JP2001321810A - Method for predicting power consumption in rolling plant - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method for predicting the power consumption of a rolling plant by which the consumption of power is accurately and rapidly predicted even to a rolled stock in the production of many kinds in small lot and also the accuracy of prediction is good maintained even if the state of a rolling mill and operation method are changed. SOLUTION: In the method for predicting the power which is consumed by the rolling mill A for each rolled stock when steel is rolled with the rolling mill A, the consumption of power for each rolled stock is predicted by calculating according to the formula below from an expected average surface temperature T before rolling of the rolled stock 2, a panned weight W, a planned length L before rolling and a planned thickness ratio R before and after rolling. The consumption of power for one rolled stock = a1.T+a2.W+a3.L+a4.R, where, a1, a2, a3, and a4 are coefficients determined by the rolling mill.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for predicting in advance the power consumption of a rolling mill for processing a steel sheet which is an intermediate product and a product in an iron making process.

[0002]

2. Description of the Related Art In a steel mill, power purchased from a power company and power generated by a private power generation facility provided in the steel mill are used to supply power to various facilities in the steel mill that require power. . Of these, the maximum amount of power purchased for a predetermined period of time, for example, every hour, is stipulated as a contract for the power purchased from the power company, and if it exceeds this, a penalty must be paid. Also, since the unit price of purchased power is generally higher than the unit price of power generated by private power generation equipment, manufacturing costs can be reduced by maximizing the use of power generated by private power generation equipment. If the amount of power generation becomes too large, a situation occurs in which power is transmitted in reverse to the power company, which adversely affects the power transmission and distribution system of the power company and must be avoided. For this reason, it is important to accurately predict the power to be used in the steelworks over several hours ahead and to make a power generation plan for the private power generation facility that matches the prediction. In particular, among steelworks, a rolling mill has a large scale and large fluctuations in electric power to be used, and a method of accurately predicting electric power used in this mill has been studied. As a conventional prediction method, for example, a method disclosed in JP-A-10-216813 has been proposed. In this method, the amount of power used per rolled material is stored in a database in a stratified manner based on a rolled material manufacturing instruction (size, weight, steel type, etc.), and is completely stored in the database based on the predicted material manufacturing instruction. This is a method of searching for a rolled material having the same manufacturing instruction and finding an amount of electric power corresponding thereto.
This method is certainly effective in the case where a rolled material having exactly the same production order is rolled in large quantities. However, there is a disadvantage that it is not possible to retrieve from the database if a part of the value of the manufacturing instruction is slightly different. It is not practical because it cannot be searched. In recent years, the needs of users have been diversified, and such multi-product small-lot production has become mainstream, and it is thought that this tendency will become even more pronounced in the future.

[0003]

SUMMARY OF THE INVENTION In order to solve the above-mentioned problems, the present invention extracts the characteristics of a rolled material closely related to the amount of electric power used and uses those characteristics to improve the rolled material particularly in the production of various kinds of small lots. In addition to accurately and quickly predicting the amount of power used, even if the state of the rolling mill or the operating method changes, the power consumption of the rolling mill maintains the prediction accuracy by changing the prediction formula accordingly. It is intended to provide a prediction method.

[0004]

According to the present invention, there is provided a method for estimating power consumption of a rolling mill according to the present invention, comprising:
In the method of estimating for each book, the power consumption of the rolling mill by the following formula based on the planned average surface temperature T before rolling of the rolled material, the planned weight W, the planned length L before rolling, and the planned thickness ratio R before and after rolling. Is a method for estimating power consumption of a rolling mill for estimating the power consumption. Power consumption per rolled material = a1 · T + a2 · W + a3 ·
L + a4 · R where a1, a2, a3, and a4 are coefficients determined by the rolling mill. In the method for predicting power consumption of a rolling mill according to the present invention, the predicted power consumption of each rolled material may be integrated per predetermined time to obtain power consumption for a predetermined time. Further, in the method for predicting power consumption of a rolling mill according to the present invention, a difference between the predicted power consumption and the actual power used in rolling the rolled material is calculated for each rolled material, and an integrated value of the difference is used. The coefficients a1, a of the prediction equation
It is preferable to modify 2, a3 and a4.

[0005]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A method for estimating the power consumption of a rolling mill according to an embodiment of the present invention will be described with reference to FIGS. FIG. 1 is a schematic view showing a rolling mill A, an electric motor 1 for driving the rolling mill A, and rolling. A rolled material (steel material) 2 is loaded into a rolling mill A from one side (left side in FIG. 1), reduced in thickness by a rolling roll 3 rotating by an electric motor 1, and discharged to the other side (right side in FIG. 1). You. It is a commonly used rolling method to roll one rolling mill A or a plurality of rolling mills continuously in the longitudinal direction of the rolled material 2. The force from the rolling roll 3 applied to the rolled material 2 at this time is schematically shown in FIG. The rotation torque generated by the electric motor 1 generates a frictional force μ between the rolling material 2 through the rolling roll 3, and this force is decomposed into a rolling force P and a propulsive force F and acts on the rolling material 2. The rolling force P is a force required to reduce the thickness, and is related to the hardness of the rolled material 2 and the thickness difference before and after rolling (t1−t2), that is, the rolling reduction. The propulsion force F is the volume of the reduced thickness. Is pushed forward, and is related to the amount of reduction and the weight of the rolled material 2. The amount of power used for each rolled material 2, that is, the amount of power used by the electric motor 1 when rolling is performed is
Since it depends on the magnitude of the friction force μ and the time when the friction force μ is generated, generally, the amount of the rolled material 2 processed, the weight of the rolled material 2, the ease with which the rolled material 2 can be processed, and It can be said that it depends on the time taken. As the values indicating these, the power consumption for each rolled material is predicted using the following information and prediction formulas that are planned with high accuracy on a daily basis. Amount processed (that is, planned thickness before and after rolling) R = average thickness of rolled material before rolling t1 / target thickness t2 of rolled material after rolling Ease of processing = planned average surface temperature T of rolled material before rolling Working time = Scheduled length of rolled material before rolling L Power consumption per rolled material = a1 · T + a2 · W + a3 ·
L + a4 · R where W = planned weight of rolled material, a1, a2, a3, a
4 is a coefficient depending on the rolling mill.

FIG. 3 shows that coefficients a1, a2, a3, and a4 are sequentially corrected when there is a difference between the predicted value of the amount of use predicted by the above-mentioned prediction formula and the amount of power actually used by the rolled material. 6 is a flowchart showing a procedure. One rolled material 2
Before the start of rolling, the predicted power consumption P is calculated (S31), and when the rolling of the rolled material 2 is completed, the actual power consumption Q (actual power consumption) used in the rolling is calculated. (S32) (S33). Next, the difference δ between the predicted power consumption P and the actual power consumption Q is calculated (S34), the file storing the integrated value I of the difference is read, and the difference calculated this time is integrated (S35). Save the results to a file. In addition, the result I of integration and a preset gain (0
The product of α, which is larger and smaller than 1, is calculated, and the result is added to each of the coefficients a1, a2, a3, and a4 to update the value of the coefficient (S36). The predicted power consumption of the next rolled material 2 is performed using the updated coefficient.

FIG. 4 shows a coefficient a in a long-term prediction.
6 is a flowchart showing a procedure for correcting 1, a2, a3, and a4. The predicted electric energy and the actual electric energy of each piece are always stored, and the data of the material rolled in the past hour is read at the timing of performing the long-term prediction (S41). The difference between the predicted power consumption and the actual power consumption is integrated (S42). Next, the product of the integrated value I and the gain α is calculated, and the result is referred to as the respective coefficients a1, a
The value of the coefficient is updated in addition to 2, a3, and a4 (S4
3). Then, the next period is predicted using the updated coefficient (S44).

[0008]

EXAMPLES As shown in Table 1 below, the predicted power of each rolled material for several hours was calculated and compared with the actual power. The hourly integrated value was compared between the predicted value and the actual value.

[0009]

[Table 1]

FIG. 5 shows the relationship between the predicted power consumption and the actual power consumption every hour. As can be seen from this figure, there is a correlation between the predicted power consumption and the actual power consumption, and the dispersion is small. From this, it is possible to accurately predict the power consumption at the time of rolling in the rolling mill.

[0011]

According to the method for predicting the power consumption of a rolling mill according to the first to third aspects, the power consumption can be accurately and quickly predicted even for rolled materials in the production of various kinds of small lots having various manufacturing instructions. be able to. In particular, in the method for predicting power consumption of a rolling mill according to the second aspect, by integrating over a predetermined time, it is possible to predict in a predetermined time unit. This has the effect of significantly reducing According to the method for predicting power consumption of a rolling mill according to the third aspect, it is possible to maintain good prediction accuracy even if the state of the rolling mill or the operating method changes.

[Brief description of the drawings]

FIG. 1 is an explanatory diagram showing a rolling mill and a rolling state applied to a method for estimating power consumption of a rolling mill according to an embodiment of the present invention.

FIG. 2 is a schematic view showing a force applied to a rolled material in a cross section during rolling by the rolling mill.

FIG. 3 is a flowchart showing a procedure for sequentially correcting coefficients of a prediction formula for each rolled material.

FIG. 4 is a flowchart showing a procedure for correcting coefficients of a prediction equation in long-term prediction.

FIG. 5 is a graph showing a relationship between a value obtained by integrating a predicted value for each rolled material in units of one hour and an actual power use value for one hour.

[Explanation of symbols]

 A: rolling mill, 1: electric motor, 2: rolled material, 3: rolling roll

Claims (3)

[Claims] 1. A method for predicting the electric power used by a rolling mill for each rolled material when rolling a steel material with a rolling mill, the method comprising the steps of: Planned length L before and planned thickness ratio R before and after rolling
And estimating the power consumption of the rolling mill by the following equation: Power consumption per rolled material = a1 · T + a2 · W + a3 ·
L + a4 · R where a1, a2, a3, and a4 are coefficients determined by the rolling mill. 2. The predicted power consumption for each rolled material is
2. The method according to claim 1, wherein the power consumption is calculated for a predetermined time by integrating the power consumption per predetermined time. 3. The difference between the predicted power consumption and the actual power used in rolling the rolled material is calculated for each rolled material,
2. The method according to claim 1, wherein the coefficient of the prediction formula is corrected using an integrated value of the difference.