OPTIMAL CALCULATION METHOD OF ENERGY OPERATING CONDITION IN IRON MILL, OPTIMAL CALCULATION DEVICE OF ENERGY OPERATING CONDITION IN IRON MILL, AND RUNNING METHOD OF IRON MILL

Abstract

An optimal calculation method of an energy operating condition in an iron mill includes calculating, using a total energy operation cost of the iron mill within a predetermined period of time from a current time as an evaluation function, an operation condition of an energy facility in the iron mill as a decision variable such that a value of the evaluation function decreases, at each predetermined time within the predetermined period of time, based on actual values and estimated values of a generation amount and a used amount of energy utility for each of factories comprised in the iron mill. The method includes a step of calculating the decision variable by imposing an equality constraint such that the decision variable related to a power generation facility included in the energy facility is constant within a predetermined aggregation time.

Claims

1. An optimal calculation method of an energy operating condition in an iron mill, the optimal calculation method comprising: calculating, using a total energy operation cost of the iron mill within a predetermined period of time from a current time as an evaluation function, an operation condition of an energy facility in the iron mill as a decision variable such that a value of the evaluation function decreases, at each predetermined time within the predetermined period of time, based on actual values and estimated values of a generation amount and a used amount of energy utility for each of factories comprised in the iron mill, wherein the method comprises a step of calculating the decision variable by imposing an equality constraint such that the decision variable related to a power generation facility included in the energy facility is constant within a predetermined aggregation time.

2. The optimal calculation method of an energy operating condition in an iron mill according to claim 1, wherein the energy utility for each of the factories includes gas, steam, and electric power.

3. The optimal calculation method of an energy operating condition in an iron mill according to claim 1, wherein the energy facility includes a mixed gas production facility, a gas holder, a coke drying quenching facility, a top-pressure recovery turbine facility, and a power generation facility that uses by-product gas, heavy oil, or steam extraction.

4. The optimal calculation method of an energy operating condition in an iron mill according to claim 1, wherein the total energy operation cost includes a cost associated with use of heavy oil, city gas, and steam and a cost associated with purchase of electricity.

5. An optimal calculation device of an energy operating condition in an iron mill for calculating, using a total energy operation cost of the iron mill within a predetermined period of time from a current time as an evaluation function, an operation condition of an energy facility in the iron mill as a decision variable such that a value of the evaluation function decreases, at each predetermined time within the predetermined period of time, based on actual values and estimated values of a generation amount and a used amount of energy utility for each of factories comprised in the iron mill, the device comprising: a calculator configured to calculate the decision variable by imposing an equality constraint so that the decision variable related to a power generation facility included in the energy facility is constant within a predetermined aggregation time.

6. An operating method of an iron mill, the method comprising a step of operating the iron mill based on the decision variable calculated by the optimal calculation method of an energy operating condition in an iron mill according to claim 1.

7. The optimal calculation method of an energy operating condition in an iron mill according to claim 2, wherein the energy facility includes a mixed gas production facility, a gas holder, a coke drying quenching facility, a top-pressure recovery turbine facility, and a power generation facility that uses by-product gas, heavy oil, or steam extraction.

8. The optimal calculation method of an energy operating condition in an iron mill according to claim 2, wherein the total energy operation cost includes a cost associated with use of heavy oil, city gas, and steam and a cost associated with purchase of electricity.

9. The optimal calculation method of an energy operating condition in an iron mill according to claim 3, wherein the total energy operation cost includes a cost associated with use of heavy oil, city gas, and steam and a cost associated with purchase of electricity.

10. The optimal calculation method of an energy operating condition in an iron mill according to claim 7, wherein the total energy operation cost includes a cost associated with use of heavy oil, city gas, and steam and a cost associated with purchase of electricity.

Description

BRIEF DESCRIPTION OF DRAWINGS

[0020] FIG. 1 is a block diagram illustrating a configuration of an optimal calculation device of the energy operating condition in an iron mill as an embodiment of the present invention.

[0021] FIG. 2 is a flowchart illustrating a flow of optimal calculation processing as an embodiment of the present invention.

[0022] FIG. 3 is a diagram for explaining the aggregation constraint condition for decision variables.

[0023] FIG. 4 is a graph illustrating changes in cost in an example of the present invention and a comparative example.

[0024] FIG. 5 is a graph illustrating changes in electric power generation in the example of the present invention and the comparative example.

DESCRIPTION OF EMBODIMENTS

[0025] Hereinafter, an optimal calculation device of the energy operating condition in an iron mill as an embodiment of the present invention will be described with reference to the drawings.

[0026] [Configuration]

[0027] First, with reference to FIG. 1, a configuration of the optimal calculation device of the energy operating condition in an iron mill as an embodiment of the present invention will be described.

[0028] FIG. 1 is a block diagram illustrating the configuration of the optimal calculation device of the energy operating condition in an iron mill according to the embodiment of the present invention. As illustrated in FIG. 1, the optimal calculation device of the energy operating condition in an iron mill as an embodiment of the present invention includes an information processing device 1 such as a workstation. The optimal calculation device of the energy operating condition in an iron mill as an embodiment of the present invention functions as an information acquisition unit 11 and an optimal calculation unit 12 when an arithmetic processing device inside the information processing device 1 executes a computer program. The functions of these units will be described later.

[0029] The optimal calculation device having such a configuration shortens the time required for optimal calculation of the energy operating condition in an iron mill by executing the following optimal calculation processing. Hereinafter, the operation of the optimal calculation device when executing the optimal calculation processing will be described with reference to FIGS. 2 and 3.

[0030] [Optimal Calculation Processing]

[0031] FIG. 2 is a flowchart illustrating a flow of the optimal calculation processing as an embodiment of the present invention. The flowchart illustrated in FIG. 2 starts at timing when an execution command of the optimal calculation processing is input to the information processing device 1, and the optimal calculation processing proceeds to the processing of step S1.

[0032] In the processing of step S1, the information acquisition unit 11 acquires data of actual values and estimated values of the generation amount and the consumption amount of energy utility of a factory in the iron mill at the current time (t=0) as input data of the optimal calculation processing. Specifically, as illustrated in Table 1 below, the information acquisition unit 11 acquires data of actual values S.sub.B(0), S.sub.C(0), S.sub.L(0), and S.sub.St(0) and estimated values S.sub.B(k), S.sub.C(k), S.sub.L(k), and S.sub.St(k) (k=1 to N) of the generation amounts of the B gas, the C gas, the LD gas, and the steam as data of the actual values and the estimated values of the generation amount of the energy utility at the current time. In addition, as illustrated in Table 2 below, the information acquisition unit 11 acquires data of actual values D.sub.B(0), D.sub.C(0), D.sub.L(0), D.sub.M(0), D.sub.St(0), and D.sub.E(0) and estimated values D.sub.B(k), D.sub.C(k), D.sub.L(k), D.sub.M(k), D.sub.St(k), and D.sub.E(k) (k=1 to N) of consumption amounts of the B gas, the C gas, the LD gas, the M gas, the steam, and the power as the data of actual values and estimated values of consumption amounts of energy utility at the current time. Each of the estimated values is obtained by estimating the generation amount and the used amount of the energy utility of each factory on the basis of the production plan of each factory in the iron mill. The production plan includes a long-term plan of about one week in addition to a short-term plans of several hours and one to two days from the present point of time, and the accuracy becomes higher for the short-term production plans. Therefore, estimated values obtained using the production plans also have a similar tendency of accuracy. With the above, the processing of step S1 is completed, and the optimal calculation processing proceeds to the processing of step S2.

TABLE-US-00001 TABLE 1 Actual Value (Current Estimated Value Item Time) k = 1 k = 2 . . . k = N B Gas Generation S.sub.B(0) S.sub.B(1) S.sub.B(2) . . . S.sub.B(N) Amount (Blast Furnace Total Value) C Gas Generation S.sub.C(0) S.sub.C(1) S.sub.C(2) . . . S.sub.C(N) Amount (Coke Oven Total Value) LD Gas Generation S.sub.L(0) S.sub.L(1) S.sub.L(2) . . . S.sub.L(N) Amount (Converter Total Value) Steam Generation S.sub.St(0) S.sub.St(1) S.sub.St(2) . . . S.sub.St(N) Amount (Factory Total Value)

TABLE-US-00002 TABLE 2 Actual Value (Current Estimated Value Item Time) k = 1 k = 2 . . . k = N B Gas Consumption D.sub.B(0) D.sub.B(1) D.sub.B(2) . . . D.sub.B(N) Amount (Factory Total Value) C Gas Consumption D.sub.C(0) D.sub.C(1) D.sub.C(2) . . . D.sub.C(N) Amount (Factory Total Value) LD Gas D.sub.L(0) D.sub.L(1) D.sub.L(2) . . . D.sub.L(N) Consumption Amount (Factory Total Value) M Gas Consumption D.sub.M(0) D.sub.M(1) D.sub.M(2) . . . D.sub.M(N) Amount (Factory Total Value) Steam Consumption D.sub.St(0) D.sub.St(1) D.sub.St(2) . . . D.sub.St(N) Amount (Factory Total Value) Electric Power D.sub.E(0) D.sub.E(1) D.sub.E(2) . . . D.sub.E(N) Consumption Amount (Factory Total Value)

[0033] In the processing of step S2, as illustrated in Table 3 below, the information acquisition unit 11 acquires data of actual values S.sub.StCDQ(0) and S.sub.ETRT(0) and estimated values S.sub.StCDQ(k) and S.sub.ETRT(k) (k=1 to N) of the CDQ boiler steam amount and the TRT power generation amount at the current time as input data for the optimal calculation processing. As a result, the processing of step S2 is completed, and the optimal calculation processing proceeds to the processing of step S3.

TABLE-US-00003 TABLE 3 Actual Value (Current Estimated Value Item Time) k = 1 k = 2 . . . k = N CDQ Boiler S.sub.StCDQ(0) S.sub.StCDQ(1) S.sub.StCDQ(2) . . . S.sub.StCDQ(N) Steam (All Units) TRT Power S.sub.ETRT(0) S.sub.ETRT(1) S.sub.ETRT(2) . . . S.sub.ETRT(N) Generation Amount (All Units)

[0034] In the processing of step S3, the information acquisition unit 11 acquires data of actual values of the amount of fuel used in all the power generation facilities in the iron mill at the current time. Specifically, in general, the M gas obtained by mixing by-product gases and adjusting the heat quantity is used in addition to the B gas, the C gas, and the LD gas as fuel in an iron mill. In addition, when a predetermined power generation amount cannot be ensured, using heavy oil or steam extraction from a CDQ turbine may be performed. Therefore, as illustrated in Table 4 below, the information acquisition unit 11 acquires data of actual values D.sub.BxU(0), D.sub.CxU(0), D.sub.LxU(0), D.sub.MxU(0), D.sub.OxU(0), S.sub.StxU(0) (x represents the identification number of a power generation facility) of amounts of the B gas, the C gas, the LD gas, the M gas, heavy oil, and extracted steam used in all power generation facilities in the iron mill at the current time. As a result, the processing of step S3 is completed, and the optimal calculation processing proceeds to the processing of step S4.

TABLE-US-00004 TABLE 4 Extracted Unit Heavy Steam Number B Gas C Gas LD gas M Gas Oil Amount Unit 1 D.sub.B1U (0) D.sub.C1U (0) D.sub.L1U (0) D.sub.M1U (0) D.sub.O1U (0) D.sub.St1U (0) Unit 2 D.sub.B2U (0) D.sub.C2U (0) D.sub.L2U (0) D.sub.M2U (0) D.sub.O2U (0) D.sub.St2U (0) . . . . . . . . . . . . . . . . . . . . . Unit x D.sub.BxU (0) D.sub.CxU (0) D.sub.LxU (0) D.sub.MxU (0) D.sub.OxU (0) D.sub.StxU (0)

[0035] In the processing of step S4, as illustrated in Table 5 below, the information acquisition unit 11 acquires data of actual values D.sub.BPow(0), D.sub.CPow(0), D.sub.LPow(0), and D.sub.TPow(0) of the amounts of the B gas, the C gas, the LD gas, and the city gas at the current time in a mixed gas manufacturing facility that supplies the M gas to the power generation facilities in the iron mill. In addition, as illustrated in Table 5 below, the information acquisition unit 11 acquires data of actual values D.sub.BMill(0), D.sub.CMill(0), D.sub.LMill(0), and D.sub.TMill(0) of the amounts of the B gas, the C gas, the LD gas, and the city gas at the current time in the mixed gas manufacturing facility that supplies the M gas to the factories in the iron mill. With the above, the processing of step S4 is completed, and the optimal calculation processing proceeds to the processing of step S5.

TABLE-US-00005 TABLE 5 Item B Gas C Gas LD Gas City Gas M Gas for Power D.sub.BPow(0) D.sub.CPow(0) D.sub.LPow(0) D.sub.TPow(0) Generation Facilities M Gas for Factories D.sub.BMill(0) D.sub.CMill(0) D.sub.LMill(0) D.sub.TMill(0)

[0036] In the processing of step S5, as illustrated in Table 6 below, the information acquisition unit 11 acquires data of gas storage amounts H.sub.BLevel(0), H.sub.CLevel(0), and H.sub.LLevel(0) and actual values H.sub.B(0), H.sub.C(0), and H.sub.L (0) of the intake amount and discharge amount of gas holders for the B gas, the C gas, and the LD gas at the current time. With the above, the processing of step S5 is completed, and the optimal calculation processing proceeds to the processing of step S6.

TABLE-US-00006 TABLE 6 Actual Intake and Item Storage Amount Discharge B Gas Holder H.sub.BLevel(0) H.sub.B(0) C Gas Holder H.sub.CLevel(0) H.sub.C(0) LD Gas Holder H.sub.LLevel(0) H.sub.L(0)

[0037] In the processing of step S6, the information acquisition unit 11 acquires data of a unit price set value necessary for calculating the cost for energy operation of the iron mill. Specifically, as illustrated in Table 7 below, the information acquisition unit 11 acquires data of actual values C.sub.Ele (0), C.sub.St(0), C.sub.O(0), and C.sub.T(0) and future contract values C.sub.Ele(k), C.sub.St(k), C.sub.O(k), and C.sub.T(k) (k=1 to N) of unit prices of the electric power, steam, heavy oil, and city gas at the current time. With the above, the processing of step S6 is completed, and the optimal calculation processing proceeds to the processing of step S7.

TABLE-US-00007 TABLE 7 Actual Value (Current Contract Value Item Time) k = 1 k = 2 . . . k = N Unit Price of C.sub.Ele(0) C.sub.Ele(1) C.sub.Ele(2) . . . C.sub.Ele(N) Electric Power (Yen/kWh) Unit Price of C.sub.St(0) C.sub.St(1) C.sub.St(2) . . . C.sub.St(N) Steam (Yen/ton) Unit Price of C.sub.O(0) C.sub.O(1) C.sub.O(2) . . . C.sub.O(N) Heavy Oil (Yen/GJ) Unit Price of C.sub.T(0) C.sub.T(1) C.sub.T(2) . . . C.sub.T(N) City Gas (Yen/GJ)

[0038] In the processing of step S7, the optimal calculation unit 12 uses the data acquired in the processing of steps S1 to S6 and executes the optimal calculation for obtaining the condition for minimizing the cost for the energy operation of the iron mill in a predetermined period (k=1 to N) from the current time. Specifically, the decision variables (variables searched in order to minimize the cost) in the optimal calculation are the amounts of the B gas, the C gas, the LD gas, the M gas, the heavy oil, and the steam extraction used in the power generation facilities illustrated in Table 8 below, the amounts of the B gas, the C gas, the LD gas, and the city gas in the mixed gas manufacturing facility D.sub.BPow(k), D.sub.CPow(k), D.sub.LPow(k), D.sub.TPow(k), D.sub.BMill(k), D.sub.CMill(k), D.sub.LMill(k), and D.sub.TMill(k) illustrated in Table 9 below, the gas storage amounts H.sub.BLevel(k), H.sub.CLevel(k), H.sub.LLevel(k) and the intake amounts and the discharge amounts H.sub.B(k), H.sub.C(k), H.sub.L(k) of the gas holders illustrated in Table 10, the amount of power purchased S.sub.EPurchase(k), the amount of steam extraction S.sub.StExtCDQ(k) from the CDQ turbine, and the amount of steam purchased S.sub.StPurchase(k)

TABLE-US-00008 TABLE 8 Extracted Unit Heavy Steam Number B Gas C Gas LD Gas M Gas Oil Amount Unit 1 D.sub.B1U (k) D.sub.C1U (k) D.sub.L1U (k) D.sub.M1U (k) D.sub.O1U (k) D.sub.St1U (k) Unit 2 D.sub.B2U (k) D.sub.C2U (k) D.sub.L2U (k) D.sub.M2U (k) D.sub.O2U (k) D.sub.St2U (k) . . . . . . . . . . . . . . . . . . . . . Unit x D.sub.BxU (k) D.sub.CxU (k) D.sub.LxU (k) D.sub.MxU (k) D.sub.OxU (k) D.sub.StxU (k)

TABLE-US-00009 TABLE 9 Item B Gas C Gas LD Gas City Gas M Gas for Power D.sub.BPow(k) D.sub.CPow(k) D.sub.LPow(k) D.sub.TPow(k) Generation Facilities M Gas for Factories D.sub.BMill(k) D.sub.CMill(k) D.sub.LMill(k) D.sub.TMill(k)

TABLE-US-00010 TABLE 10 Intake and Item Storage Amount Discharge Amount B Gas Holder H.sub.BLevel(k) H.sub.B(k) C Gas Holder H.sub.CLevel(k) H.sub.C(k) LD Gas Holder H.sub.LLevel(k) H.sub.L(k)

[0039] Meanwhile, the cost to be minimized is the sum of heavy oil as a supplemental fuel, city gas, steam, and the amount of power purchased. Each unit price is as illustrated in Table 7, and a total value f of the cost from the current time to N periods ahead is described using the unit prices as expressed in the following formula (1). In addition, the following constraint conditions (a) to (1) are set at the time of the optimal calculation. With the above, the processing of step S7 is completed, and a series of steps of the optimal calculation processing ends.

f=Σ.sub.k=1.sup.N(C.sub.Ele(k)S.sub.EPurchase(k)+C.sub.St(k)S.sub.StPurchase(k)+C.sub.O(k)Σ.sub.j=1.sup.xD.sub.OjU(k)+C.sub.T(k)(D.sub.TPow(k)+D.sub.TMill(k)))  (1)

[0040] (a) B Gas Balance Constraint

[00001]$\begin{array}{cc}{S}_B\left(k\right)=D_B\left(k\right)+\underset{\mathrm{For}M\mathrm{gas}}{\underset{\_}{D_{\mathrm{BPow}}\left(k\right)+D_{\mathrm{BMill}}\left(k\right)}}+\underset{\begin{array}{c}\mathrm{for}\mathrm{power}\\ \mathrm{generation}\mathrm{facility}\end{array}}{\underset{\_}{\underset{j=1}{\overset{x}{.Math.}}{D}_{\mathrm{BjU}}\left(k\right)}}+\underset{\begin{array}{c}\mathrm{intake}\mathrm{amount}\\ \mathrm{of}\mathrm{gas}\mathrm{hold}\end{array}}{\underset{\_}{H_B\left(k\right)}}& \left(2\right)\end{array}$

[0041] (b) C Gas Balance Constraint

[00002]$\begin{array}{cc}{S}_C\left(k\right)=D_C\left(k\right)+\underset{\mathrm{For}M\mathrm{gas}}{\underset{\_}{D_{\mathrm{CPow}}\left(k\right)+D_{\mathrm{CMill}}\left(k\right)}}+\underset{\begin{array}{c}\mathrm{for}\mathrm{power}\\ \mathrm{generation}\mathrm{facility}\end{array}}{\underset{\_}{\underset{j=1}{\overset{x}{.Math.}}{D}_{\mathrm{CjU}}\left(k\right)}}+\underset{\begin{array}{c}\mathrm{intake}\mathrm{amount}\\ \mathrm{of}\mathrm{gas}\mathrm{holder}\end{array}}{\underset{\_}{H_C\left(k\right)}}& \left(3\right)\end{array}$

[0042] (c) LD Gas Balance Constraint

[00003]$\begin{array}{cc}{S}_L\left(k\right)=D_L\left(k\right)+\underset{\mathrm{For}M\mathrm{gas}}{\underset{\_}{D_{\mathrm{LPow}}\left(k\right)+D_{\mathrm{LMill}}\left(k\right)}}+\underset{\begin{array}{c}\mathrm{for}\mathrm{power}\\ \mathrm{generation}\mathrm{facility}\end{array}}{\underset{\_}{\underset{j=1}{\overset{x}{.Math.}}{D}_{\mathrm{LjU}}\left(k\right)}}+\underset{\begin{array}{c}\mathrm{intake}\mathrm{amount}\\ \mathrm{of}\mathrm{gas}\mathrm{holder}\end{array}}{\underset{\_}{H_L\left(k\right)}}& \left(4\right)\end{array}$

[0043] (d) Factory M Gas Balance Constraint

D.sub.M(k)=D.sub.BMill(k)+D.sub.CMill(k)+D.sub.LMill(k)+D.sub.TMill(k)  (5)

[0044] (e) Power Generation Facility M Gas Balance Constraint

[00004]$\begin{array}{cc}\underset{J=1}{\overset{x}{.Math.}}{D}_{\mathrm{MjU}}\left(k\right)=D_{\mathrm{BPow}}\left(k\right)+D_{CPow}\left(k\right)+D_{\mathrm{LPow}}\left(k\right)+D_{TPow}\left(k\right)& \left(6\right)\end{array}$

[0045] (f) Gas Holder Storage Amount

H.sub.BLevel(k)=H.sub.BLevel(k−1)+H.sub.B(k)T  (7-1)

H.sub.CLevel(k)=H.sub.CLevel(k−1)+H.sub.C(k)T  (7-2)

H.sub.LLevel(k)=H.sub.LLevel(k−1)+H.sub.L(k)T  (7-3)

[0046] Where T represents a fixed time interval.

[0047] (g) Power Generation Facility Model

[00005]$\begin{array}{cc}{S}_{E1U}\left(k\right)=f_1\left(D_{B1U}\left(k\right)+D_{C1U}\left(k\right)+D_{L1U}\left(k\right)+D_{M1U}\left(k\right)+D_{O1U}\left(k\right),S_{\mathrm{St}1U}\left(k\right)\right)& \left(8-1\right)\end{array}$$\begin{array}{cc}{S}_{E2U}\left(k\right)=f_2\left(D_{B2U}\left(k\right)+D_{C2U}\left(k\right)+D_{L2U}\left(k\right)+D_{M2U}\left(k\right)+D_{O2U}\left(k\right),S_{\mathrm{St}2U}\left(k\right)\right)& \left(8-2\right)\end{array}$$.Math.$$\begin{array}{cc}{S}_{\mathrm{ExU}}\left(k\right)=f_x\left(D_{BxU}\left(k\right)+D_{CxU}\left(k\right)+D_{LxU}\left(k\right)+D_{\mathrm{MxU}}\left(k\right)+D_{\mathrm{OxU}}\left(k\right),S_{\mathrm{StxU}}\left(k\right)\right)& \left(8-x\right)\end{array}$

[0048] Where f.sub.n (n=1, 2, . . . , x) represents a power generation model having an input heat amount and a steam extraction amount of a power generation facility as arguments.

S.sub.ECDQ(k)=f.sub.CDQ(S.sub.StCDQ(k),S.sub.StExtCDQ(k))  (9)

Here, f.sub.CDQ represents a power generation model having a boiler steam amount and a steam extraction amount of the CDQ as arguments.

[0049] (h) Power Balance Constraint

D.sub.E(k)=S.sub.ETRT(k)+S.sub.ECDQ(k)+Σ.sub.j=1.sup.xS.sub.EjU(k)+S.sub.EPurchase(k)  (10)

[0050] (i) Steam Balance Constraint The steam generation amount and the steam consumption amount at time k (=1 to N) are equal.

[00006]$\begin{array}{cc}{S}_{\mathrm{St}}\left(k\right)=D_{\mathrm{St}}\left(k\right)\underset{j=1}{\overset{x}{.Math.}}{S}_{\mathrm{StjU}}\left(k\right)+S_{\mathrm{StExtCDQ}}\left(k\right)+S_{\mathrm{StPurchase}}\left(k\right)& \left(11\right)\end{array}$

[0051] (j) Upper and Lower Limits Constraint

[0052] An inequality constraining the upper and lower limits of a decision variable is set. For example, let a decision variable be V, an upper limit value thereof be U.sub.x, and a lower limit value thereof be L.sub.x, an inequality constraint expressed in the following formula (12) is obtained.

L.sub.x≤V(k)≤U.sub.x  (12)

[0053] (k) Aggregation Constraint Condition for Decision Variables for Calculation Time Reduction

[0054] A constraint is provided to shorten the calculation (search) time by aggregating decision variables after a specified time and searching with the same value. For example, in a case where the terminal time is T×24 periods ahead of the current time as illustrated in FIG. 3(a), a constraint is provided in which the specified time is aggregated in units of 3×T periods halfway after T×13 periods and search is performed with the same value during these periods as illustrated in FIG. 3(b). Specifically, in the process of creating the constraint condition corresponding to N periods from the current time, the following aggregation constraint is imposed when the following condition 1 and condition 2 are simultaneously satisfied with the specified time as being J and the aggregation number as being n (natural number). Note that, in the present embodiment, the aggregation constraint condition is imposed on decision variables related to the power generation facilities. This is because it is difficult to make changes for a supply and demand facility of a factory since the supply and demand plan is set, whereas it is easy to change the operation condition of a power generation facility. In addition, it is preferable to set the designated time at a time after a time at which the accuracy of a production plan that an operator wants to know as reference information becomes relatively low.

[0055] (Condition 1) After the designated time J, equal to or less than the final time N. That is, J+1≤t≤N holds.

[0056] (Condition 2) Remainder determination (t−J) mod n=1 holds. This is a condition that the remainder obtained when (t−J) is divided by n is 1.

[0057] (Aggregation Constraint) An equality constraint V(t)=V(l) is set for l=t+1, . . . , min(t+n−1, N).

[0058] (1) Change Rate Constraint

[0059] In the case of defining the change rate, if the upper limit value is denoted by U.sub.v and the lower limit value is denoted by L.sub.v, inequality constraints expressed in the following formulas (13) and (13)′ are obtained.

k=1,2, . . . ,J where, L.sub.v≤(V(k)−V(k−1))/T≤U.sub.v  (13)

k=J+1, . . . ,N where, n L.sub.v≤(V(k)−V(k−1))/T≤nU.sub.v  (13)′

[0060] Here, formula (13)′ is necessary for increasing the change rate depending on the aggregation number n of the decision variable and thereby providing a change rate equivalent to that at a time at which the aggregation is not performed.

EXAMPLES

[0061] In an example of the invention, the terminal time is twelve periods ahead (one period lasts five minutes), and the optimal calculation was performed by setting the aggregation number to 6 after 7 periods for a plurality of decision variables representing the amount of fuel used at a plurality of power generation facilities, whereas in a conventional example, although the terminal time is twelve periods ahead, the optimal calculation was performed without performing aggregation, and the both results were compared. Note that calculation conditions for the both are the same except for whether or not decision variables are aggregated (cost unit price, supply and demand measurement values, etc. Processing of steps S1 to S6 illustrated in FIG. 2), and the same computer was used for both calculations. As a result, the ratio of the calculation times between the conventional example and the example of the invention (=present example/conventional example) was about 0.90, and a 10% reduction in calculation time was achieved. This can be said to be an effect of the constraint condition in which the decision variables are aggregated in the present example. At this point, as illustrated in FIG. 4, the cost was almost equivalent to that of the conventional example up to the sixth period, and the cost of the present example became higher than that of the conventional example at and after the seventh period for which the aggregation was performed. This is because the search range is constrained by the aggregation of decision variables so that the power generation amount at and after the seventh period becomes a constant value as illustrated in FIG. 5, for example. Meanwhile, a utilization method is presumed in which the optimal calculation is executed at constant periods and the operator follows the calculation result of the time before the aggregation is performed and refers as reference values to the time after the aggregation is performed, and thus the influence on the cost is minor.

[0062] Although the embodiments to which the invention made by the present inventors is applied have been described above, the present invention is not limited by the description and the drawings included as a part of the disclosure of the present invention according to the present embodiments. That is, other embodiments, examples, operation techniques, and the like made by those skilled in the art on the basis of the present embodiment are all included in the scope of the present invention.

INDUSTRIAL APPLICABILITY

[0063] According to the present invention, it is possible to provide an optimal calculation method and an optimal calculation device of the energy operating condition in an iron mill capable of shortening a time required for optimal calculation of the energy operating condition in the iron mill. In addition, according to the present invention, it is possible to provide a running method of an iron mill capable of operating the iron mill under the optimal energy operating condition.

REFERENCE SIGNS LIST

[0064] 1 INFORMATION PROCESSING DEVICE [0065] 11 INFORMATION ACQUISITION UNIT [0066] 12 OPTIMAL CALCULATION UNIT