JP2017156963A - Operation support device, operation support system, operation support method and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To support an efficient operation examination of a resource supply facility.SOLUTION: The present invention relates to an operation support device configured to support operation of a demand/supply system including a resource supply facility, a resource user facility and a supply path. The operation support device comprises: mathematical formula group generation means by which, upon inputting a demand/supply system model of the demand/supply system, facility capability information representing facility capabilities of the resource supply facility and the supply path and analysis condition information including an attention restriction indicating one restriction condition among restriction conditions in an optimization problem of the demand/supply system,a mathematical formula group including multiple mathematical formulas representing a target variable of the optimization problem and the restriction condition is generated; first-order predicate logic formula generation means for generating a first-order predicate logic formula based on the mathematical formula group generated by the mathematical formula group generation means; and quantifier elimination means for generating a relational logic formula representing a relationship between the target variable of the demand/supply system model and the attention restriction according to a quantifier elimination method.SELECTED DRAWING: Figure 2

Description

  The present invention relates to an operation support apparatus, an operation support system, an operation support method, and a program.

  Regarding the distribution of the production and supply of resources (for example, steam and cold energy) that are produced and supplied by multiple facilities, the cost to be consumed (for example, gas, heavy oil, electric power, etc.) according to the demand of the facilities that require the resources And the like are conventionally known.

  In addition, by visualizing the relationship between the total cost (total cost) of facilities that produce and supply resources and the total demand of facilities that demand those resources, efficient operation of the supply and demand system can be examined. The technique which can be performed is conventionally known (for example, refer patent document 1).

Japanese Patent No. 576476

  Here, there are constraints such as an upper limit constraint and a lower limit constraint on the production / supply amount in facilities for producing and supplying resources (resource supply facilities).

  However, in the above-described conventional technology, it has not been possible to perform a study in consideration of the relationship between the constraint condition of the resource supply facility and the total cost. Therefore, for example, when the constraint condition of the resource supply facility can be relaxed, it has not been possible to examine whether or not the supply and demand system can be made efficient by the relaxation of the constraint condition.

  The embodiment of the present invention has been made in view of the above points, and aims to support efficient operation examination of resource supply facilities.

  To achieve the above object, an embodiment of the present invention provides a supply and demand including a resource supply facility for supplying resources, a resource consumer facility for demanding resources supplied from the resource supply facility, and a resource supply route. A driving support device for supporting the operation of the grid, wherein the supply and demand system model of the supply and demand system, the facility capacity information indicating the facility capacity of the resource supply facility and the supply path, and the constraint condition in the optimization problem of the supply and demand system Formula group generation means for generating a formula group including a plurality of formulas representing the objective variable of the optimization problem and the constraint condition when analysis condition information including a target constraint indicating one of the constraint conditions is input A first-order predicate logical expression generation means for generating a first-order predicate logical expression based on the mathematical expression group generated by the mathematical expression group generation means, and a first-order predicate logic generated by the first-order predicate logical expression generation means The expression The quantifier elimination method comprises the the objective variable of the supply system model, and a quantifier elimination means for generating a relation logic expression representing the relationship between the target constraint.

  According to the embodiment of the present invention, it is possible to support efficient operation examination of resource supply facilities.

It is a figure which shows the structure of an example of the operation assistance system which concerns on this embodiment. It is a figure explaining the outline | summary of the method of improving the efficiency of operation | use of a resource supply equipment with a support apparatus. It is a figure which shows the hardware constitutions of an example of the assistance apparatus which concerns on this embodiment. It is a figure which shows the function structure of an example of the assistance apparatus which concerns on this embodiment. It is a figure which shows an example of a supply-and-demand system model. It is a figure which shows an example of equipment capability information. It is a figure which shows an example of analysis condition information. It is a flowchart of an example of the production | generation process of the relational formula which concerns on this embodiment. It is a figure which shows an example of the 1st numerical formula group. It is a figure which shows an example of the 2nd numerical formula group. It is a figure which shows an example of a 3rd numerical formula group. It is a figure which shows an example of an external condition numerical formula group. It is a figure which shows an example of a first order predicate logical expression. It is a figure which shows an example of a relational logical expression. It is a flowchart of an example of the visualization process which concerns on this embodiment. It is a figure which shows an example of the relationship graph which shows the relationship between an objective variable and attention restrictions. It is a figure which shows an example of the 2nd numerical formula group after correction. It is FIG. (1) explaining the relationship between the total cost before and behind correction, and a total demand. It is a figure which shows the other example of analysis condition information. It is a figure which shows the other example of a first order predicate logical expression. It is a figure which shows the other example of a relational logical expression. It is a figure which shows the other example of the relationship graph which shows the relationship between an objective variable and attention restrictions. It is a figure which shows the other example of the 2nd numerical formula group after correction. It is the figure (the 2) explaining the relationship between the total cost before and behind correction, and a total demand.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

  First, the system configuration of the operation support system 1 according to the present embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating a configuration of an example of an operation support system according to the present embodiment.

  The operation support system 1 shown in FIG. 1 includes a support device 10 and an input / output device 20 and supports examination of efficient operation of the supply and demand system. Here, the supply and demand system means a resource supply facility that produces and supplies resources, a resource consumer facility that demands resources that the resource supply facility produces and supplies, and a resource supply facility that supplies resources to the resource consumer facility. And a supply path for the system.

  Specific examples of the supply and demand system include, for example, a steam generation facility that produces and supplies “steam” as a resource, a steam use facility that demands “steam” to produce electric power, and a steam generation facility. And an electric power system including a steam transport facility for supplying “steam” to the steam using facility.

  The support device 10 is an information processing device such as a computer, for example, and provides information for supporting examination of efficient operation of the supply and demand system. That is, the support apparatus 10 determines the total cost consumed by the supply and demand system when the restriction condition is relaxed according to the total resource (total demand) demanded by the supply and demand system and the constraint condition of the supply and demand system ( Information for determining whether or not the total cost can be reduced is provided.

  Here, the constraint condition is a constraint condition in the optimization problem of the supply and demand system, for example, the lower limit or upper limit constraint of the resource amount of the resource that the resource supply facility produces and supplies, and the resource amount that the supply route can supply. Examples include a lower limit constraint and an upper limit constraint. The total cost consumed by the supply and demand system is, for example, the cost (consumption cost) of gas and power consumed when the resource supply facility produces and supplies resources, and the supply route supplies resources. It is the total of costs such as power (consumption costs).

  The input / output device 20 is a device including a keyboard, a mouse, a display, and the like, for example. The input / output device 20 is used to input various types of information (for example, total demand, resource supply facility constraint conditions, etc.) to the support device 10, and information provided from the support device 10 (for example, A relationship graph showing the relationship between the total cost and the constraint condition).

  Note that the input / output device 20 may be directly connected to the support device 10 or may be connected via a network or the like.

  Here, in the operation support system 1 according to the present embodiment, an outline of a method for improving the efficiency of the operation of the supply and demand system (that is, the efficiency of the operation of the resource supply facility) by the support apparatus 10 will be described with reference to FIG. While explaining. FIG. 2 is a diagram illustrating an outline of a method for improving the efficiency of operation of the resource supply facility by the support device.

  As shown in FIG. 2, the support device 10 includes a supply / demand system model M that models the system configuration of the supply / demand system, facility capability information C that indicates the resource supply facilities included in the supply / demand system, and the facility capabilities of the supply path, The objective variable, the external condition, and the analysis condition information D defining the attention constraint are input. Note that the restriction of interest is a restriction condition in the optimization problem of the supply and demand system that the user (for example, a person in charge of operation or design of the supply and demand system) wants to know the relationship with the objective variable. That is.

  Then, the support apparatus 10 outputs a relationship graph indicating the relationship between the objective variable (that is, the total cost) and the attention constraint. In the present embodiment, the external condition defined in the analysis condition information D is the total demand amount in the supply and demand system. However, the external condition is not limited to the total demand, and any condition that affects the objective variable and constraint conditions of the supply and demand system can be set. For example, when the equipment efficiency is a model that changes with a parameter, a condition that the parameter should satisfy may be set as an external condition.

In the present embodiment, the objective variable is described as being the total cost, but is not limited thereto. As the objective variable, for example, an arbitrary variable such as the total energy consumed by the supply and demand system and the total CO ₂ emission amount discharged by the supply and demand system can be set.

  Thereby, the user can reduce the total cost while maintaining the total demand amount of the supply and demand system by relaxing the attention restriction based on, for example, the relation graph displayed on the input / output device 20. Can be considered. In other words, the user can consider whether or not a more efficient supply and demand system can be operated based on the relationship graph (that is, whether or not a more efficient resource supply facility can be operated). .

  Next, the hardware configuration of the support apparatus 10 according to the present embodiment will be described with reference to FIG. FIG. 3 is a diagram illustrating a hardware configuration of an example of the support device according to the present embodiment.

  The support device 10 illustrated in FIG. 3 includes a CPU 11, a RAM (Random Access Memory) 12, a ROM (Read Only Memory) 13, a storage device 14, an external I / F 15, and a communication I / F 16. These pieces of hardware are connected to each other via a bus B so that they can communicate with each other.

  The CPU 11 is an arithmetic device that realizes control and functions of the entire support device 10 by reading a program and data from the ROM 13 and the storage device 14 onto the RAM 12 and executing processing.

  The RAM 12 is a volatile semiconductor memory that can temporarily store programs and data. The ROM 13 stores data such as OS (Operating System) settings and network settings of the support apparatus 10.

  The storage device 14 is a non-volatile memory that stores various programs and data. The programs and data stored in the storage device 14 include a program that realizes the present embodiment, an OS that is basic software for controlling the entire support device 10, and a program that provides various functions on the OS.

  The external I / F 15 is an interface with an external device. The external device includes a recording medium 15a. Thereby, the support apparatus 10 can read and write the recording medium 15a via the external I / F 15. The recording medium 15a includes a flexible disk, CD, DVD, SD memory card, USB memory, and the like.

  The communication I / F 16 is an interface for connecting the support apparatus 10 to a network. Thereby, the support apparatus 10 can perform data communication via the communication I / F 16.

  The support apparatus 10 according to the present embodiment can implement various processes described later by having the above hardware configuration.

  Next, the functional configuration of the support apparatus 10 according to the present embodiment will be described with reference to FIG. FIG. 4 is a diagram illustrating a functional configuration of an example of the support device according to the present embodiment.

  The support device 10 illustrated in FIG. 4 includes a relational logic expression generation unit 101 and a visualization unit 102. Each of these functional units is realized by a process that the CPU 11 causes one or more programs installed in the support apparatus 10 to execute.

  The relational logic expression generation unit 101 generates a relational logic expression for displaying a relation graph indicating the relation between the objective variable (total cost) and the attention constraint. In other words, the relational logical expression generation unit 101 generates a relational logical expression that expresses the relation between the objective variable (total cost) and the attention constraint by a logical expression.

  Here, the relational logical expression generation unit 101 includes a mathematical expression group generation unit 111, a first-order predicate logical expression generation unit 1112, and a quantifier elimination unit 113.

  The formula group generation unit 111 is a set of formulas representing objective variables in the optimization problem and definitions related thereto based on the supply and demand system model M and the facility capability information C input from the input / output device 20. A “numerical expression group” and a “second mathematical expression group” that is a set of expressions representing the constraint conditions are generated.

  Further, the formula group generation unit 111 changes the second formula group with respect to the attention constraint based on the analysis condition information D input from the input / output device 20 and the generated second formula group. 3 formula groups "are generated.

  Based on the analysis condition information D input from the input / output device 20, the first-order predicate logical expression generation unit 112 generates an “external condition formula group” that is a set of expressions representing external conditions. In addition, the first-order predicate logical expression generation unit 112 generates a “first-order predicate logical expression” based on the first mathematical expression group and the third mathematical expression group generated by the mathematical expression group generation unit 111 and the external condition mathematical expression group. Is generated.

  The quantifier elimination unit 113 uses a quantifier elimination method based on the first-order predicate logical expression generated by the first-order predicate logical expression generation unit 112 to express a relational logic representing the relationship between the total cost and the attention constraint as a logical expression. Generate an expression.

  The visualization unit 102 outputs a relation graph based on the relational logical expression generated by the relational logical expression generation unit 101 to the input / output device 20. That is, the visualization unit 102 displays a relationship graph G indicating the relationship between the objective variable (total cost) and the attention constraint on the input / output device 20.

  Here, the supply and demand system model M, the facility capability information C, and the analysis condition information D input from the input / output device 20 will be described.

  First, the supply and demand system model M will be described with reference to FIG. FIG. 5 is a diagram illustrating an example of a supply and demand system model.

  The supply and demand system model M shown in FIG. 5 uses the gas supplied from the gas supply facility as fuel to generate steam in each of the steam generation facilities 1 to 3, supplies steam to the steam use facility by the steam transport facility, Steam is demanded in steam-using facilities.

  At this time, each of the steam generating facilities 1 to 3 is a “resource supply facility”, a steam using facility is a “resource consumer facility”, and a steam transport facility is a “supply route”. Further, the gas consumed as fuel in each of the steam generating facilities 1 to 3 is “consumption cost”, and the steam supplied from each of the steam generating facilities 1 to 3 is “resource”. In the supply and demand system model M shown in FIG. 5, an example in which there is one resource consumer facility is shown, but the present invention is not limited to this, and there may be a plurality of resource consumer facilities.

  Next, the facility capability information C corresponding to the supply and demand system model M will be described with reference to FIG. FIG. 6 is a diagram illustrating an example of facility capability information.

The facility capability information C shown in FIG. 6 is information representing the characteristics and constraint conditions of the resource supply facilities 1 to 3. That is, the consumption cost (consumption gas amount) C ₁ of the resource supply facility 1 can be expressed as “C ₁ = 30S ₁ ” in relation to the supply amount (steam supply amount) S ₁ as shown in FIG. . Further, the constraint conditions (lower limit constraint and upper limit constraint) of the resource supply facility 1 can be expressed as “S ₁ ≧ 1” and “S ₁ ≦ 8”, as shown in FIG.

Similarly, the consumption cost (consumption gas amount) C ₂ of the resource supply facility 2 may be expressed as “C ₂ = 40S ₂ ” in relation to the supply amount (steam supply amount) S ₂ as shown in FIG. it can. Further, the constraint conditions (lower limit constraint and upper limit constraint) of the resource supply facility 2 can be expressed as “S ₂ ≧ 3” and “S ₂ ≦ 9”, as shown in FIG.

Similarly, the consumption cost (consumption gas amount) C ₃ of the resource supply facility 2 is expressed as “C ₃ = 50S ₃ ” in relation to the supply amount (steam supply amount) S ₃ as shown in FIG. it can. Further, the constraint conditions (lower limit constraint and upper limit constraint) of the resource supply facility 3 can be expressed as “S ₃ ≧ 2” and “S ₃ ≦ 8” as shown in FIG.

  Next, the analysis condition information D will be described with reference to FIG. FIG. 7 is a diagram illustrating an example of analysis condition information.

Analysis condition information D shown in FIG. 7 is information defining objective variables, external conditions, and attention constraints. That is, in the analysis condition information D shown in FIG. 7, a variable “E” indicating the total cost (total gas consumption) is defined as the objective variable. Further, in the analysis condition information D shown in FIG. 7, the total demand amount “L = 15” of resources demanded by the supply / demand system indicated by the supply / demand system model M is defined as the external condition Cnt ₁ . Furthermore, in the analysis condition information D shown in FIG. 7, the lower limit constraint “Rst _1,1 ” of the resource supply facility 1 is defined as the attention constraint.

As will be described later, the lower limit constraint “Rst _1,1 ” is a constraint condition indicating the lower limit of the supply amount of the resource supply facility 1 of the supply and demand system model M, and “S ₁ −1 ≧ 0”. .

  Thus, the user creates the supply and demand system model M, the facility capability information C, and the analysis condition information D using the input / output device 20 and inputs them to the support device 10. In the following description, unless otherwise specified, it is assumed that the supply and demand system model M shown in FIG. 5, the facility capability information C shown in FIG. 6, and the analysis condition information D shown in FIG. 7 are input to the support device 10. do.

  Next, processing for generating a relational logical expression in the support device 10 included in the operation support system 1 according to the present embodiment will be described with reference to FIG. FIG. 8 is a flowchart of an example of relational logic expression generation processing according to the present embodiment.

  First, the relational logic expression generation unit 101 causes the expression group generation unit 111 to generate a first expression group and a second expression group based on the supply and demand system model M and the facility capability information C (step S1). That is, the formula group generation unit 111 generates the first formula group 1000 shown in FIG. 9 and the second formula group 2000 shown in FIG. 10 based on the supply and demand system model M and the equipment capability information C.

The first mathematical expression group 1000 shown in FIG. 9 is generated by defining mathematical expressions Obj ₁ representing objective variables and mathematical expressions Obj _{2 to} Obj ₄ representing the characteristics of the resource supply facilities 1 to 3, respectively. Here, Obj ₁ is defined as an expression “E = C ₁ + C ₂ + C ₃ ” representing the relationship between the total cost E of the supply and demand system and the consumption costs C _{1 to} C ₃ of the resource supply facilities ₁ to _3. . Obj ₂ is defined by an expression “C ₁ = 30S ₁ ” representing the relationship between the consumption cost C ₁ of the resource supply facility 1 and the supply amount S ₁ . Similarly, Obj ₃ and Obj ₄ are defined as “C ₂ = 40S ₂ ” and “C ₃ = 50S ₃ ”.

The second mathematical expression group 2000 shown in FIG. 10 includes expressions Rst _L , Rst _1,1 , Rst _1,2 , Rst _2,1 , Rst _2,2 , Rst _3,1 and Rst _3,2 representing the constraint conditions. Generated by defining. Here, Rst _L is defined as a constraint condition “L− (S ₁ + S ₂ + S ₃ ) = 0” representing a supply and demand balance, where _L is the total demand amount of the supply and demand system. In addition, Rst _1,1 is “s ₁ g ₁ = S ₁ −1” and “s ₁ g ₁ ≧ 0”, where “s ₁ g ₁ ” is a variable representing the lower limit of the supply amount of the resource supply facility 1. Is defined. Similarly, Rst _{1 and 2} are “s ₁ g ₂ = 8−S ₁ ” and “s ₁ g ₂ ≧ 0”, where “s ₁ g ₂ ” is a variable representing the upper limit of the supply amount of the resource supply facility 1. Is defined. The same applies to Rst _2,1 , Rst _2,2 , Rst _3,1 and Rst _3,2 .

  Next, the relational logic expression generation unit 101 causes the expression group generation unit 111 to generate a third expression group based on the analysis condition information D and the second expression group (step S2). That is, the formula group generation unit 111 generates the third formula group 3000 shown in FIG. 11 based on the analysis condition information D and the second formula group 2000.

The third mathematical expression group 3000 shown in FIG. 11 is generated by excluding the inequality restriction of the attention restriction from the constraint conditions included in the second mathematical expression group 2000. Here, the attention constraint included in the external condition information D shown in FIG. 7 is “Rst _1,1 ”. Therefore, by removing (deleting) the inequality constraint “s ₁ g ₁ ≧ 0” from the constraint condition Rst _1,1 included in the second formula group 2000 shown in FIG. 10, the third formula group 3000 is created. The In the third mathematical formula group 3000, the constraint condition Rst _1,1 excluding the illegal expression constraint “s ₁ g ₁ ≧ 0” is defined as “(Rst _1,1 ) ^* ”.

  Next, the relational logic expression generation unit 101 generates an external conditional expression group based on the analysis condition information D by the first-order predicate logic expression generation unit 112 (step S3). That is, the first-order predicate logical expression generation unit 112 generates the external condition mathematical expression group 4000 shown in FIG. 12 based on the analysis condition information D.

The external condition formula group 4000 shown in FIG. 12 is generated by extracting external conditions included in the analysis condition information D shown in FIG. Here, the external condition included in the analysis condition information D shown in FIG. 7 is “Cnt ₁ ”. Accordingly, the external condition formula group 4000 shown in FIG. 12 defines the external condition Cnt ₁ .

Next, the relational logic expression generation unit 101 uses the first-order predicate logic expression generation unit 112 based on the first mathematical expression group, the third mathematical expression group, and the external condition mathematical expression group, and the target variable E and the attention constraint. A first-order predicate logical expression indicating that variables other than s ₁ g ₁ exist is generated (step S4). That is, the first-order predicate logical expression generation unit 112 is based on the first mathematical expression group 1000 shown in FIG. 9, the third mathematical expression group 3000 shown in FIG. 11, and the external condition mathematical expression group 4000 shown in FIG. A first order predicate logical expression 5000 shown in FIG. 13 is generated.

  The first order predicate logical expression 5000 shown in FIG. 13 can be generated by using a method similar to the method disclosed in Japanese Patent No. 576476, for example.

Specifically, the first-order predicate logical expression generation unit 112 _first performs Obj _{1 to} Obj ₄ , Rst _L , (Rst _1,1 ) ^* , Rst ₁ , ₂ , Rst _2,1 , Rst _2,2 , Rst _{2,2 3,1} , Rst _3,2 , and Cnt ₁ are combined by AND. Then, first-order logic formulas generator 112, the variable _(L, except the target constraint _s 1 _{g 1} and objective variable _{E, S 1, S 2,} S 3, C 1, C 2, C 3, s 1 g ₂ , s ₂ g ₁ , s ₂ g ₂ , s ₃ g ₁ , s ₃ g ₂ ) are also given presence symbols. Thereby, the first order predicate logical expression 5000 shown in FIG. 13 is generated.

  Next, the relational logic expression generating unit 101 generates a relational logic expression from the first-order predicate logical expression by using the limit symbol erasing method by the quantifier elimination unit 113 (step S5). That is, the quantifier elimination unit 113 generates the relational logical expression 6000 shown in FIG. 14 from the first-order predicate logical expression 5000 shown in FIG. 13 using the quantifier elimination method.

  The relational logical expression 6000 shown in FIG. 14 can be generated using a method similar to the method disclosed in Japanese Patent No. 5761476, for example. Note that the quantifier elimination method is a known technique, and therefore its description is omitted.

As a result, a relational logical expression 6000 is generated in which the relation between the objective variable E and the attention constraint s ₁ g ₁ is expressed by a logical expression.

As described above, the support device 10 according to the present embodiment can generate a relational logical expression representing the relationship between the objective variable defined by the user in the analysis condition information D and the attention constraint. In the relational logic generation process shown in FIG. 8, a relational logical expression representing the relationship between the objective variable E (that is, the total cost of the supply and demand system) and the attention constraint s ₁ g ₁ is generated. For example, s ₁ g ₂ , s ₂ g ₁ , s ₂ g ₂ , s ₃ g ₁ , or s ₃ g ₂ may be used.

  Next, in the support device 10 included in the operation support system 1 according to the present embodiment, a process for visualizing a relational logical expression (that is, a process for outputting a relational graph based on the relational logical expression to the input / output device 20) is shown in FIG. This will be described with reference to FIG. FIG. 15 is a flowchart of an example of a visualization process according to the present embodiment.

  First, the visualization unit 102 draws a region in which the relational logical expression generated by the relational logical expression generation unit 101 is true (step S11).

Next, the visualization unit 102 draws the boundary (constraint boundary) of the target constraint (for example, s ₁ g ₁ ) (step S12).

  Finally, the visualization unit 102 outputs the drawn area and boundary to the input / output device 20 (step S13).

  As a result, a relationship graph indicating the relationship between the objective variable and the attention constraint is displayed on the input / output device 20.

Here shows the objective variable E, the relationship graph _{G a} showing the relationship between the target restriction _s 1 _{g 1} in FIG. 16 (a). In the relation graph G _a shown in FIG. 16A, the region R _{a in} which the relational logical expression representing the relationship between the objective variable E and the target constraint s ₁ g ₁ is true and the constraint boundary B of the target constraint s ₁ g ₁ are included. _a (ie, s ₁ g ₁ = 0) is included. Thereby, the user can know that the objective variable E and the attention constraint s ₁ g _{1 are in a} positive correlation with the relation graph G _a shown in FIG. Therefore, the user can determine that the total cost E can be reduced if the attention constraint s ₁ g ₁ can be set to “0” or less (that is, the constraint can be relaxed).

Similarly, shows the objective variable E, the relationship graph _{G b} showing the relationship between the target restriction _s 1 _{g 2} in FIG. 16 (b). In the relation graph G _b shown in FIG. 16B, the region R _{b in} which the relational logical expression representing the relationship between the objective variable E and the target constraint s ₁ g ₂ is true and the constraint boundary B of the target constraint s ₁ g _{2 b} (ie, s ₁ g ₂ = 0). Thereby, the user can know that the objective variable E and the attention constraint s ₁ g ₂ are in a negative correlation with the relation graph G _b shown in FIG. Therefore, the user can determine that the total cost E cannot be reduced even if the attention constraint s ₁ g _{2 is set} to “0” or less (that is, even if the constraint is relaxed).

Similarly, FIG. 16C shows a relationship graph G _c showing the relationship between the objective variable E and the attention constraint s ₂ g ₁ . In the relation graph G _c shown in FIG. 16C, the region R _{c in} which the relational logical expression representing the relationship between the objective variable E and the attention constraint s ₂ g ₁ is true and the constraint boundary B of the attention constraint s ₂ g _{1 c} (ie, s ₂ g ₁ = 0). Thereby, the user can know that the objective variable E and the attention constraint s ₂ g ₁ are negatively correlated with each other by the relation graph G _c shown in FIG. Therefore, the user can determine that the total cost E cannot be reduced even if the attention constraint s ₂ g _{1 is set} to “0” or less.

Similarly, FIGS. 16D to 16F show relation graphs G _{d to} G _f , respectively. Similarly to the above, these relationship graphs G _{d to} G _f indicate whether or not the user can lower the total cost when the attention constraints s ₂ g _{2 to} s ₃ g ₂ are set to “0” or less, respectively. Can be judged.

Here, the relationship between the total cost E and the total cost L of the supply and demand system when the constraint corresponding to the attention constraint s ₁ g ₁ is relaxed will be described.

For example, as shown in FIG. 17, it is assumed that “Rst _1,1 ” included in the second mathematical formula group 2000 is corrected to “(Rst _1,1 ) ′” (that is, the constraint is relaxed). In other words, it is assumed that the lower limit constraint “S ₁ −1 ≧ 0” of the resource supply facility 1 is modified to “S ₁ ≧ 0”.

In this case, for example, the graph shown in FIG. 18 can be obtained by drawing a graph indicating the relationship between the total cost E before and after the correction and the total demand L by the method disclosed in Japanese Patent No. 576476. it can. As shown in FIG. 18, the user can know that the total cost in the case where the total demand amount L of the supply and demand system is 14 to 24 is reduced by relaxing the constraints Rst ₁ , ₁ .

Therefore, when the total demand amount L of the supply and demand system is 14 to 24, the user can determine that more efficient operation is possible by relaxing the restriction Rst ₁ , 1 of the resource supply facility 1. .

  As described above, in the operation support system 1 according to the present embodiment, the user creates the analysis condition information D including the objective variable and the attention constraint, thereby visualizing the relationship between the objective variable and the attention constraint in the supply and demand system. Can do. For this reason, in the operation support system 1 according to the present embodiment, the user determines whether or not the value of the objective variable (for example, the total cost) can be lowered by relaxing the constraint condition of the attention constraint. Can do.

  Therefore, according to the operation support system 1 according to the present embodiment, whether or not the user can improve the efficiency of the operation of the supply and demand system by relaxing various constraints on the resource supply facilities included in the supply and demand system, It is possible to examine how much mitigation is effective.

Hereafter, an example in which the external conditions included in the analysis condition information D are different from those in FIG. 7 will be described. That is, it is assumed that the analysis condition information D input from the input / output device 20 to the support device 10 is as shown in FIG. In the analysis condition information D shown in FIG. 19, the external condition Cnt ₁ is defined as “L = 10”.

  In this case, the first-order predicate logical expression 5000A shown in FIG. 20 is generated by executing the processing of steps S1 to S4 by the relational logical expression generation unit 101 of the support apparatus 10. Further, the relational logic expression generation unit 101 of the support apparatus 10 executes the process of step S5, thereby generating the relational logic expression 6000A shown in FIG.

And the relation graph (G _a ) ′ shown in FIG. 22A is displayed on the input / output device 20 by the processing of the steps S11 to S13 being executed by the visualization unit 102 of the support device 10.

The relation graph (G _a ) ′ shown in FIG. 22A includes _a region (R _a ) ′ in which the relational logical expression representing the relation between the objective variable E and the attention constraint s ₁ g ₁ is true. In the relationship graph (G _a ) ′ shown in FIG. 22A, the constraint boundary (B _a ) ′ of the target constraint s ₁ g ₁ is not displayed (that is, displayed on the region (R _a ) ′. Not.) Thereby, the user determines that the attention constraint s ₁ g ₁ cannot be reduced (that is, the constraint Rst ₁ , ₁ cannot be relaxed) by using the relation graph (G _a ) ′ illustrated in FIG. can do.

Similarly, FIGS. 22B to 2F show relationship graphs (G _b ) ′ to (G _f ) ′ when the external condition Cnt ₁ is “L = 10”, respectively. Similarly to the above, these relationship graphs (G _b ) ′ to (G _f ) ′ allow the user to lower the total cost when the attention constraints s ₁ g _{2 to} s ₃ g ₂ are set to “0” or less, respectively. It can be determined whether or not it is possible. In the relation graph (G _d ) ′ shown in FIG. 22D, the total cost is lowered when the attention constraint s ₂ g ₂ is lowered to “−3” (relaxation is reduced), while “−3” or less. This shows an example where the total cost increases when the value is lowered.

Here, the relationship between the total cost E and the total cost L of the supply and demand system when the constraint corresponding to the attention constraint s ₃ g ₂ is relaxed will be described.

For example, as shown in FIG. 23, it is assumed that “Rst _3,2 ” included in the second mathematical formula group 2000 is corrected to “(Rst _3,2 ) ′” (that is, the constraint is relaxed). In other words, it is assumed that the upper limit constraint “S ₁ −8 ≦ 0” of the resource supply facility 3 is modified to “S ₁ −9 ≦ 0”.

In this case, for example, the graph shown in FIG. 24 can be obtained by drawing a graph showing the relationship between the total cost E before and after the correction and the total demand L by the method disclosed in Japanese Patent No. 576476. it can. As shown in FIG. 24, the user can know that the total cost in the case where the total demand amount L of the supply and demand system is 5 to 19 is reduced by relaxing the constraints Rst _{3 and 2} .

Therefore, when the total demand amount L of the supply and demand system is 5 to 19, the user can determine that more efficient operation is possible by relaxing the restrictions Rst ₃ and ₂ of the resource supply facility 3. .

  The present invention is not limited to the specifically disclosed embodiments, and various modifications and changes can be made without departing from the scope of the claims.

DESCRIPTION OF SYMBOLS 1 Operation support system 10 Support apparatus 20 Input / output device 101 Relational logic expression generation part 102 Visualization part 111 Formula group generation part 112 First-order predicate logic expression generation part 113 Limit symbol elimination part

Claims (8)

A driving support device that supports the operation of a supply and demand system including a resource supply facility that supplies resources, a resource consumer facility that demands resources supplied from the resource supply facility, and a resource supply path,
Including a supply and demand system model of the supply and demand system, facility capacity information indicating the facility capacity of the resource supply facility and the supply path, and an attention constraint indicating one of the constraint conditions in the optimization problem of the supply and demand system When the analysis condition information is input, a formula group generation unit that generates a formula group including a plurality of formulas representing the objective variable of the optimization problem and the constraint condition;
First-order predicate logical expression generation means for generating a first-order predicate logical expression based on the mathematical expression group generated by the mathematical expression group generation means;
The first order predicate logical expression generated by the first order predicate logical expression generation means is limited to generate a relational logical expression representing the relationship between the objective variable of the supply and demand system model and the attention constraint by a limit symbol elimination method. Symbol erasing means;
A driving support device having   Based on the relational logic generated by the limit symbol erasing means, a graph is generated that represents the region satisfying the relational logical expression and the constraint boundary of the attention constraint, and the display device connected to the driving support device The driving support apparatus according to claim 1, further comprising a visualization unit that displays the graph. The visualization means includes:
The driving support device according to claim 2, wherein a graph in which the region and a straight line indicating the constraint boundary are superimposed is generated, and the graph is displayed on the display device. The formula group generation means includes:
As the objective variable, a first mathematical expression group representing a relationship between a resource supply amount of the resource supply facility and a consumption cost in the resource supply facility is generated,
As the constraint condition, after generating a second mathematical expression group representing an upper limit constraint and / or a lower limit constraint of the resource supply amount of the resource supply facility and the supply path, an upper limit constraint included in the second mathematical expression group and / or Or the driving assistance apparatus as described in any one of Claims 1 thru | or 3 which produces | generates the 3rd numerical formula group which deleted the upper limit constraint corresponding to the said attention constraint, or the inequality constraint of a lower limit constraint among lower limit constraints. The analysis condition information includes an external condition indicating a total demand amount of the resource demanded by the resource consumer facility,
The first order predicate logical expression generation means includes:
The first mathematical formula group, the third mathematical formula group, and the external condition are combined by a logical product, and are included in the first mathematical formula group, the third mathematical formula group, and the external condition. The driving support device according to claim 4, wherein the first-order predicate logical expression is generated by adding an existence symbol indicating that a variable exists. A driving support device for supporting the operation of a supply and demand system including a resource supply facility for supplying resources, a resource consumer facility for demanding resources supplied from the resource supplying facility, and a resource supply route, and the driving support device A driving support system having an input / output device connected to
Including a supply and demand system model of the supply and demand system, facility capacity information indicating the facility capacity of the resource supply facility and the supply path, and an attention constraint indicating one of the constraint conditions in the optimization problem of the supply and demand system When the analysis condition information is input, a formula group generation unit that generates a formula group including a plurality of formulas representing the objective variable of the optimization problem and the constraint condition;
First-order predicate logical expression generation means for generating a first-order predicate logical expression based on the mathematical expression group generated by the mathematical expression group generation means;
The first order predicate logical expression generated by the first order predicate logical expression generation means is limited to generate a relational logical expression representing the relationship between the objective variable of the supply and demand system model and the attention constraint by a limit symbol elimination method. Symbol erasing means;
Visualization means for displaying a graph representing a region satisfying the relational logical expression and a constraint boundary of the attention restriction based on the relational logical expression generated by the limit symbol erasing means;
A driving support system. A driving support method used for a driving support device that supports the operation of a supply and demand system including a resource supply facility that supplies resources, a resource consumer facility that demands resources supplied from the resource supply facility, and a resource supply route Because
Including a supply and demand system model of the supply and demand system, facility capacity information indicating the facility capacity of the resource supply facility and the supply path, and an attention constraint indicating one of the constraint conditions in the optimization problem of the supply and demand system When the analysis condition information is input, a formula group generation procedure for generating a formula group including a plurality of formulas representing the objective variable of the optimization problem and the constraint condition;
A first-order predicate logical expression generation procedure for generating a first-order predicate logical expression based on the mathematical expression group generated by the mathematical expression group generation procedure;
A limitation that generates a relational logical expression that represents the relationship between the objective variable of the supply and demand system model and the attention constraint by using a limit symbol elimination method on the first-order predicate logical expression generated by the first-order predicate logical expression generation procedure. Symbol erasure procedure;
A driving support method. An operation support device for supporting operation of a supply and demand system including a resource supply facility for supplying resources, a resource consumer facility for demanding resources supplied from the resource supply facility, and a resource supply route;
Including a supply and demand system model of the supply and demand system, facility capacity information indicating the facility capacity of the resource supply facility and the supply path, and an attention constraint indicating one of the constraint conditions in the optimization problem of the supply and demand system Formula group generation means for generating a formula group including a plurality of formulas representing the objective variable of the optimization problem and the constraint condition when analysis condition information is input,
First-order predicate logical expression generation means for generating a first-order predicate logical expression based on the mathematical expression group generated by the mathematical expression group generation means;
The first order predicate logical expression generated by the first order predicate logical expression generation means is limited to generate a relational logical expression representing the relationship between the objective variable of the supply and demand system model and the attention constraint by a limit symbol elimination method. Symbol erasing means,
Program to function as.

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