CN113159360A - Method for predicting power consumption of ferrous metal smelting and calendering processing industry - Google Patents

Method for predicting power consumption of ferrous metal smelting and calendering processing industry Download PDF

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CN113159360A
CN113159360A CN202011114946.2A CN202011114946A CN113159360A CN 113159360 A CN113159360 A CN 113159360A CN 202011114946 A CN202011114946 A CN 202011114946A CN 113159360 A CN113159360 A CN 113159360A
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power consumption
ferrous metal
metal smelting
steel
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刘青
单葆国
谭显东
张春成
张莉莉
王向
汲国强
张成龙
王红
吴姗姗
吴鹏
姚力
吴陈锐
薛万磊
徐楠
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State Grid Energy Research Institute Co Ltd
North China Electric Power University
Economic and Technological Research Institute of State Grid Shandong Electric Power Co Ltd
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State Grid Energy Research Institute Co Ltd
North China Electric Power University
Economic and Technological Research Institute of State Grid Shandong Electric Power Co Ltd
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Abstract

The invention relates to a method for predicting the power consumption of ferrous metal smelting and calendering processing industries. The method comprises the following steps: step 1: firstly, collecting and processing historical data of the output and the power consumption of main products in ferrous metal smelting and calendering processing industries, and calculating the power consumption of the main products in unit output; step 2: secondly, predicting the yield and unit yield power consumption of main products in the ferrous metal smelting and calendering processing industry in the target year; and step 3: and finally, calculating the power consumption prediction result of the ferrous metal smelting and calendering processing industry in the target year. The invention solves the problem of how to predict the power consumption of the ferrous metal smelting and calendering industry, can accurately predict the power consumption of the ferrous metal smelting and calendering industry, and is beneficial to reasonably and effectively utilizing electric power.

Description

Method for predicting power consumption of ferrous metal smelting and calendering processing industry
Technical Field
The invention relates to the technical field of electric power engineering, in particular to a method for predicting the power consumption of ferrous metal smelting and calendering processing industries.
Background
The electric quantity prediction technology can guide the construction of electric power facilities and equipment and reduce the excessive consumption of energy.
The patent analyzes the correlation between the power consumption and the output of the ferrous metal smelting and calendering industry, quotes the power consumption of unit output, and provides a power consumption prediction model of the ferrous metal smelting and calendering industry. The method mainly uses a trend extrapolation method or a regression model to predict the yield and unit yield power consumption of main products in the ferrous metal smelting and calendering industry of the target year, and finally predicts the power consumption of the ferrous metal smelting and calendering industry of the target year.
Disclosure of Invention
The invention aims to solve the technical problem of providing a method for predicting the power consumption of ferrous metal smelting and calendaring industry. Specifically, in order to further research the relation between the power consumption of the ferrous metal industry and the industry production, the invention provides a power consumption prediction method for the ferrous metal smelting and calendering processing industry, which can quantitatively analyze the correlation between the power consumption and the yield of the ferrous metal industry. Firstly, collecting and processing historical data of the output and the power consumption of main products in ferrous metal smelting and calendering processing industries, and calculating the power consumption of the main products in unit output; secondly, predicting the yield and unit yield power consumption of main products in the ferrous metal smelting and calendering processing industry of the target year by using a trend extrapolation method or a regression model; and finally, calculating the power consumption prediction result of the ferrous metal smelting and calendering processing industry in the target year. The method has the main difficulties that firstly, the data of the electric furnace steel power consumption and the converter steel power consumption are not published, and certain difficulty exists in data collection, so that the historical and current electric furnace steel power consumption and converter steel power consumption are estimated according to the proportion relation between the electric furnace steel output and the steel output; secondly, the influence factors which need to be considered by the regression model of the unit yield power consumption of the main products are not easy to determine, and different influence factors are adopted according to the characteristics of different products. The method can predict the power consumption of ferrous metal smelting and calendering processing industries, is favorable for reasonable and effective power planning, and promotes the stable increase of the economy of high-energy-consumption industries.
Technical objects that can be achieved by the present invention are not limited to what has been particularly described above, and other technical objects that are not described herein will be more clearly understood by those skilled in the art from the following detailed description.
The technical scheme for solving the technical problems is as follows:
according to one aspect of the present disclosure, there is provided a method for predicting the amount of electricity used in ferrous metal smelting and calendaring, the method comprising:
step 1: firstly, historical data of the output and the power consumption of main products in ferrous metal smelting and calendering processing industries are collected and processed, and the unit output power consumption of the main products is calculated;
step 2: secondly, predicting the yield and unit yield power consumption of main products in the ferrous metal smelting and calendering processing industry in the target year;
and step 3: and finally, calculating the power consumption prediction result of the ferrous metal smelting and calendering processing industry in the target year.
Optionally, the historical data comprises converter steel production w1Electric furnace steel yield w2Iron alloy yield w3Electric power p for steel and iron12Electric power p for ferroalloy3According to the electric furnace steel yield w2Account for the steel yield w12Specific gravity, estimation of the amount of Steel Power consumption p of the converter1Electric power consumption p for electric furnace steel2The historical data of (a), wherein,
Figure 100033DEST_PATH_IMAGE002
。
optionally, the specific production power consumption r of the converter steel is calculated according to the obtained historical data of the production and the power consumption1Electric furnace steel unit yield power consumption r2Specific output power consumption r of HeFe alloy3Wherein, in the step (A),
Figure 686348DEST_PATH_IMAGE004
。
optionally, step 2 further comprises the steps of:
step 21: predicting the main product yield of the ferrous metal smelting and calendering processing industry in the target year,wherein, a trend extrapolation method is adopted to predict the converter steel yield W of the target year1Electric furnace steel yield W2Yield of ferroalloy W3；
Step 22: establishing a regression model for the unit yield power consumption of main products in ferrous metal smelting and calendering processing industry, wherein the unit yield power consumption r of converter steel1Relates to a technical input ratio e of ferrous metal smelting and rolling processing industry1Ton steel smoke emission e2The regression model of (2); specific yield power consumption r of electric furnace steel2Relating to the research and development cost e of ferrous metal smelting and calendering processing industry3The regression model of (2); specific output power consumption r of ferroalloy3Relating to the technical improvement expenditure e of ferrous metal smelting and calendering processing industry4Ton steel smoke emission e2The regression model of (2);
step 23: predicting the technical input ratio e of ferrous metal smelting and rolling processing industry in the target year by adopting a trend extrapolation method1Ton steel smoke emission e2Research and development cost e of ferrous metal smelting and calendering processing industry3The technical improvement expenditure e of ferrous metal smelting and calendering processing industry4；
Step 24: according to the prediction result in the step 23 and the regression model in the step 22, obtaining the unit yield power consumption R of the converter steel in the target year1Electric furnace steel unit yield power consumption R2Specific output of ferroalloy and power consumption R3。
Optionally, step 3 further comprises the steps of:
step 31: the power consumption p of the converter steel in the historical years1Electric power consumption p for electric furnace steel2Electric power p for ferroalloy3Obtaining the power consumption p' of the main product in the target year, and further calculating the specific gravity phi historical data of the power consumption of the main product in the power consumption p of the ferrous metal smelting and calendering processing industry, wherein,
Figure 1
step 32: predicting the power consumption of the main products in the target year by adopting a trend extrapolation methodThe specific weight of the alloy is the electric quantity used in ferrous metal smelting and rolling processing industryФ；
Step 33: calculating the electric quantity P of the converter steel in the target year1Electric power P for electric furnace steel2Electric power P for ferroalloy3Further obtaining the power consumption P' of the main product in the target year, wherein,
Figure 533398DEST_PATH_IMAGE008
P′=P 1+P 2+P 3；
step 34: obtaining the power consumption P of the ferrous metal smelting and calendering processing industry in the target year, wherein,
Figure 2
。
optionally, the trend extrapolation includes a linear, quadratic or logarithmic trend extrapolation.
According to an aspect of the present disclosure, there is provided an apparatus for predicting electric power consumption in ferrous metal smelting and rolling industries, comprising: memory, processor and computer program stored on the memory and executable on the processor, the computer program when executed by the processor implementing the steps of a method for predicting power usage in the ferrous metal smelting and calendering industry as described in any one of the above.
According to an aspect of the present disclosure, the present invention provides a computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon an implementation program of information transfer, which when executed by a processor implements the steps of the method for predicting electric power usage for ferrous metal smelting and calendering processing industry as described in any one of the above.
The above-described embodiments are only some of the embodiments of the present invention, and those skilled in the art can derive and understand various embodiments including technical features of the present invention from the following detailed description of the present invention.
It will be appreciated by persons skilled in the art that the effects that can be achieved by the present invention are not limited to what has been particularly described hereinabove and other advantages of the present invention will be more clearly understood from the following detailed description.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 shows a flow chart of a method for predicting the power consumption in ferrous metal smelting and calendaring operations according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to exemplary embodiments of the invention, examples of which are illustrated in the accompanying drawings. The detailed description, which will be given below with reference to the accompanying drawings, is intended to explain exemplary embodiments of the present invention, rather than to show the only embodiments that can be implemented according to the present invention. The following detailed description includes specific details in order to provide a thorough understanding of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced without these specific details.
In some instances, well-known structures and devices are omitted or shown in block diagram form, focusing on important features of the structures and devices so as not to obscure the concept of the present invention. The same reference numbers will be used throughout the specification to refer to the same or like parts.
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
In the description of the present invention, it is to be understood that the terms "upper", "lower", "center", "inner", "outer", "top", "bottom", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience in describing the present invention and simplifying the description, but do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected;
they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Example 1
Fig. 1 is a flow chart illustrating a method for predicting the power consumption of ferrous metal smelting and rolling processing industry according to an embodiment of the present invention. The invention provides a method for predicting the power consumption of ferrous metal smelting and calendaring industry, which comprises the following steps of S1-S3:
s1: the method comprises the following steps of collecting and processing historical data of the yield and the power consumption of main products in ferrous metal smelting and calendering processing industries, and calculating the unit yield power consumption of the main products:
the method comprises the following steps: historical data of the output and the power consumption of main products in ferrous metal smelting and calendaring industries are collected and processed.
The main products of ferrous metal smelting and calendering industry include steel and iron alloys, wherein steel can be divided into converter steel and electric furnace steel according to the manufacturing process. The yield of converter steel needs to be collectedw 1Electric furnace steel yieldw 2Iron alloy yieldw 3Historical data, data originated from the national institute of statistics, the iron and steel industry association of china. Also needs to collect the power consumption of steelp 12Electric power consumption of iron alloyp 3And data, wherein the data is derived from the medium electric connection. Because of the power consumption of the converter steelp 1Electric power consumption for electric furnace steelp 2Data are not published, so according to electric furnace steel yieldw 2Account for the steel yieldw 12Specific gravity, estimation of electric power consumption of converter steelp 1Electric power consumption for electric furnace steelp 2Historical data. The time span of the historical data is nearly 20 years in the current year, and the data object is China.
Figure DEST_PATH_IMAGE011
Step two: calculating unit yield power consumption historical data of main products
Calculating the power consumption of the unit yield of the converter steel according to the data of the yield and the power consumption of the main products in the step oner 1Electric furnace steel unit yield power consumptionr 2Power consumption per unit output of ferroalloyr 3。
Figure DEST_PATH_IMAGE012
S2: the method for predicting the yield and the unit yield power consumption of main products in the ferrous metal smelting and calendering processing industry in the target year specifically comprises the following steps:
the method comprises the following steps: and predicting the main product yield of the ferrous metal smelting and calendering processing industry in the target year.
Predicting the yield of converter steel in the target year by adopting a linear, quadratic function or logarithmic function trend extrapolation methodW 1Electric furnace steel yieldW 2Iron alloy yieldW 3。
Step two: and establishing a regression model for the unit output power consumption of main products in ferrous metal smelting and calendering processing industries. Wherein, the unit yield of the converter steel consumes the electricityr 1Relates to the technical input ratio of ferrous metal smelting and calendering processing industrye 1Ton steel smoke and dust emissione 2The regression model of (2); specific yield power consumption of electric furnace steelr 2Relates to ferrous metal smelting and calendering processing industry R&D expensese 3The regression model of (2);unit output power consumption of ferroalloyr 3Relating to the technical improvement expenditure of ferrous metal smelting and calendering processing industrye 4Ton steel smoke and dust emissione 2The regression model of (1).
As an example, a converter steel specific production power consumption model was obtained as followsr 1Ton steel smoke and dust emissione 2 The units of (A) are kilowatt-hour/ton and ton/ten thousand yuan respectively.
Figure DEST_PATH_IMAGE013
The electric furnace steel specific yield power consumption model is obtained as follows, wherein, the specific yield power consumptionr 2Ferrous metal smelting and calendering industry R&D expensese 3 The units of (A) are kilowatt-hour/ton and ten thousand yuan respectively.
Figure DEST_PATH_IMAGE014
The ferroalloy yield power consumption model is obtained as follows, wherein, the unit yield power consumptionr 3 And the expenditure of technical reconstructione 4 Ton steel smoke and dust emissione 2 The units of (A) are kilowatt-hour/ton, ten thousand yuan and ton/ten thousand yuan respectively.
Figure DEST_PATH_IMAGE015
Step three: predicting the technical input ratio of ferrous metal smelting and rolling industry in the target year by linear, quadratic function or logarithmic functionE 1Ton steel smoke and dust emissionE 2Ferrous metal smelting and calendering industry R&D expensesE 3The technical transformation expenditure of ferrous metal smelting and rolling processing industryE 4。
Step four: according to the predicted result in the third step and the regression model in the second stepType, obtaining the unit yield power consumption of the converter steel in the target yearR 1Electric furnace steel unit yield power consumptionR 2Power consumption of ferroalloy per outputR 3。
S3: and finally, calculating the power consumption prediction result of the ferrous metal smelting and calendering processing industry in the target year, and specifically comprising the following steps of:
the method comprises the following steps: electric quantity of converter steel used in historical yearsp 1Electric power consumption for electric furnace steelp 2Electric power consumption of iron alloyp 3Obtaining the power consumption of the main products in the target yearp′And further calculating the power consumption of the main products in the power consumption of the ferrous metal smelting and calendering processing industriesp Specific gravity ofφHistorical data.
Figure 3
Step two: and (3) predicting the specific gravity phi of the power consumption of the main product in the target year accounting for the power consumption of the ferrous metal smelting and rolling processing industry by adopting a trend extrapolation method such as a linear function, a quadratic function or a logarithmic function.
Step three: calculating the electric quantity of the converter steel in the target year according to the step one and the step four in the S2P 1Electric power consumption for electric furnace steelP 2Electric power consumption of iron alloyP 3Further obtain the power consumption of the main products in the target yearP′。
Figure DEST_PATH_IMAGE017
P′=P 1+P 2+P 3
Step four: and according to the results of the second step and the third step, obtaining the power consumption P of the ferrous metal smelting and calendering processing industry in the target year.
Figure 4
Example 2
According to an embodiment of the present invention, there is provided an apparatus for predicting electric power consumption in ferrous metal smelting and rolling industries, including: a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program when executed by the processor implementing the steps of the method for predicting electric power usage for the ferrous metal smelting and calendering industry as described in embodiment 1 above.
Example 3
According to an embodiment of the present invention, there is provided a computer-readable storage medium having stored thereon a program for implementing information transfer, which when executed by a processor implements the steps of the method for predicting electric power usage for ferrous metal smelting and calendaring industry as described in embodiment 1 above.
At present, Chinese economy enters a new normal state, meaning that element driving and investment driving are switched to innovation driving, economic structures are continuously upgraded, and economy is switched to a high-quality development stage from a high-speed growth stage.
The ecological civilization construction is greatly promoted, and the energy production and the consumption revolution are actively promoted to gradually become a social consensus. Similarly, the electric power industry is faced with a new trend that the whole national industrial structure is developed towards high quality, and the energy efficiency and the energy utilization rate are continuously improved. The electricity consumption is used as a 'rain and sun meter' for economic development, and the change condition of the electricity consumption is concerned by various fields. Theoretically, the relationship between the power consumption and the increase value is very close, and under the condition that the industrial structure or the energy consumption level does not change much, the power consumption acceleration rate is positively correlated with the industrial increase value. The invention relates to a method for predicting the power consumption of ferrous metal smelting and calendering processing industry, which is one of four high-energy-consumption industries, and the method is used for predicting the power consumption of the ferrous metal smelting and calendering processing industry under the current macroscopic economic level so as to accurately grasp the economic and electric conditions of the industry and then make preliminary judgment on the whole industry.
From the above description of the embodiments, it is obvious for those skilled in the art that the present application can be implemented by software and necessary general hardware, and of course, can also be implemented by hardware. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as a floppy disk, a Read-only memory (ROM), a Random Access Memory (RAM), a FLASH memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods described in the embodiments of the present application.
As mentioned above, a detailed description of the preferred embodiments of the invention has been given to enable those skilled in the art to make and practice the invention. Although the present invention has been described with reference to exemplary embodiments, those skilled in the art will appreciate that various modifications and changes can be made in the present invention without departing from the spirit or scope of the invention described in the appended claims. Thus, the present invention is not intended to be limited to the particular embodiments shown and described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (8)

1.一种用于预测黑色金属冶炼及压延加工业用电量的方法，其特征在于，所述方法包括：1. a method for predicting ferrous metal smelting and rolling processing industry electricity consumption, is characterized in that, described method comprises: 步骤1：首先搜集并处理黑色金属冶炼及压延加工业主要产品的产量和用电量的历史数据，计算主要产品的单位产量电耗；Step 1: First collect and process the historical data on the output and electricity consumption of the main products of the ferrous metal smelting and rolling industry, and calculate the electricity consumption per unit output of the main products; 步骤2：其次预测目标年份黑色金属冶炼及压延加工业主要产品的产量和单位产量电耗；Step 2: Next, predict the output of the main products of the ferrous metal smelting and rolling processing industry and the power consumption per unit of output in the target year; 步骤3：最后计算目标年份黑色金属冶炼及压延加工业用电量预测结果。Step 3: Finally, calculate the forecast result of electricity consumption of ferrous metal smelting and rolling processing industry in the target year. 2.根据权利要求1所述的方法，2. The method according to claim 1, 其特征在于，所述历史数据包括转炉钢产量w1、电炉钢产量w2、铁合金产量w3、钢铁用电量p12、铁合金用电量p3，按照电炉钢产量w2占钢铁产量w12比重，估算转炉钢用电量p1和电炉钢用电量p2的历史数据，其中，It is characterized in that, the historical data includes converter steel output w 1 , electric furnace steel output w 2 , ferroalloy output w 3 , iron and steel power consumption p 12 , ferroalloy power consumption p 3 , according to the share of electric furnace steel output w 2 in steel output w 12 Specific gravity, estimated historical data of converter steel power consumption p 1 and electric furnace steel power consumption p 2 , where,
Figure DEST_PATH_IMAGE001
。
Figure DEST_PATH_IMAGE001
. 3.根据权利要求2所述的方法，3. The method according to claim 2, 其特征在于，根据所获得的产量和用电量的历史数据，计算转炉钢单位产量电耗r1、电炉钢单位产量电耗r2和铁合金单位产量电耗r3，其中，It is characterized in that, according to the obtained historical data of output and power consumption, the power consumption r 1 per unit output of converter steel, the power consumption r 2 per unit output of electric furnace steel and the power consumption r 3 per unit output of ferroalloy are calculated, wherein,
Figure DEST_PATH_IMAGE002
。
Figure DEST_PATH_IMAGE002
. 4.根据权利要求3所述的方法，4. The method of claim 3, 其特征在于，步骤2还包括以下步骤：It is characterized in that, step 2 also comprises the following steps: 步骤21：预测目标年份黑色金属冶炼及压延加工业主要产品产量，其中，采用趋势外推法，预测目标年份转炉钢产量W1、电炉钢产量W2、铁合金产量W3；Step 21: Predict the output of the main products of the ferrous metal smelting and rolling processing industry in the target year, wherein, using the trend extrapolation method, predict the output of converter steel W 1 , the output of electric furnace steel W 2 , and the output of ferroalloy W 3 in the target year; 步骤22：对黑色金属冶炼及压延加工业主要产品单位产量电耗建立回归模型，其中，转炉钢单位产量电耗r1是关于黑色金属冶炼及压延加工业技术投入比率e1、吨钢烟尘排放e2的回归模型；电炉钢单位产量电耗r2是关于黑色金属冶炼及压延加工业研发经费e3的回归模型；铁合金单位产量电耗r3是关于黑色金属冶炼及压延加工业技术改造经费支出e4、吨钢烟尘排放e2的回归模型；Step 22: Establish a regression model for the power consumption per unit output of the main products of the ferrous metal smelting and rolling industry, where the power consumption r 1 per unit output of the converter steel is related to the technical input ratio e 1 of the ferrous metal smelting and rolling processing industry, the emission of smoke and dust per ton of steel The regression model of e 2 ; the electricity consumption per unit output of electric furnace steel r 2 is the regression model of the research and development expenditure of the ferrous metal smelting and rolling processing industry; e 3 ; Regression model of expenditure e 4 and soot emission e 2 per ton of steel; 步骤23：采用趋势外推法，预测目标年份黑色金属冶炼及压延加工业技术投入比率e1、吨钢烟尘排放e2、黑色金属冶炼及压延加工业研发经费e3、黑色金属冶炼及压延加工业技术改造经费支出e4；Step 23: Use the trend extrapolation method to predict the technological investment ratio e 1 of the ferrous metal smelting and rolling processing industry in the target year, the emission of smoke and dust per ton of steel e 2 , the research and development expenses of the ferrous metal smelting and rolling processing industry e 3 , and the ferrous metal smelting and rolling processing industry. Expenditure on industrial technological transformation e 4 ; 步骤24：根据步骤23中的预测结果，以及步骤22中的回归模型，获得目标年份转炉钢单位产量电耗R1、电炉钢单位产量电耗R2、铁合金单位产量电耗R3。Step 24: According to the prediction result in Step 23 and the regression model in Step 22, obtain the power consumption R 1 per unit output of converter steel, R 2 per unit output of electric furnace steel, and R 3 per unit output of ferroalloy in the target year. 5.根据权利要求4所述的方法，5. The method of claim 4, 其特征在于，步骤3还包括以下步骤：It is characterized in that, step 3 also comprises the following steps: 步骤31：由历史年份转炉钢用电量p1、电炉钢用电量p2、铁合金用电量p3，得到目标年份主要产品用电量p′，进而计算主要产品用电量占黑色金属冶炼及压延加工业用电量p的比重φ历史数据，其中，Step 31: From the power consumption p 1 of the converter steel, the power consumption p 2 of the electric furnace steel, and the power consumption p 3 of the ferroalloy in the historical years, the power consumption p' of the main products in the target year is obtained, and then the proportion of the power consumption of the main products in ferrous metals is calculated. The historical data of the proportion φ of the electricity consumption p of the smelting and rolling processing industry, among which,
Figure DEST_PATH_IMAGE003
Figure DEST_PATH_IMAGE003
 步骤32：采用趋势外推法，预测目标年份主要产品用电量占黑色金属冶炼及压延加工业用电量的比重Ф；Step 32: Use the trend extrapolation method to predict the proportion Ф of the electricity consumption of the main products in the ferrous metal smelting and rolling processing industry in the target year; 步骤33：计算目标年份转炉钢用电量P1、电炉钢用电量P2、铁合金用电量P3，进而得到目标年份主要产品用电量P′，其中，Step 33: Calculate the electricity consumption P 1 of the converter steel, the electricity consumption P 2 of the electric furnace steel, and the electricity consumption P 3 of the ferroalloy in the target year, and then obtain the electricity consumption P' of the main products in the target year, wherein,
Figure DEST_PATH_IMAGE004
Figure DEST_PATH_IMAGE004
 P′=P 1+P 2+P 3； P′ = P 1 + P 2 + P 3 ; 步骤34：得到目标年份黑色金属冶炼及压延加工业用电量P，其中，Step 34: Obtain the electricity consumption P of the ferrous metal smelting and rolling processing industry in the target year, wherein,
Figure DEST_PATH_IMAGE005
。
Figure DEST_PATH_IMAGE005
. 6.根据权利要求5所述的方法，6. The method of claim 5, 其特征在于，所述趋势外推法包括线性、二次函数或对数函数趋势外推法。It is characterized in that, the trend extrapolation method includes a linear, quadratic function or logarithmic function trend extrapolation method. 7.一种用于预测黑色金属冶炼及压延加工业用电量的设备，其特征在于，包括：存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序，所述计算机程序被所述处理器执行时实现如权利要求1至6中任一项所述的用于预测黑色金属冶炼及压延加工业用电量的方法的步骤。7. A device for predicting the power consumption of ferrous metal smelting and rolling processing industry, characterized in that it comprises: a memory, a processor and a computer program stored on the memory and running on the processor, The computer program, when executed by the processor, implements the steps of the method for predicting electricity consumption in the ferrous metal smelting and rolling industry as claimed in any one of claims 1 to 6. 8.一种计算机可读存储介质，其特征在于，所述计算机可读存储介质上存储有信息传递的实现程序，所述程序被处理器执行时实现如权利要求1至6中任一项所述的用于预测黑色金属冶炼及压延加工业用电量的方法的步骤。8. A computer-readable storage medium, characterized in that, an implementation program for information transmission is stored on the computer-readable storage medium, and when the program is executed by a processor, the implementation as claimed in any one of claims 1 to 6 is realized. The steps of the described method for predicting the electricity consumption of the ferrous metal smelting and rolling industry.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103440556A (en) * 2013-09-04 2013-12-11 国家电网公司 Electricity consumption prediction method based on economic conduction
CN105956716A (en) * 2016-05-20 2016-09-21 国网安徽省电力公司经济技术研究院 Total social electricity consumption prediction method based on industry economy and electricity relationship
CN111553524A (en) * 2020-04-23 2020-08-18 国网能源研究院有限公司 Method for forecasting electricity consumption in ferrous metal smelting and rolling industry

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103440556A (en) * 2013-09-04 2013-12-11 国家电网公司 Electricity consumption prediction method based on economic conduction
CN105956716A (en) * 2016-05-20 2016-09-21 国网安徽省电力公司经济技术研究院 Total social electricity consumption prediction method based on industry economy and electricity relationship
CN111553524A (en) * 2020-04-23 2020-08-18 国网能源研究院有限公司 Method for forecasting electricity consumption in ferrous metal smelting and rolling industry

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