JP5761476B2 - Energy management support device and energy management support program - Google Patents

Description

  The present invention relates to a technology for supporting the operation of a facility for supplying energy for a supply and demand system having a resource supply facility for supplying resources such as electric power and gas and a resource consumer facility for demanding resources.

  2. Description of the Related Art Conventionally, a technique for optimizing a system by expressing a problem such as system control and circuit analysis by a first-order predicate logical expression and solving this is known (for example, Non-Patent Document 1). .

  Specifically, a quantifier represented by a universal symbol (∀) or an existence symbol (∃), and a logical symbol represented by a product (∧) or a sum (∨) of a polynomial equality or inequality of other variables The first order predicate logical expressions are obtained by combining the logical expressions combined using. Among variables appearing in a logical expression, a variable bound by a quantifier is called a bound variable, and a variable not bound by a quantifier is called a free variable. In the first order predicate logical expression, optimization is achieved by eliminating the bound variable and deriving a logical expression that the free variable should satisfy.

  As a known technique, a technique for performing control system design and control system analysis using a quantifier elimination method is also disclosed (for example, Patent Document 1). According to this, the control system analysis / design apparatus formulates the input control problem as a linear matrix inequality (LMI) or a bilinear matrix inequality (BMI). Then, the constraints such as the design specifications expressed as LMI or BMI are transformed into constraints of the form in which inequalities are connected with logical sums, the control system is converted into a first-order predicate logical expression, and the variable with the quantifier is The control system is analyzed from the deleted formula.

  In particular, for a technique for optimizing the operation of a power system, optimal power flow calculation is generally known (for example, Non-Patent Document 2). According to the optimal power flow calculation, in a supply system in which the power generation equipment and the load equipment are connected by a supply path, the desired power is generated while minimizing the fuel cost consumed by the power generation equipment according to the load of the load equipment. Perform optimization.

JP 11-328239 A

Hirokazu Anai and Kazuhiro Yokoyama, “Calculation algorithm of QE and its application Optimization by mathematical processing”, University of Tokyo Press, 2011, p. 214-221 Sekine Taiji [others], "Optimal Power Flow Calculation (OPF)", NEC Corporation, 2002, p. 20-25

  According to the prior art, it is possible to determine how the existing supply system can be optimized. That is, the prior art is an optimization technique when resource supply facilities and their capacities are specifically set. In other words, in the conventional technology, in order to efficiently operate the resource supply equipment, when examining the problems such as how much capacity each equipment should have or how the supply and demand system should be configured Cannot be used effectively.

In addition, prior to the introduction of conventional optimal operation techniques, it is usually necessary to consider in advance, but there is no way to know in advance how much the current operation results are and there is room for improvement for further energy saving. It was difficult to determine whether or not to do so, and there was a risk in terms of return on investment.
Furthermore, when evaluating how good the ideal operation required by the conventional optimal operation technology is compared to the conventional operation, there was a method of evaluating by difference or improvement ratio, etc. It is difficult to objectively evaluate how reasonable the improvement rate is. For example, when the improvement rate is insufficient, such as less than 0.01%, it is difficult to determine whether the conventional optimal operation technique is deficient or due to the operation limit of the supply and demand system.

  An object of this invention is to provide the means which can be utilized widely widely when examining the efficient operation of resource supply equipment.

  A first aspect of the present invention consumes energy for a resource supply facility for supplying resources, a resource consumer facility for demanding resources supplied from the resource supply facility, and a supply and demand system having a resource supply path. An energy management support device for supporting the operation of equipment, wherein when the supply / demand system model of the supply / demand system and the equipment capacity information indicating the equipment capacity of the resource supply equipment and the supply path are input, the supply / demand system model and Based on the equipment capability information, a formula group generating unit that generates a formula group consisting of a plurality of formulas representing the objective function and constraint conditions of the optimization problem for the supply and demand system represented by the supply and demand system model, and the formula group generating unit A first-order predicate logical expression generation unit that generates a first-order predicate logical expression from the generated mathematical formula group, and the generated first-order predicate logical expression by the quantifier elimination method, A quantifier that obtains an expression representing the relationship between the total demand in the resource consumer facility and the total energy consumed in the resource supply facility, and a visualization unit that visualizes the relation obtained as a result of processing in the quantifier It is characterized by having.

  A second aspect of the present invention consumes energy for a resource supply facility for supplying resources, a resource consumer facility for demanding resources supplied from the resource supply facility, and a supply and demand system having a resource supply path. An energy management support program for causing an information processing device to execute energy management support processing for supporting operation of equipment, wherein the equipment represents a supply and demand system model of the supply and demand system, the resource supply equipment, and the equipment capacity of the supply path When capability information is input, a formula group consisting of a plurality of formulas representing an objective function and constraint conditions of an optimization problem for the supply and demand system represented by the supply and demand system model is generated based on the supply and demand system model and the equipment capability information Then, a first-order predicate logical expression is generated from the generated mathematical expression group, and the generated first-order predicate logical expression is processed by a quantifier elimination method. Obtaining a formula representing the relation between the total demand in the resource consumer equipment and the total energy consumption in the resource supply equipment, and visualizing the relational expression obtained as a result of processing in the limit symbol elimination unit, To do.

  A third aspect of the present invention is the total demand amount in the resource consumer facility and the total energy consumption in the resource supply facility obtained as a result of processing in the limit symbol elimination unit in the visualization unit of the energy management support apparatus. In addition to the visualization result of the expression that expresses the relationship between the total demand amount and the total energy consumption of the resource supply facility, the actual value at the time of operation is further displayed, and the ideal operation using the conventional optimal operation technology The calculated value at the time is further displayed.

  According to a fourth aspect of the present invention, in the first-order predicate logical expression generation unit and the quantifier elimination unit of the energy management support device, a partial total demand amount and a partial demand amount for some resources of the supply and demand system It is characterized by obtaining an expression representing the relationship with the total partial supply amount of resources.

  ADVANTAGE OF THE INVENTION According to this invention, the technique which can be utilized widely effectively when examining the efficient operation | use of a resource supply equipment is provided.

It is a figure explaining the outline | summary of the method of optimizing operation | use of a resource supply facility by an energy management assistance apparatus. It is a block diagram of the energy management assistance apparatus which concerns on 1st Embodiment. It is a figure which illustrates a supply-and-demand system model. It is a figure which illustrates the equipment capability information corresponding to the supply-and-demand system model of FIG. It is a figure which illustrates the numerical formula group which a numerical formula group production | generation part produces | generates in 1st Embodiment. It is a figure explaining the first order predicate logical expression which a first order predicate logical expression generation part generates in a 1st embodiment. It is a figure explaining the process of the first order predicate logic formula which a quantifier elimination part performs in 1st Embodiment. It is a figure which shows the example of the graph which a visualization part outputs in 1st Embodiment. It is a figure which shows the other example of a supply-and-demand system model. It is a figure which illustrates the equipment capability information corresponding to the supply-and-demand system model of FIG. It is a figure which illustrates the numerical formula group which a numerical formula group production | generation part produces | generates in 2nd Embodiment. It is a figure explaining the first order predicate logical expression which a first order predicate logical expression generation part generates in a 2nd embodiment. It is a figure explaining the process of the 1st-order predicate logical formula which the quantifier elimination part in 2nd Embodiment performs. It is a figure which shows the example of the graph output in a visualization part in 2nd Embodiment. It is a figure explaining the outline | summary of the method of optimizing operation | use of a resource supply equipment with an energy management assistance apparatus in 3rd Embodiment. It is a block diagram of the energy management assistance apparatus which concerns on 3rd Embodiment. It is a figure which shows the example of the graph output in a visualization part in 3rd Embodiment.

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

  FIG. 1 is a diagram for explaining an outline of a method for optimizing the operation of a supply facility for supplying resources by the energy management support apparatus according to the present invention. As shown in FIG. 1, the energy management support apparatus 1 includes a supply and demand system model M that represents how the supply and demand system is configured, and equipment capacity information C that represents the facility capacity of the supply facilities and supply paths in the supply and demand system. Thus, the relationship between the total demand amount of the customer facility that demands the resource and the total energy consumption amount of the supply facility is output and displayed as a graph. The user refers to the graph displayed and displayed to optimize the operation of the supply facility.

Hereinafter, the energy management support device 1 in FIG. 1 will be specifically described by taking as an example a case where optimization is aimed at a supply and demand system that supplies and supplies power as a resource.
<First Embodiment>
FIG. 2 is a configuration diagram of the energy management support apparatus 1 according to the present embodiment. The energy management support apparatus 1 shown in FIG. 2 includes a formula group generation unit 11, a first-order predicate logical expression generation unit 12, a quantifier elimination unit 13, and a visualization unit 14, and is based on information input from the input / output device 5. Then, a graph representing the relationship between the demand amount in the customer facility and the energy consumption in the supply facility is created and output to the input / output device 5.

  The energy management support apparatus 1 receives the supply / demand system model M and the facility capability information C of the supply system from the input / output device 5. First, with reference to FIG.3 and FIG.4, the information which the energy management assistance apparatus 1 receives from the input / output device 5 is demonstrated concretely.

  FIG. 3 is a diagram illustrating a supply and demand system model M. Here, the supply and demand system model M in the case where two power generation facilities are provided will be described.

  A user of the energy management support device 1 sets a supply and demand system model to be optimized through input means such as a keyboard and a pointing device of the input / output device 5. Specifically, the power generation amount in the power generation facility as the supply facility, the load amount in the load facility as the customer facility, the voltage phase of the bus directly connected to the power generation facility and the load facility, and the impedance of the line between the buses are set.

  In the example illustrated in FIG. 3, the power generation amount of the power generation facility 1 is P1 [MW], the power generation amount of the power generation facility 2 is P2 [MW], and the load amount of the load facility is L [MW]. The voltage phase of the bus 1 directly connected to the power generation facility 1 is θ1 [rad], the voltage phase of the bus 2 directly connected to the power generation facility 2 is θ2 [rad], and the voltage phase of the bus 3 directly connected to the load facility is θ3 [rad]. To do. The impedances of the buses 1 to 3, 2 to 3, and 1 to 2 are j0.1 [pu], respectively.

  The supply and demand system model M uses, for example, an XML (Extensible Markup Language) format, a specific configuration of the supply and demand system such as the number of installed power generation facilities and each physical quantity (P1, P2, θ1 to θ3, j0.1, etc.) Alternatively, the input / output device 5 may set the supply and demand system model M illustrated in FIG. 3 based on the input information. Or it is good also as a structure which a user draws the supply-and-demand system model M shown in FIG. 3 using software, such as Visio (trademark) and MATLAB (trademark).

  FIG. 4 is a diagram illustrating the facility capability information C of the supply system and the supply route. In FIG. 4, the facility capability information C corresponding to the supply and demand system model M of FIG. 3 is illustrated.

  The user of the energy management support device 1 sets the facility capability information C via the input means of the input / output device 5 as in the case of the supply and demand system model M. Specifically, as the equipment capability information C, an equation or an inequality that represents the supply capability of the supply facility and the supply path, which is necessary for determining the objective function and the constraint condition of the optimization problem, is set. In the embodiment, the facility capacity information C sets an expression representing the fuel cost of each power generation facility and the upper limit of the tidal current between the buses.

In the example shown in FIG. 4, the fuel cost C1 [$ / MWh] per hour of the power generation facility 1 is expressed by the following equation as a function of the power generation amount P1.
C1 (P1) = 0.01P1 ² + 14P1 + 100 (1)
Similarly, the fuel cost C2 [$ / MWh] per hour of the power generation facility 2 is expressed by the following equation as a function of the power generation amount P2.
C2 (P2) = 0.02P2 ² + 16P2 + 80 (2)
The upper limit of the tidal current between the bus 1 and the bus 3 in FIG. 3 is expressed by the following inequality.
(Θ1-θ3) /0.1≦240/P0 (3)
In the above inequality, P0 is the reference power in the supply system. From the condition that the power flow from the power generation facility 1 to the load facility (θ1−θ3) /0.1×P0 and the output distribution is performed so that this does not exceed the capacity 240 [MW] of the supply path, The inequality is obtained.

  For example, the facility capability information C allows the user to sequentially input the upper and lower limits of the supply of the power generation equipment that is the supply system, the energy consumption, and the upper and lower limits of the power flow of the bus that is the supply path. It is good also as a structure which stands | starts up the formula shown in FIG. 4 using required information. Or it can also be set as the structure which makes a user input the formula shown in FIG. 4 directly.

  In addition, in the Example, although the energy management assistance apparatus 1 is set as the structure which receives the supply-and-demand system model M of FIG. 3, and the facility capability information C of FIG. 4 from the input / output device 5, it is not limited to this. For example, the energy management support device 1 sets the supply / demand system model M and the facility capability information C itself, and only receives information necessary for setting the supply / demand system model M and the facility capability information C from the input / output device 5. It can also be configured.

  When the energy management support apparatus 1 receives the information illustrated in FIG. 3 or FIG. 4 from the input / output apparatus 5, the energy management support apparatus 1 sets the objective function and constraint conditions of the optimization problem based on the information, and from the set objective function and constraint conditions Generate a first order predicate formula. Then, by simplifying the generated first-order predicate logical expression by the quantifier elimination method, the total demand amount in the load facility (load amount L in the above example) and the total consumed energy in the power generation facility (in the above example, the fuel cost) And a graph is created. The created graph is output and displayed on the input / output device 5.

  The operation of each part of the energy management support apparatus 1 in FIG. 2 will be specifically described.

  The formula group generation unit 11 represents the objective function and the constraint condition of the optimization problem for the set supply and demand system model from the information input via the input / output device 5 as illustrated in FIGS. 3 and 4. Generate a mathematical expression group consisting of a plurality of mathematical expressions.

  FIG. 5 is a diagram illustrating a formula group generated by the formula group generation unit 11 in the present embodiment. Here, among the mathematical formula groups illustrated in FIG. 5, the mathematical formula group including the objective function of the optimization problem and the formula representing the definition is referred to as a “first mathematical formula group”, and the formula representing the constraint condition of the optimization problem is used. The following formula group will be described as a “second formula group”.

  First, the first mathematical formula group is a total value of the fuel costs of the power generation facilities 1 and 2 in FIG. 3, a function E (objective function Obj1) representing the total cost, and a variable C1 (P1) included in E , C2 (P2).

Since the objective function Obj1 is defined by the total fuel cost of the power generation facilities 1 and 2, it is expressed by the following equation.
Obj1: = E = C1 (P1) + C2 (P2)
Here, the objective function Obj1 is generated from the supply and demand system model M among the information input via the input / output device 5. In FIG. 5, the formula generated from the supply and demand system model M is shown with (*) mark.

The definitions of the variables C1 (P1) and C2 (P2) included in the objective function Obj1 are set from the equipment capability information C in FIG. 4 and are as in the above formulas (1) and (2).
C1 (P1 ) = 0.01P1 ² + 14P1 + 100
C2 (P2) = 0.02P2 ² + 16P2 + 80
Next, the second group of mathematical expressions represents the supply capacity for each of the two power generation facilities (power generation facilities 1 and 2) and the two supply paths (bus 1 to bus 3, bus 2 to bus 3) in FIG. It consists of a group of mathematical expressions to be defined. In the example shown in FIG. 5, it is comprised from the numerical formula group which defines the power generation capability of each power generation equipment, supply-and-demand balance, and a tidal current.

  The first to third constraint conditions Rst1 to Rst3 are derived from the fact that the sum of the currents flowing into each bus of the supply and demand system is zero according to Kirchhoff's first law. Specifically, Rst1 to Rst3 represent the sum of currents flowing into the buses 1 to 3, respectively, and are expressed as follows. 5, the first to third constraint conditions Rst1 to Rst3 are generated from the supply and demand system model M illustrated in FIG.

母線１と母線３との間の潮流上限より定まる制約条件Ｒｓｔ４については、先に図４を参照して説明した（３）式のとおりであり、上記の（３）式は、図４の設備能力情報Ｃの潮流上限による。

The constraint condition Rst4 determined from the upper limit of the tidal current between the bus 1 and the bus 3 is the same as the equation (3) described above with reference to FIG. 4, and the above equation (3) is the facility of FIG. According to the tidal upper limit of capability information C.

制約条件Ｒｓｔ５〜Ｒｓｔ７については、発電設備１、２の発電量及び負荷設備の負荷量が負でないことに基づき生成する。具体的には、入出力装置５から入力された変数Ｐ１、Ｐ２、Ｌを用いて、それぞれ以下の式を生成する。
Ｒｓｔ５：＝Ｐ１≧０
Ｒｓｔ６：＝Ｐ２≧０
Ｒｓｔ７：＝Ｌ≧０
基準電圧Ｐ０と母線３の条件を表す制約条件Ｃｎｔ１、Ｃｎｔ２には、それぞれ基準電圧、母線３の電圧位相を表す式を生成する。これらの制約条件についても、入出力装置５から入力された変数Ｐ０、θ３を用いて、以下の式を生成する。
Ｃｎｔ１：＝Ｐ０＝１０００
Ｃｎｔ２：＝θ３＝０
一階述語論理式生成部１２は、図５の第１及び第２の数式群を結合して、一階述語論理式を生成する。

The constraint conditions Rst5 to Rst7 are generated based on the fact that the power generation amount of the power generation facilities 1 and 2 and the load amount of the load facility are not negative. Specifically, using the variables P1, P2, and L input from the input / output device 5, the following equations are generated respectively.
Rst5: = P1 ≧ 0
Rst6: = P2 ≧ 0
Rst7: = L ≧ 0
For the constraint conditions Cnt1 and Cnt2 representing the conditions of the reference voltage P0 and the bus 3, formulas representing the reference voltage and the voltage phase of the bus 3 are generated, respectively. Also for these constraints, the following equations are generated using the variables P0 and θ3 input from the input / output device 5.
Cnt1: = P0 = 1000
Cnt2: = θ3 = 0
The first-order predicate logical expression generation unit 12 combines the first and second mathematical expression groups in FIG. 5 to generate a first-order predicate logical expression.

  FIG. 6 is a diagram illustrating the first-order predicate logical expression generated by the first-order predicate logical expression generation unit 12 in the present embodiment.

  As described above with reference to FIG. 5, the formula group generation unit 11 of the energy management support apparatus 1 is configured to supply and supply system model M input through the input / output device 5 and the facility capability information of the supply facility and the supply route. From C, first and second mathematical formula groups are generated. The first and second mathematical formula groups represent the objective function and constraint conditions of the optimization problem, respectively. The first-order predicate logical expression generation unit 12 enables operation of a supply system that satisfies the total demand amount (load amount L) of the load facility from the first and second mathematical expression groups representing the objective function and the constraint condition. A condition is derived, and thereby a relationship between L and the total energy consumption (total cost E) is obtained.

  Specifically, the first-order predicate logical expression generation unit 12 combines the first mathematical expression group representing the objective function and the second mathematical expression group representing the constraint condition by a logical product “∧”. Then, an existence symbol “∃” indicating that the variables P0, P1, P2, θ1, θ2, and θ3 indicating the state of the supply system exist is assigned. The expression (a) in FIG. 6 is a first-order predicate logical expression generated in this way.

  When the specific mathematical formula group of FIG. 5 generated by the mathematical formula group generation unit 11 is applied to the formula (a) and the appearance is arranged to improve the visibility, the first-order predicate logical formula φ is expressed by the formula (b). It is expressed in In formula (b), for convenience, the denominator is paid for each formula in the formula group in FIG.

  The limit symbol erasure unit 13 obtains an expression in which the limit symbol included in the logical expression generated by the first order predicate logical expression generation unit 12 is deleted. The formula processing method by the limit symbol erasing unit 13 will be specifically described with reference to FIG.

  FIG. 7 is a diagram for explaining processing of the first-order predicate logical expression performed by the quantifier elimination unit 13 in the present embodiment.

  The limit symbol erasing unit 13 deletes the limit symbol from the equation (b) in FIG. 6, and calculates the total demand amount, the load amount L in the above example, the total energy consumption amount, and the total cost E in the above example. Get the relational expression. Since the method of deleting the quantifier from the first-order predicate logical expression such as the expression (b) in FIG. 6 is a known technique, the details thereof are omitted here.

The obtained relational expression ans1 of L and E is as follows.
ans1: = 150 × E−L ² −2200 × L ≧ 0 and
((100 × E-L ² -1400 × L-18000 ≦ 0and
100 × E-9 × L ² + 5400 × L-1429200 ≦ 0and
L-100 ≧ 0and
L-412 ≦ 0or
50 × E-L2-800 × L-9000 ≦ 0and
L ≧ 0and
^{(100 × E-L 2 -1400} × L-18000 ≧ 0) or (L-100) ≧ 0) and
(100 × E-9 × L2 + 5400 × L-1429200 ≧ 0 or (L-412) ≦ 0))
The visualization unit 14 graphs the relationship between the total demand amount (load amount L) in the load facility and the total energy consumption (total cost E) in the power generation facility from the formula ans1 of FIG. 7 obtained by the limit symbol elimination unit 13. Then, the output means such as a monitor of the input / output device 5 is output and displayed. A known technique is used as a technique for drawing a graph from the formula ans1 of FIG.

  FIG. 8 is a diagram illustrating an example of a graph output from the visualization unit 14 to the input / output device 5 in the present embodiment. FIG. 8 illustrates a case where the mathematical formula of FIG. 7 obtained by solving the formula (b) of FIG. 6 is graphed. The horizontal axis is the load amount L [MW] of the load facility in FIG. 3, and the vertical axis is the total fuel cost E (P1, P2) [$ / MWh] of the power generation facilities 1 and 2 in FIG. is there.

  According to the graph shown in FIG. 8, for example, when the load amount L of the load facility exceeds about 700 [MW], it can be seen that the supply is impossible.

  Moreover, since the range of the load amount L of about 300 to 600 [MW] has a wide range of the total fuel cost, that is, the total cost E of the power generation equipment, it can be seen that there is a large room for optimization.

  Thus, according to the energy management support apparatus 1 according to the present embodiment, the first order predicate logical expression is generated from the objective function and the constraint condition of the optimization problem, and the quantifier is deleted from the generated logical expression, The relationship between the load amount L (total demand amount) of the load facility and the total fuel cost, that is, the total cost E (total energy consumption in the power generation facility) is output and displayed as a graph. The first-order predicate logical expression represents the state of the supply system by combining the first and second mathematical formula groups with a logical product so that a condition for enabling the operation of the supply system satisfying the load L is derived. Creates a variable with an existence symbol. Then, a relational expression between the load L and the total cost E obtained from the logical expression thus obtained is visualized as a graph. As a result, the user can not only optimize the supply and demand system having a supply system / supply path having a predetermined facility capacity, but also optimize (energy saving) by providing what kind of equipment. It becomes easy to consider whether it can be done.

  In the above description, a case in which the functions of all the configurations are provided in one information processing apparatus is illustrated, but the present invention is not limited to this. For example, it is also possible to adopt a configuration in which functions are distributed to a plurality of information processing devices, and the above-described processing is executed by an energy management support system including a plurality of information processing devices.

Moreover, it is good also as comprising by a program about the whole or one part of each part which comprises the energy management assistance apparatus 1 of FIG. When the configuration of the energy management support apparatus 1 includes a program, for example, a control program for executing the above method is stored in advance in a memory or the like of the information processing apparatus, and this is read by a control unit (not shown in FIG. 2). By performing this, the same actions and effects can be achieved.
<Second Embodiment>
In the above embodiment, in order to facilitate the examination of optimization in a certain supply and demand system, a first-order predicate logical expression is generated from the input supply and demand system model M and facility capacity information C, and this is used as a quantifier elimination method. The graph is output. On the other hand, in this embodiment, when the input information is changed, the load amount L of the load facility and the total energy consumption E (total cost) of the power generation facility are changed by changing the input information. It is different in that the change in the relationship between the two can be confirmed.

  Below, the detail of operation | movement of the energy management assistance apparatus 1 which concerns on this embodiment is demonstrated with reference to drawings. In addition, about the structure of the energy management assistance apparatus 1 which concerns on this embodiment, since it is the same as that of said embodiment and is as showing in FIG. 2, description is abbreviate | omitted here and it demonstrates focusing on a different point. To do.

  FIG. 9 is a diagram illustrating another example of the supply and demand system model M. As illustrated in FIG. As shown in FIG. 9, three power generation facilities are provided, and a supply facility and a supply route are added to the supply and demand system model of FIG.

  Specifically, the power generation facility 3 is added, the power generation amount is P3 [MW], the voltage phase of the bus 4 directly connected to the power generation facility 3 is θ4 [rad], and the impedance of the buses 3 to 4 is j0. 1 [pu].

  For example, let's examine the relationship between L and E when a user of the energy management support device 1 inputs a supply and demand system model M in FIG. 2 and confirms the graph in FIG. Suppose that. In such a case, the energy management support apparatus 1 temporarily stores the graph of FIG. 8 or the formula ans1 of FIG. 7 in a memory or the like, generates a formula group based on the changed information, Build a first-order predicate formula. Then, a graph is output from an expression obtained by processing the first order predicate logical expression by the quantifier elimination method, and can be compared with the graph of FIG.

  As shown in FIG. 9, when one power generation facility is added, it is necessary to change the facility capacity information C. This will be described with reference to FIG.

  FIG. 10 is a diagram illustrating facility capability information C corresponding to the supply and demand system model M of FIG.

  As shown in FIG. 10, with respect to the power generation facility 3 added in the supply and demand system model M, a mathematical formula defining the fuel cost C3 [$ / MWh] per hour of the power generation facility 3 and the bus 4 directly connected to the power generation facility 3 And a formula for determining the upper limit of the tidal current between the bus 3 directly connected to the load facility.

Specifically, the fuel cost C3 per hour of the power generation facility 3 is expressed by the following formula as a function of the power generation amount P3 of the power generation facility 3.
C3 (P3) = 0.01P3 ² + 18P3 + 60
Further, the upper limit of the tidal current between the bus 3 and the bus 4 is expressed by the following inequality.
(Θ4-θ3) /0.1≦240/P0
The other three equations are as described with reference to FIG.

  When the energy management support apparatus 1 receives the input of the supply and demand system model M in FIG. 9 and the facility capability information C in FIG. 10 from the input / output device 5, the energy management support apparatus 1 executes the same processing as in the above embodiment. That is, the objective function and constraint conditions of the optimization problem are set according to the input information, a first-order predicate logical expression is generated from the set objective function and constraint conditions, and this is processed by the quantifier elimination method. . Thereby, the relationship between the load amount L (total demand amount) in the load facility and the total cost E (total energy consumption) in the power generation facility is obtained, a graph is created, and output is displayed on the input / output device 5.

  FIG. 11 is a diagram illustrating a formula group generated by the formula group generation unit 11 in the present embodiment. Similarly to the above-described embodiment, a mathematical expression group consisting of an expression representing an objective function of an optimization problem and a definition related thereto, and a mathematical expression group consisting of an expression representing a constraint condition are defined as a first mathematical expression group and a second mathematical expression group, respectively.

First, for the first group of mathematical expressions, the total value of the fuel cost of the power generation facility is set as the total cost E, and this is set as the objective function Obj1 as in the above embodiment. The cost C3 (P3) of the added power generation facility 3 is added to the objective function Obj1.
Obj1 : = E = C1 (P1) + C2 (P2) + C3 (P3)
The generation of the objective function Obj1 from the supply and demand system model M in FIG. 9 is the same as in the above embodiment. Also in FIG. 11, formulas generated from the supply and demand system model M are indicated with (*) marks.

Of the variables C1 (P1), C2 (P2) and C3 (P3) included in the objective function Obj1, the definitions of C1 (P1) and C2 (P2) are the same as in the above embodiment. Here, the definition of C3 (P3) is added. Formulas representing these variables are set from the equipment capability information C.
C1 (P1 ) = 0.01P1 ² + 14P1 + 100
C2 (P2) = 0.02P2 ² + 16P2 + 80
C3 (P3) = 0.01P3 ² + 18P3 + 60
Of the twelve mathematical formulas Rst1 to Rst10 and Cnt1 to Cnt2 constituting the second mathematical formula group, the mathematical formulas changed with respect to the second mathematical formula group generated in the above embodiment are the constraint conditions Rst2 and Rst3. , Rst4, Rst6 and Rst9. The other mathematical expressions are the same as the mathematical expressions generated in the above-described embodiment of FIG.

  The second and fourth constraints Rst2 and Rst4 are derived from the fact that the sum of the currents flowing into the buses 2 and 4 is zero, respectively. In contrast to the above embodiment, since the power generation equipment 3 (and the bus 4 directly connected thereto) is added to the supply and demand system model M, the third term for the corresponding constraint conditions Rst2 and Rst3 in FIG. Has been added.

制約条件Ｒｓｔ３は、追加された発電設備３に直結する母線４に対して流れ込む電流の総和がゼロであることにより導出され、図５の数式群に対し、新たに追加される制約条件である。具体的には、以下のとおりに表される。

The constraint condition Rst3 is derived from the fact that the sum of the currents flowing into the bus 4 directly connected to the added power generation facility 3 is zero, and is a constraint condition newly added to the mathematical formula group of FIG. Specifically, it is expressed as follows.

制約条件Ｒｓｔ６は、図９の母線４と母線３との間の潮流上限により、以下の不等式で表される。なお、母線１と母線３との間の潮流上限による制約条件Ｒｓｔ５は、図５の第４の制約条件Ｒｓｔ４と同様である。

The constraint condition Rst6 is expressed by the following inequality by the upper limit of the tidal current between the bus 4 and the bus 3 in FIG. Note that the constraint condition Rst5 due to the upper limit of the flow between the bus 1 and the bus 3 is the same as the fourth constraint Rst4 in FIG.

制約条件Ｒｓｔ７、Ｒｓｔ８は、図５の第５及び第６の制約条件Ｒｓｔ５、Ｒｓｔ６とそれぞれ同様である。発電設備の発電量が負でないことによる条件式としては、制約条件Ｒｓｔ９が追加される。
Ｒｓｔ９：＝Ｐ３≧０
なお、負荷設備の負荷量が負でないことによる制約条件Ｒｓｔ１０は、図５の第７の制約条件Ｒｓｔ７と同様である。

The constraint conditions Rst7 and Rst8 are the same as the fifth and sixth constraint conditions Rst5 and Rst6 in FIG. A constraint condition Rst9 is added as a conditional expression for the fact that the power generation amount of the power generation facility is not negative.
Rst9: = P3 ≧ 0
Note that the constraint condition Rst10 due to the fact that the load amount of the load facility is not negative is the same as the seventh constraint condition Rst7 in FIG.

  The constraint conditions Cnt1 and Cnt2 representing the conditions of the reference voltage P0 and the bus 3 are the same as the constraint conditions Cnt1 and Cnt2 shown in FIG.

  The first-order predicate logical expression generation unit 12 of the energy management support apparatus 1 generates a first-order predicate logical expression from the mathematical formula group of FIG. 11 generated by the mathematical formula group generation unit 11.

  FIG. 12 is a diagram illustrating the first-order predicate logical expression generated by the first-order predicate logical expression generation unit 12 in the present embodiment.

  The first-order predicate logical expression generation unit 12 derives a condition that enables operation of the supply system so as to satisfy the load amount L of the load facility, from the first and second mathematical expression groups, similarly to the above-described embodiment. Thereby, the relationship between L and total energy consumption (total cost E) is obtained.

  Specifically, similarly to the above-described embodiment, the first mathematical expression group representing the objective function and the second mathematical expression group representing the constraint condition are combined with the logical product “∧” to represent the state of the supply system. An existence symbol “∃” indicating that a variable exists is assigned. The expression (c) in FIG. 12 is a first-order predicate logical expression generated in this way.

  When the specific mathematical expression group of FIG. 11 generated by the mathematical expression group generation unit 11 is applied to the expression (c) and the appearance is arranged to improve the visibility, the first-order predicate logical expression φ is expressed by the expression (d) It is expressed in Similar to the above embodiment, in the formula (d), for convenience, the denominator is paid for each of the formula group in FIG. .

  The limit symbol erasing unit 13 obtains a symbol from which the limit symbol included in the first-order predicate logical expression φ shown in FIG. 12 is deleted.

  FIG. 13 is a diagram for explaining the processing of the first-order predicate logical expression performed by the quantifier elimination unit 13 in the present embodiment.

  FIG. 13 shows an expression ans1 obtained by erasing the limit sign from the formula (d) in FIG. 12 using a known technique by the limit sign elimination method. Similarly to the above embodiment, by deleting the limit symbol, a relational expression between the load amount L of the load facility and the total cost E of the supply facility is obtained. The relational expression ans1 between L and E will be omitted here for the sake of simplicity.

  The visualization unit 14 obtains the relationship between the total demand amount (load amount L) in the load facility and the total energy consumption (total cost E) in the power generation facility from the formula in FIG. 13 obtained by the limit symbol elimination unit 13. And is output and displayed on an output means such as a monitor of the input / output device 5.

  FIG. 14 is a diagram illustrating an example of a graph output from the visualization unit 14 to the input / output device 5 in the present embodiment. The horizontal axis represents the load amount L [MW] of the load facility, and the vertical axis represents the total fuel cost E [$ / MWh] per hour of the power generation facility.

  According to the graph shown in FIG. 14, for example, the load amount L that can be supplied to the load facility by the power generation facility as the supply system is 700 [MW] in FIG. When added, it can be seen that it increases to 950 [MW].

  Further, in the range where the load amount L exceeds 500 [MW], the lower limit of the total cost E is lower than that in FIG. For example, when the load L is 600 [MW], the lower limit of the total cost E is 1400 [MW] in the case of two power generation facilities in FIG. 8, whereas the power generation facility in FIG. In the case of three units, it is 1200 [MW]. Thereby, it can be seen that in this range, the room for energy saving is increased, that is, it is possible to further reduce the total cost as compared with the case of two power generation facilities.

  Furthermore, in the range where the load L is in the vicinity of 600 [MW] to 700 [MW], the range of the total cost E is wider than that in FIG. Thus, it can be seen that in this range, the total cost can vary greatly compared to the case where there are two power generation facilities.

  As described above, the graph shown in FIG. 8 is temporarily held in a storage unit such as a memory, and the visualization unit 14 arranges the graph shown in FIG. It is good also as a structure output-displayed on a monitor etc. A means for making it easier for the user of the energy management support apparatus 1 to make a comparative study between the case where the power generation facility is composed of two units and the case where the power generation facility is composed of three units can be provided.

Thus, according to the energy management support device 1 according to the present embodiment, the relationship between the load amount (total demand amount) L of the load facility and the total fuel cost, that is, the total cost (total energy consumption in the power generation facility) E Display output as a graph. When there is a change (including addition, deletion, etc.) in the input / output system model M or the equipment capability information C, a graph corresponding to the newly input information is created and displayed. The previously created graph may be temporarily stored and compared with this. For users, as well as the conventional optimization of a supply and demand system, it is also considered how optimization (energy saving) can be achieved by changing the equipment. It becomes easy.
<Third Embodiment>
In the above embodiment, in a certain supply and demand system, a first-order predicate logical expression is generated from the input supply and demand system model M and the facility capability information C, and this is processed by the quantifier elimination method, so that the load amount of the load facility The graph showing the relationship between L and the total energy consumption E (total cost) of the power generation equipment is output. On the other hand, the present embodiment is different in that the actual operation value and the calculated value by the conventional optimum operation are further displayed.

  Below, the detail of operation | movement of the energy management assistance apparatus 1 which concerns on this embodiment is demonstrated with reference to drawings. The details of the operation of the same parts as those in the above embodiment are the same as those in the above embodiment, and therefore different points will be mainly described.

  FIG. 15 is a diagram illustrating an outline of a method for optimizing the operation of a supply facility for supplying resources by the energy management support apparatus according to the present invention. In addition to FIG. 1, data representing the operation result value and the calculated value by the conventional optimum operation is input to the energy management support apparatus.

  FIG. 16 is a configuration diagram of the energy management support apparatus 1 according to the present embodiment. In FIG. 16, in addition to the energy management support apparatus 1 shown in FIG. 2, a measuring apparatus 20 and an optimum operation apparatus 21 are shown. Based on the result information input from the measuring device 20 and the calculated value input from the optimum operation device 21, the input / output device 5 outputs the operation result value / calculated value D to the energy management support device 1.

  FIG. 17 is a diagram illustrating an example of a graph output from the visualization unit 14 to the input / output device 5 in the present embodiment. The relationship between the load amount (total demand amount) L of the load facility and the total fuel cost, that is, the total cost (total energy consumption in the power generation facility) E is output as a graph. In addition to the graph representing the output area as in the above embodiment, the operation result value / calculated value D data input from the input / output device 5 are plotted in an overlapping manner. The operation result value is plotted with a circle and the calculated value is plotted with a cross mark. Since the calculated value is lower than the operation result value at the same load amount L, it can be said that optimization (energy saving) is achieved.

  However, there is almost no difference between the actual value and the calculated value when the load amount L is around 400 [MW], and the difference between the actual value and the calculated value tends to increase as the load amount L increases.

  In the conventional optimum operation technology, it has not been possible to rationally explain that the effect of optimization (energy saving) differs depending on the load L.

  On the other hand, in FIG. 17, the relationship between the load amount (total demand amount) L of the load facility and the total fuel cost, that is, the total cost (total energy consumption in the power generation facility) E is shown as an area, and the operation result value and the calculated value are also shown. Are displayed in a superimposed manner, not because there is a defect in the conventional optimum operation technology, but because of the operation limit of the supply and demand system, there is almost no difference between the actual value and the calculated value when the load amount L is around 400 [MW]. I understand that.

  As described above, in the energy management support apparatus 1 according to the present embodiment, the current operation results and the calculated value when optimization (energy saving) is achieved by the conventional optimum operation technology are compared with the theoretically possible area. Based on this, it becomes easy to evaluate the validity of the optimization (energy saving) effect.

  Therefore, the energy management support apparatus 1 according to the present embodiment compares the current operation results with theoretically possible areas before operating the optimum operation apparatus, and determines in advance whether there is room for improvement for energy saving. By examining it, it is possible to support a user who determines whether or not to introduce the optimum operation technology.

Furthermore, the energy management support apparatus 1 according to the present embodiment shows how good the ideal operation obtained by the conventional optimum operation technology is after the operation of the optimum operation device compared to the conventional operation. When evaluating, it is possible to assist the user by identifying whether the conventional optimum operation technique is deficient or due to the operation limit of the supply and demand system.
<Fourth Embodiment>
In the above, the total demand and total supply of resources in the supply and demand system were visualized, but the partial total demand for some resources in the supply and demand system and the partial supply for some resources. An expression expressing the relationship with the total supply amount can also be obtained. For example, in FIG. 9, when it is assumed in advance that the operation of a specific one of the three supply facilities is set to a fixed value, the above-mentioned implementation is performed for the remaining two units. As in the example, visualization can be performed by generating a first-order predicate logical expression and applying the quantifier elimination method. Specifically, in the equipment capacity information C, a constraint condition that the supply amount of a specific facility is a fixed value is provided, and a variable indicating the total supply amount of the remaining two units is set as the total cost E. .

  Since other details are the same as those in the above embodiment, the description thereof is omitted here.

  In the above, the case where the energy management support apparatus 1 performs visualization for optimization of the supply system that supplies power is described, but the present invention is not limited to this. For example, the above-described method can be applied to a supply system that supplies resources such as hot and cold heat, steam, and gas.

  The present invention is not limited to the above-described embodiment as it is, and can be embodied by modifying the constituent elements without departing from the scope of the invention in the implementation stage. Moreover, various inventions can be formed by appropriately combining a plurality of constituent elements disclosed in the embodiment. For example, all the constituent elements shown in the embodiments may be appropriately combined. Furthermore, constituent elements over different embodiments may be appropriately combined. It goes without saying that various modifications and applications are possible without departing from the spirit of the invention.

DESCRIPTION OF SYMBOLS 1 Energy management support apparatus 5 Input / output device 11 Formula group generation part 12 First-order predicate logic expression generation part 13 Limit symbol elimination part 14 Visualization part 20 Measurement apparatus 21 Optimal operation apparatus

Claims (8)

Energy management support that supports the operation of energy consuming facilities for resource supply facilities that supply resources, resource consumer facilities that demand resources supplied from the resource supply facilities, and supply and demand systems that have resource supply paths A device,
When the supply and demand system model of the supply and demand system and the facility capacity information indicating the facility capacity of the resource supply facility and the supply path are input, the supply and demand represented by the supply and demand system model based on the supply and demand system model and the facility capacity information A formula group generation unit that generates a formula group composed of a plurality of formulas representing the objective function and constraint conditions of the optimization problem for the system;
A first order predicate logical expression generation unit that generates a first order predicate logical expression from the mathematical expression group generated in the mathematical expression group generation unit;
More quantifier elimination method, by processing the first-order logic formulas described above generated, the resource consumer quantifier elimination unit to obtain an expression representing the relation between the total energy consumption in the resource supply facility to the total demand in the facility When,
A visualization unit that visualizes a relational expression obtained as a result of processing in the limit symbol elimination unit;
An energy management support device characterized by comprising: The formula group generation unit generates a first formula group that expresses a relationship between a resource supply amount of the resource supply facility and an energy consumption amount in the resource supply facility as the objective function, and the resource Generating a second set of mathematical expressions expressing the supply capacity of the supply facility and the supply path;
The first-order predicate logical expression generation unit combines the first and second mathematical formula groups with a logical product, and represents the state of the resource supply facility and the supply path included in the first and second mathematical formula groups. The energy management support apparatus according to claim 1, wherein the first-order predicate logical expression is generated by adding an existence symbol indicating that a variable exists. When further receiving the change of the supply and demand system model and the equipment capacity information, the formula group generation unit, the first-order predicate logical expression generation unit, the limit symbol elimination unit and the visualization unit, the changed supply and demand system model and 3. The energy management support apparatus according to claim 1, wherein the processing is executed using equipment capacity information, and a result corresponding to the changed supply and demand system model and equipment capacity information is output. When further receiving changes in the supply and demand system model and the equipment capacity information, a storage unit that temporarily holds the relational expression obtained in the limit symbol elimination unit or the graph created in the visualization unit;
Further comprising
The said visualization part outputs and displays the graph based on the said changed supply-and-demand system model and equipment capability information, and the graph before a change using the information hold | maintained at the said memory | storage part. The energy management support device described. The visualization unit further displays result data obtained by measuring the total demand amount in the resource consumer facility and the total energy consumption in the resource supply facility, in addition to the visualization result of the relational expression obtained as a result of processing in the limit symbol elimination unit The energy management support device according to any one of claims 1 to 4, wherein In addition to the visualization result of the relational expression obtained as a result of processing in the quantifier elimination unit, the visualization unit calculates the optimal demand calculated by the optimal operation device for the total demand amount in the resource consumer facility and the total energy consumption in the resource supply facility The energy management support device according to claim 1, further displaying a calculated value during operation. The formula group generation unit generates the formula group using information about a part of resources of the supply and demand system,
The quantifier elimination unit obtains an expression representing a relationship between a partial demand amount for a part of resources in the supply and demand system and a partial supply amount for a part of resources. Item 1. An energy management support device according to item 1. Energy management support that supports the operation of energy consuming facilities for resource supply facilities that supply resources, resource consumer facilities that demand resources supplied from the resource supply facilities, and supply and demand systems that have resource supply paths An energy management support program for causing an information processing apparatus to execute processing,
When the supply and demand system model of the supply and demand system and the facility capacity information indicating the facility capacity of the resource supply facility and the supply path are input, the supply and demand represented by the supply and demand system model based on the supply and demand system model and the facility capacity information Generate a formula group consisting of a plurality of formulas representing the objective function and constraints of the optimization problem for the system,
Generate a first-order predicate logical expression from the generated mathematical expression group,
More quantifier elimination method, by processing the first-order logic formulas described above produce, give an expression representing the relation between the total energy consumption in the total demand with the resource supply facilities in the resource consumer equipment,
Visualizing the relational expression obtained as a result of processing by the quantifier elimination method ,
An energy management support program characterized by this.

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