure 7 shows multiple key performance indicators KPI (here, the relationship between CAPEX+OPEX and CO2 emissions) in a comparable form. To reduce CO2 emissions, CAPEX+OPEX increases, but when CAPEX+OPEX is reduced, CO2 emissions increase. Therefore, it becomes possible to compare and select which value to adopt based on the key performance indicator KPI.

[0045] Figure 8 is a graph showing the results of the optimized operation plan. The horizontal axis of the graph indicates time. The vertical axis of the upper graph indicates power. The vertical axis of the lower graph indicates heat quantity.

[0046] The initial period when the purchased electricity price in the graph is as low as 10 [yen / kWh] is, for example, from 0:00 am to 8:00 am, and all power is supplied by purchased electricity. And the charging power to the battery PCS is supplied by the purchased electricity.

[0047] The period when the purchased electricity price is as high as 20 [yen / kWh] is, for example, from 8:00 am to 10:00 pm. Initially, the output of the PV-PCS (photovoltaic power conditioner) is insufficient, and the insufficient power is supplemented by the discharge of the battery PCS, gas cogeneration power generation, and purchased electricity. At this time, steam demand is generated, so it is supplied by the steam of the gas boiler.

[0048] As the output of the PV-PCS (photovoltaic power conditioner) increases over time, the amount of supplementary power for the insufficient power gradually decreases. At this time, there is a period when the battery PCS is charged with purchased electricity and gas cogeneration power generation. At this time, since the steam demand is gradually increasing, it is supplied by both the steam of the gas cogeneration and the steam of the gas boiler.

[0049] When the output of the PV-PCS (photovoltaic power conditioner) decreases over time, the shortage of power is compensated again by the discharge of the battery PCS, gas cogeneration, and purchased power. Here, as shown by the solid line in the upper graph, the battery PCS discharges until its charge level reaches zero. The steam demand at this time is met by the steam of the gas cogeneration.

[0050] The period when the purchased power price drops to 10 [yen / kWh] is, for example, from 10 p.m. to 12 a.m., and all the power is supplied by purchased power. And the charging power to the battery PCS is supplied by the purchased power. And since steam demand is occurring at this time, it is met by the steam of the gas boiler.

[0051] According to the present invention, for KPIs that customers value, it is possible to quickly propose an optimal configuration of energy devices such as generators, batteries, electric vehicles, and chargers. And it is possible to rapidly deploy a planning system for operation.

[0052] [1] For a system (3) that combines a conversion type facility (solar power generation panel 32, solar power generation panel power conditioner 33, gas cogeneration 41, battery power conditioners 34, 35, gas boiler 42) that takes one or more types of resources as inputs and outputs one or more types of resources, or an accumulation type facility (battery 36) that takes one or more types of resources as inputs, outputs the same type of resources, and accumulates the difference, for each of the above-mentioned conversion type facilities, with at least the input resource amount and output resource amount per time as decision variables, a conversion type facility condition generation unit (11) that generates the relationship between the input resource amount and the output resource amount as a constraint condition, For each of the above-mentioned accumulation type facilities, with at least the input resource amount and output resource amount per time as decision variables, a constraint condition is generated that the accumulation resource amount, which is the sum of the difference between the input resource amount and the output resource amount and the accumulated resource amount at that time, is equal to or greater than a given lower limit value and equal to or less than an upper limit value, and an accumulation type facility condition generation unit (12) is provided. A network condition generation unit (13) that generates, as a constraint condition of the network, that the sum of the output resource amounts of the same type from the conversion type equipment or the storage type equipment and the sum of the input resource amounts of the same type to other conversion type equipment or other storage type equipment are equal, or that the input resource amount is larger; An objective function generation unit (14) that generates an objective function related to key performance evaluation indicators using one or more values of the input resource amount or the output resource amount; Using the decision variables and constraint conditions of zero or more of the conversion type equipment generated by the conversion type equipment condition generation unit (11), the decision variables and constraint conditions of zero or more of the storage type equipment generated by the storage type equipment condition generation unit (12), one or more of the network constraint conditions generated by the network condition generation unit (13), and the objective function generated by the objective function generation unit (14), an optimal planning unit (15) that calculates the input resource amount and output resource amount of the conversion type equipment and the storage type equipment for each time; An equipment combination type optimization device, characterized by comprising the above.

[0053] [1] According to [1], an optimal equipment configuration in a system combining conversion type equipment and storage type equipment can be searched for in a short time.

[0054] [2] The conversion type equipment condition generation unit (11) receives an input of a piecewise linear conversion map that converts the input resource amount (DC power, AC power, gas, sunlight) of the conversion type equipment into an output resource amount (DC power, AC power, steam). The equipment combination type optimization device according to [1], characterized by the above.

[0055] [2] According to [2], since the input / output characteristics of the conversion type equipment are shown by a piecewise linear conversion map, the calculation amount of the simulation of this input / output characteristic can be reduced and the calculation can be performed quickly.

[0056] [3] The conversion type equipment inputs (DC power, AC power, gas, sunlight) one or more types of energy resources and outputs one or more types of resources (DC power, AC power, steam). The equipment combination type optimization device according to [1], characterized in that...

[0057] [3] According to this, it is possible to easily calculate the optimal equipment configuration of a system (3) including generators, power conditioners, etc. that mutually convert various resources.

[0058] [4] The storage type equipment inputs resources of one or more types of energy and outputs the same type of resources, and accumulates the difference. The equipment combination type optimization device according to [1], characterized in that...

[0059] [4] According to this, it is possible to easily calculate the optimal equipment configuration of a system (3) including storage type equipment represented by a storage battery (36), etc.

[0060] [5] The network condition generation unit (13) has a unit conversion function between the input resource amount and the output resource amount of the conversion type equipment. The equipment combination type optimization device according to [1], characterized in that...

[0061] [5] According to this, even when the input and output unit systems of the conversion type equipment are different, it is possible to simulate the equipment input and output of the system (3).

[0062] [6] Any of the input resources and output resources of the conversion type equipment, and the input resources and output resources of the storage type equipment are electric power, and a power charge conversion unit (18) that calculates the relationship between the power and the charge with different power charges for each time zone. The equipment combination type optimization device according to [1], further comprising... The equipment combination type optimization device according to [1], characterized in that...

[0063] [6] According to this, even if the power company changes the power charge plan for each time zone, the change can be made local.

[0064] [7] An equipment configuration generation unit (17) that generates the equipment configuration of a system combining conversion type equipment or storage type equipment. The equipment combination type optimization device according to [1], characterized by comprising

[0065] According to [7], the optimal equipment configuration of the system (3) combining the conversion type equipment or the accumulation type equipment can be easily calculated.

[0066] [8] A system template group (22) for fitting any conversion type equipment or any accumulation type equipment, An equipment catalog group (21) related to the conversion type equipment or the accumulation type equipment to be fitted into any of the system template groups (22), The equipment combination type optimization device according to [7], characterized by comprising

[0067] [8] According to [8], since it comprises a system template group (22) and an equipment catalog group (21) to be fitted into any of them, it is possible to easily and quickly generate a variation of the equipment configuration of the system (3).

[0068] [9] The equipment configuration generation unit (17) fits any of the conversion type equipment or the accumulation type equipment of the equipment catalog group (21) into any of the system template groups (22) to generate the equipment configuration of the system. The equipment combination type optimization device according to [8], characterized by

[0069] [9] According to [9], the equipment configuration generation unit (17) can quickly generate a variation of the equipment configuration of the system (3) by fitting the equipment of the equipment catalog group (21) into any of the system template groups (22).

[0070]

[10] The equipment configuration generation unit (17) comprises an equipment catalog group related to the conversion type equipment or the accumulation type equipment, and generates the equipment configuration of the system by selecting and combining one or more pieces of equipment from the equipment catalog group. The equipment combination type optimization device according to [7], characterized by

[0071] According to

[10] , the combination of the equipment configuration of the system can be generated from the equipment catalog group.

[0072]

[11] For each equipment configuration of a plurality of systems generated by the equipment configuration generation unit (17), compare the important performance evaluation indicators calculated by the optimal plan formulation unit (15), and select the equipment configuration for which the most excellent important performance evaluation indicator is calculated. An optimal equipment configuration selection unit (19), The equipment combination type optimization device according to [7], further comprising the above.

[0073]

[11] According to this, based on the important performance evaluation indicators related to the equipment configuration of the system, the most excellent equipment configuration can be selected.

[0074]

[12] An optimal equipment configuration selection support unit (16) that displays, in a comparable manner, a plurality of important performance evaluation indicators calculated by the optimal plan formulation unit (15) for each equipment configuration of a plurality of systems generated by the equipment configuration generation unit (17), The equipment combination type optimization device according to claim [7], further comprising the above.

[0075]

[12] According to this, it is possible to support the selection of the equipment configuration of the system based on the important performance evaluation indicators.

[0076]

[13] For a system (3) that combines a conversion type equipment that takes one or more types of resources as input and outputs one or more types of resources, or an accumulation type equipment that takes one or more types of resources as input, outputs the same type of resources, and accumulates the difference, the conversion type equipment condition generation unit (11) determines, for each of the conversion type equipments, at least the input resource amount and the output resource amount at each time as decision variables, and generates the relationship between the input resource amount and the output resource amount as a constraint condition. The storage type equipment condition generation unit (12) generates, for each of the storage type equipments, a constraint condition that at least the input resource amount and the output resource amount at each time are decision variables, and the storage resource amount, which is the sum of the difference between the input resource amount and the output resource amount and the storage resource amount at the time, is equal to or greater than a lower limit value and equal to or less than an upper limit value. The network condition generation unit (13) generates, as a network constraint condition, that the sum of the output resource amounts of the same type from the conversion type equipment or the storage type equipment, and the sum of the input resource amounts of the same type to other conversion type equipments or other storage type equipments are equal, or the input resource amount is larger. The objective function generation unit (14) generates an objective function related to the key performance evaluation index using one or more values of the input resource amount or the output resource amount. The optimal planning department (15) calculates the input resource amount and the output resource amount for each time of the conversion type equipment and the storage type equipment using the decision variables and constraint conditions of 0 or more of the conversion type equipments generated by the conversion type equipment condition generation unit (11), the decision variables and constraint conditions of 0 or more of the storage type equipments generated by the storage type equipment condition generation unit (12), one or more network constraint conditions generated by the network condition generation unit (13), and the objective function generated by the objective function generation unit (14). An equipment combination type optimization method characterized by comprising the above.

[0077] According to

[13] , the optimal equipment configuration in a system combining a conversion type equipment and a storage type equipment can be searched in a short time.

[0078]

[14] On a computer, For a system that combines a conversion facility that takes one or more types of resources as input and outputs one or more types of resources, or an accumulation facility that takes one or more types of resources as input, outputs the same type of resources, and accumulates the difference, for each of the conversion facilities, a procedure for generating at least the input resource amount and output resource amount per time as decision variables, and using the relationship between the input resource amount and the output resource amount as a constraint condition, For each of the accumulation facilities, a procedure for generating at least the input resource amount and output resource amount per time as decision variables, and using as a constraint condition that the accumulated resource amount, which is the sum of the difference between the input resource amount and the output resource amount and the accumulated resource amount at that time, is equal to or greater than a lower limit value and equal to or less than an upper limit value, A procedure for generating, as a network constraint condition, that the sum of the output resource amounts of the same type from the conversion facility or the accumulation facility, and the sum of the input resource amounts of the same type to other conversion facilities or other accumulation facilities are equal, or the input resource amount is larger, A procedure for generating an objective function related to key performance evaluation indicators using one or more values of the input resource amount or the output resource amount, A procedure for calculating the input resource amount and output resource amount per time of the conversion facility and the accumulation facility using the generated decision variables and constraint conditions of zero or more of the conversion facilities, the generated decision variables and constraint conditions of zero or more of the accumulation facilities, the generated one or more network constraint conditions, and the generated objective function, An equipment combination type optimization program for executing the above.

[0079] According to

[14] , an optimal equipment configuration in a system combining a conversion facility and an accumulation facility can be searched for in a short time.

[0080] (Modification example) The present invention is not limited to the above-described embodiments, and includes various modifications. For example, the above-described embodiments have been described in detail for easy understanding of the present invention, and are not necessarily limited to those having all the configurations described. It is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Further, it is possible to add, delete, or replace other configurations for a part of the configuration of each embodiment.

[0081] Each of the above configurations, functions, processing units, processing means, etc. may be realized by hardware such as an integrated circuit for a part or all of them. Each of the above configurations, functions, etc. may be realized by software by a processor interpreting and executing a program for realizing each function. Information such as a program, table, file, etc. for realizing each function can be placed in a recording device such as a memory, hard disk, SSD (Solid State Drive), or a recording medium such as a flash memory card, DVD (Digital Versatile Disk).

[0082] In each embodiment, the control lines and information lines show those considered necessary for explanation, and do not necessarily show all the control lines and information lines on the product. In reality, it may be considered that almost all the configurations are interconnected.

Explanation of Reference Numerals

[0083] 10 Equipment Combination Type Optimization Device 11 Conversion Type Equipment Condition Generation Unit 12 Accumulation Type Equipment Condition Generation Unit 13 Network Condition Generation Unit 14 Objective Function Generation Unit 15 Optimal Plan Formulation Unit 16 Optimal Equipment Configuration Selection Support Unit 17 Equipment Configuration Generation Unit 18 Power Charge Conversion Unit 19 Optimal Equipment Configuration Selection Unit 21 Equipment Catalog Group 22 System Templates Group 23 Equipment Combination Type Optimization Program 101 CPU 102 ROM 103 RAM 104 Input Unit 105 Communication Unit 106 Display Unit 107 Memory Unit 3 System 30 Electricity Selling Equipment 31 Power Demand 32 Solar Power Generation Panel 33 Solar Power Generation Panel Power Conditioner 35,34 Battery Power Conditioner 36 Battery 301,302,304,305 Power Nodes 40 Gas Purchase Equipment 41 Gas Cogeneration 42 Gas Boiler 43 Steam Demand 401 Gas Node 402 Steam Node

Claims

1. Regarding a system that combines a conversion-type facility that takes one or more types of resources as input and outputs one or more types of resources, or an accumulation-type facility that takes one or more types of resources as input, outputs the same type of resources, and accumulates the difference, for each of the above conversion-type facilities, at least the input resource amount and output resource amount for each time are used as decision variables, and a conversion-type facility condition generation unit that generates the relationship between the input resource amount and the output resource amount as a constraint condition; Regarding each of the above accumulation-type facilities, at least the input resource amount and output resource amount for each time are used as decision variables, and an accumulation-type facility condition generation unit that generates, as a constraint condition, that the accumulation resource amount, which is the sum of the difference between the input resource amount and the output resource amount and the accumulated resource amount at that time, is equal to or greater than a given lower limit value and equal to or less than an upper limit value; A network condition generation unit that generates, as a network constraint condition, that the sum of the output resource amounts of the same type from the above conversion-type facility or the above accumulation-type facility and the sum of the input resource amounts of the same type to other conversion-type facilities or other accumulation-type facilities are equal, or that the input resource amount is larger; An objective function generation unit that generates an objective function related to key performance evaluation indicators using one or more values among the above input resource amount or output resource amount; Using the decision variables and constraint conditions of 0 or more of the above conversion-type facilities generated by the conversion-type facility condition generation unit, the decision variables and constraint conditions of 0 or more of the above accumulation-type facilities generated by the accumulation-type facility condition generation unit, 1 or more of the above network constraint conditions generated by the network condition generation unit, and the above objective function generated by the objective function generation unit, an optimal planning unit that calculates the input resource amount and output resource amount for each time of the conversion-type facility and the accumulation-type facility; An equipment combination type optimization device characterized by comprising the above.

2. The conversion-type facility condition generation unit receives the input of a piecewise linear conversion map that converts the input resource amount of the conversion-type facility into an output resource amount. The equipment combination type optimization device according to claim 1, characterized by the above.

3. The conversion-type facility takes one or more types of energy resources as input and outputs one or more types of resources. The equipment combination type optimization device according to claim 1, characterized by the above.

4. The accumulation-type facility takes one or more types of energy resources as input, outputs the same type of resources, and accumulates the difference. The equipment combination type optimization device according to claim 1, characterized in that...

5. The network condition generation unit has a unit conversion function between the input resource amount and the output resource amount of the conversion type equipment. The equipment combination type optimization device according to claim 1, characterized in that...

6. Any one of the input resources and output resources of the conversion type equipment, and the input resources and output resources of the storage type equipment is electric power, A power rate conversion unit that calculates the relationship between power and rate with different power rates by time zone. The equipment combination type optimization device according to claim 1, further comprising...

7. An equipment configuration generation unit that generates an equipment configuration of a system combining conversion type equipment or storage type equipment. The equipment combination type optimization device according to claim 1, characterized in that it comprises...

8. A system template group for fitting any conversion type equipment or any storage type equipment, An equipment catalog group related to the conversion type equipment or storage type equipment for fitting into any of the system template groups. The equipment combination type optimization device according to claim 7, characterized in that it comprises...

9. The equipment configuration generation unit generates the equipment configuration of the system by fitting any one of the conversion type equipment or storage type equipment in the equipment catalog group into any of the system template groups. The equipment combination type optimization device according to claim 8, characterized in that...

10. The equipment configuration generation unit comprises an equipment catalog group related to conversion type equipment or storage type equipment, and generates the equipment configuration of the system by selecting and combining one or more pieces of equipment from the equipment catalog group. The equipment combination type optimization device according to claim 7, characterized in that...

11. An optimal equipment configuration selection unit that compares the important performance evaluation indicators calculated by the optimal plan formulation unit for each equipment configuration of the plurality of systems generated by the equipment configuration generation unit, and selects the equipment configuration for which the most excellent important performance evaluation indicator is calculated. The equipment combination type optimization device according to claim 7, further comprising...

12. An optimal equipment configuration selection support unit that displays the plurality of important performance evaluation indicators calculated by the optimal plan formulation unit in a comparable form for each equipment configuration of the plurality of systems generated by the equipment configuration generation unit. The equipment combination type optimization device according to claim 7, further comprising...

13. For a system that combines a conversion-type facility that takes one or more types of resources as input and outputs one or more types of resources, or an accumulation-type facility that takes one or more types of resources as input, outputs the same type of resources, and accumulates the difference, a conversion-type facility condition generation unit, for each of the conversion-type facilities, uses at least the input resource amount and the output resource amount at each time as decision variables, and generates the relationship between the input resource amount and the output resource amount as a constraint condition. An accumulation-type facility condition generation unit, for each of the accumulation-type facilities, uses at least the input resource amount and the output resource amount at each time as decision variables, and generates as a constraint condition that the accumulation resource amount, which is the sum of the difference between the input resource amount and the output resource amount and the accumulated resource amount at that time, is equal to or greater than a lower limit value and equal to or less than an upper limit value. A network condition generation unit generates, as a network constraint condition, that the sum of the output resource amounts of the same type from the conversion-type facility or the accumulation-type facility, and the sum of the input resource amounts of the same type to another conversion-type facility or another accumulation-type facility are equal, or the input resource amount is larger. An objective function generation unit generates an objective function regarding an important performance evaluation index using one or more values among the input resource amount or the output resource amount. An optimal plan formulation unit calculates the input resource amount and the output resource amount at each time for the conversion-type facility and the accumulation-type facility using the decision variables and constraint conditions of zero or more of the conversion-type facilities generated by the conversion-type facility condition generation unit, the decision variables and constraint conditions of zero or more of the accumulation-type facilities generated by the accumulation-type facility condition generation unit, one or more network constraint conditions generated by the network condition generation unit, and the objective function generated by the objective function generation unit. An equipment combination type optimization method characterized by comprising the above.

14. On a computer, For a system that combines a conversion-type facility that takes one or more types of resources as input and outputs one or more types of resources, or an accumulation-type facility that takes one or more types of resources as input, outputs the same type of resources, and accumulates the difference, for each of the conversion-type facilities, a procedure for using at least the input resource amount and the output resource amount at each time as decision variables and generating the relationship between the input resource amount and the output resource amount as a constraint condition. For each of the storage-type devices, a procedure for generating, with at least the amount of input resources and the amount of output resources at each time as decision variables, and with the constraint that the storage resource amount, which is the sum of the difference between the amount of input resources and the amount of output resources and the storage resource amount at the time, is equal to or greater than a lower limit value and equal to or less than an upper limit value. A procedure for generating, as a constraint condition of the network, that the sum of the amounts of output resources of the same type from the conversion-type device or the storage-type device, and the sum of the amounts of input resources of the same type to other conversion-type devices or other storage-type devices are equal, or that the amount of input resources is greater. A procedure for generating an objective function related to key performance evaluation indicators using one or more values among the amount of input resources or the amount of output resources. A procedure for calculating the amount of input resources and the amount of output resources at each time for the conversion-type device and the storage-type device, using the generated decision variables and constraint conditions for 0 or more of the conversion-type devices, the generated decision variables and constraint conditions for 0 or more of the storage-type devices, the generated constraint conditions for 1 or more of the networks, and the generated objective function. A facility combination type optimization program for causing the above to be executed.

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