Method and device for quickly identifying power consumption abnormity in long-process iron and steel enterprises
By obtaining and analyzing the historical production data of long-process steel enterprises, using Pareto graph and fitting curve methods, the problem that enterprises cannot accurately judge power consumption is solved, and the effect of quickly identifying power consumption abnormalities and improving judgment accuracy is achieved.
Patent Information
- Application Number
- CN202411162813.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-23
- Publication Date
- 2024-12-10
AI Technical Summary
Long-process steel companies lack effective unified energy consumption management systems at process levels, resulting in the inability to accurately judge the enterprise's energy efficiency and the inability to quickly identify power consumption abnormalities.
By obtaining the company's historical production data, the comprehensive power consumption of tons of steel in the whole process, the comprehensive power consumption of tons of steel in the process level, and the comprehensive power consumption of tons of equipment level, the Pareto graph and fitting curve method are used to locate abnormal power consumption processes and equipment. Draw a visual chart for power consumption analysis.
It realizes the rapid identification of abnormal electricity consumption processes and equipment when the steel output is normal, improves the accuracy and speed of power consumption judgment, and can accurately identify whether the power consumption indicators in the entire process are abnormal when the steel output is abnormal.
Smart Images
Figure CN119106807A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of power consumption data analysis, and in particular to a method and device for quickly identifying power consumption anomalies in a long-process steel enterprise. Background Art
[0002] China's steel industry is still dominated by the long process, with the short process accounting for about 10%. Electricity is an indispensable energy source for steel companies. According to statistics, my country's steel industry consumes about 10% of the country's total electricity consumption and about 15% of industrial electricity consumption.
[0003] The power system of a long-process steel enterprise is characterized by many and dispersed users, multiple power generation sources, frequent load changes, close connection with the production process, and significant impact of the output of each process.
[0004] Electricity costs account for about 10% of the production costs of steel companies. It is imperative to strengthen the control of electricity consumption in each process, adopt comprehensive electricity-saving measures, reduce the comprehensive electricity consumption per ton of steel in the entire process, and achieve systematic energy conservation and consumption reduction.
[0005] In the current long-process steel enterprises, there is a lack of an effective and unified energy consumption management system at the process level, so it is impossible to accurately judge the energy efficiency of the enterprise.
[0006] Therefore, a method and device for quickly identifying abnormal power consumption in a long-process steel enterprise is provided to solve the above problems. Summary of the invention
[0007] The technical problem to be solved by the present invention is that, in the current long-process steel enterprises, there is a lack of an effective process-level unified energy consumption management system, so it is impossible to accurately judge the energy efficiency of the enterprise. Therefore, a method for quickly identifying abnormal power consumption in a long-process steel enterprise is provided. The method for quickly identifying abnormal power consumption in a long-process steel enterprise includes: Obtain the company's historical production data and extract the comprehensive power consumption per ton of steel in the entire process and the comprehensive power consumption per ton of production at the process level; Extract the comprehensive power consumption per ton of steel at the process level from the company's historical production data; extract the comprehensive power consumption per ton of production at the equipment level from the company's historical production data; When steel production is normal, the power consumption is judged to be normal by the comprehensive power consumption per ton of steel in the whole process and the comprehensive power consumption per ton of steel at the process level; if the power consumption is abnormal, the abnormal power consumption process and abnormal power consumption equipment are located by drawing the Pareto chart method; When steel production is abnormal, the historical power consumption data of the enterprise's normal power consumption is divided into several data groups according to preset conditions; Draw a scatter point model of the process output and the process-level comprehensive power consumption per ton in the data group, and output a fitting curve: process-level comprehensive power consumption per ton = a*process output + b. Substitute the daily process output into the fitting curve to obtain the corresponding actual process-level comprehensive power consumption per ton; According to the actual process-level comprehensive power consumption per ton of output and the process-level comprehensive power consumption per ton of output, determine the abnormal power consumption of the process today; Use the table tool to draw a visual chart and include the daily output and electricity consumption per ton of each process into the chart.
[0008] Furthermore, it also includes: when steel production is normal, judging whether the power consumption is normal through the comprehensive power consumption per ton of steel in the whole process and the comprehensive power consumption per ton of steel at the process level; if the power consumption is normal, the company's power consumption for that day is normal.
[0009] Furthermore, the method of locating abnormal power consumption processes and abnormal power consumption equipment by drawing a Pareto chart includes: Build a company-level power consumption Pareto chart based on the comprehensive power consumption per ton of steel in the entire process and the comprehensive power consumption per ton of steel at the process level to locate processes with abnormal power consumption; The equipment-level comprehensive power consumption per ton of output of the abnormal power consumption process is extracted and combined with the comprehensive power consumption per ton of output of the process to construct the process-level power consumption Pareto chart of the process to locate the abnormal power consumption equipment.
[0010] Furthermore, the comprehensive electricity consumption per ton of steel in the whole process = total electricity consumption of the whole enterprise / steel output, the comprehensive electricity consumption per ton of steel at the process level = electricity consumption of the process / steel output, the comprehensive electricity consumption per ton of production at the process level = electricity consumption of the process / output of the process, and the comprehensive electricity consumption per ton of production at the equipment level = electricity consumption of the equipment / output of the process in which the equipment is located.
[0011] Furthermore, the comprehensive electricity consumption per ton of steel in the whole process is the sum of the comprehensive electricity consumption per ton of steel at each process level, and the comprehensive electricity consumption per ton of production at the process level is the sum of the comprehensive electricity consumption per ton of production at each equipment level.
[0012] Further, judging the abnormal power consumption of the process today according to the actual process-level comprehensive power consumption per ton of production and the process-level comprehensive power consumption per ton of production includes: Set constant K, which includes the upper limit (maximum value) K1 and the lower limit (minimum value) K2. Substitute K into the fitting formula: process-level comprehensive electricity consumption per ton of output = a*process output + b*K; when the actual process-level comprehensive electricity consumption per ton of output is greater than a*process output + b*K1, the electricity consumption of the process today is abnormal.
[0013] On the other hand, the present application provides a device for quickly identifying abnormal power consumption in a long-process steel enterprise, comprising: The historical data acquisition module is used to obtain the company's historical production data and extract the comprehensive power consumption per ton of steel in the entire process and the comprehensive power consumption per ton of production at the process level; The data extraction module is used to extract the comprehensive power consumption per ton of steel at the process level from the company's historical production data; extract the comprehensive power consumption per ton of production at the equipment level from the company's historical production data; The abnormal power consumption positioning module is used to determine whether the power consumption is normal through the comprehensive power consumption per ton of steel in the whole process and the comprehensive power consumption per ton of steel at the process level when the steel production is normal; if the power consumption is abnormal, the abnormal power consumption process and abnormal power consumption equipment are located by drawing a Pareto chart; The data group division module is used to divide the historical power consumption data of the enterprise's normal power consumption into several data groups according to preset conditions when the steel production is abnormal; The fitting curve drawing module is used to draw the scatter point model of the process output and the process-level comprehensive power consumption per ton in the data group, and output the fitting curve: the process-level comprehensive power consumption per ton = a*process output + b. The daily process output is brought into the fitting curve to obtain the corresponding actual process-level comprehensive power consumption per ton; The abnormal power consumption judgment module is used to judge the abnormal power consumption of the process today based on the actual process-level comprehensive power consumption per ton of production and the process-level comprehensive power consumption per ton of production; The visualization chart generation module is used to draw visualization charts through table tools, and bring the daily output and electricity consumption per ton of each process into the chart.
[0014] On the other hand, the present application provides an electronic device, the electronic device comprising a memory and at least one processor, the memory storing instructions; The at least one processor calls the instructions in the memory to enable the electronic device to execute each step of the method for quickly identifying abnormal power consumption in a long-process steel enterprise as described in any one of the above items.
[0015] On the other hand, the present application provides a computer-readable storage medium having instructions stored thereon, which, when executed by a processor, implement the various steps of the method for quickly identifying abnormal power consumption in a long-process steel enterprise as described in any of the above items.
[0016] The implementation of the present invention has the following beneficial effects: 1. When steel production is normal, this application can quickly identify processes and on-site equipment with abnormal electricity consumption by breaking down electricity consumption per ton of steel and per ton of production. When steel production is abnormal, by collecting historical data and establishing a process-level energy load curve model, it can accurately identify whether the electricity consumption indicators of each production process of a steel enterprise throughout the entire process are abnormal, thereby improving the speed and accuracy of judgment. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] Figure 1 is a flow chart of the present invention; Figure 2 It is the process energy consumption load curve model diagram; Figure 3 It is a comparison model diagram of process energy consumption load curve; Figure 4It is a schematic diagram of the structure of a device for quickly identifying abnormal power consumption in a long-process steel enterprise; Figure 5 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Example
[0019] Please refer to the instruction manual Figure 1-2 In this embodiment, a method for a long-process steel enterprise to quickly identify abnormal power consumption is provided. The method for a long-process steel enterprise to quickly identify abnormal power consumption includes: Obtain the company's historical production data and extract the comprehensive power consumption per ton of steel in the entire process and the comprehensive power consumption per ton of production at the process level; Extract the comprehensive power consumption per ton of steel at the process level from the company's historical production data; extract the comprehensive power consumption per ton of production at the equipment level from the company's historical production data; When steel production is normal, the power consumption is judged to be normal by the comprehensive power consumption per ton of steel in the whole process and the comprehensive power consumption per ton of steel at the process level; if the power consumption is abnormal, the abnormal power consumption process and abnormal power consumption equipment are located by drawing the Pareto chart method; When steel production is abnormal, the historical power consumption data of the enterprise's normal power consumption is divided into several data groups according to preset conditions; Draw a scatter point model of the process output and the process-level comprehensive power consumption per ton in the data group, and output a fitting curve: process-level comprehensive power consumption per ton = a*process output + b. Substitute the daily process output into the fitting curve to obtain the corresponding actual process-level comprehensive power consumption per ton; According to the actual process-level comprehensive power consumption per ton of output and the process-level comprehensive power consumption per ton of output, determine the abnormal power consumption of the process today; Use the table tool to draw a visual chart and include the daily output and electricity consumption per ton of each process into the chart.
[0020] It also includes: when steel production is normal, judging whether the power consumption is normal through the comprehensive power consumption per ton of steel in the entire process and the comprehensive power consumption per ton of steel at the process level; if the power consumption is normal, the company's power consumption is normal for that day.
[0021] The abnormal power consumption processes and equipment located by drawing the Pareto chart include: Build a company-level power consumption Pareto chart based on the comprehensive power consumption per ton of steel in the entire process and the comprehensive power consumption per ton of steel at the process level to locate processes with abnormal power consumption; The equipment-level comprehensive power consumption per ton of output of the abnormal power consumption process is extracted and combined with the comprehensive power consumption per ton of output of the process to construct the process-level power consumption Pareto chart of the process to locate the abnormal power consumption equipment.
[0022] The comprehensive electricity consumption per ton of steel in the whole process = total electricity consumption of the whole enterprise / steel output, the comprehensive electricity consumption per ton of steel at the process level = electricity consumption of the process / steel output, the comprehensive electricity consumption per ton of production at the process level = electricity consumption of the process / output of the process, the comprehensive electricity consumption per ton of production at the equipment level = electricity consumption of the equipment / output of the process in which the equipment is located.
[0023] The comprehensive electricity consumption per ton of steel in the whole process is the sum of the comprehensive electricity consumption per ton of steel at each process level, and the comprehensive electricity consumption per ton of production at the process level is the sum of the comprehensive electricity consumption per ton of production at each equipment level.
[0024] According to the actual process-level comprehensive power consumption per ton of output and the process-level comprehensive power consumption per ton of output, the abnormal power consumption of the process today includes: Set constant K, which includes upper limit (maximum value) K1 and lower limit (minimum value) K2. Substitute K into the fitting formula: comprehensive power consumption per ton of production at process level = a*process output + b*K; In interval 1, when the actual process-level comprehensive power consumption per ton of output is greater than a*process output+b*K1, the process is considered to have excessive power consumption today and abnormal power consumption exists; In interval 2, when a*process output + b*K1 is greater than or equal to the actual process-level comprehensive power consumption per ton, and a*process output + b is greater than the process output, the power consumption of this process is large today, and it is judged to be normal. Interval three: when a*process output + b is greater than or equal to the actual process-level comprehensive power consumption per ton greater than a*process output + b*K2, the process has qualified electricity consumption today and is judged to be normal; Interval 4: When a*process output + b*K2 is greater than or equal to the actual process-level comprehensive power consumption per ton, the power consumption of the process today is excellent and is judged to be normal; For the above four intervals, a scoring system can also be used to score the intervals to determine the electricity consumption within a period of time. For example, interval 1 is -2 points, interval 2 is -1 point, interval 3 is +1 point, and interval 4 is +2 points. Different constants K can be set for different processes. For coking and sintering, K=1±0.015 can be set; for ironmaking and steelmaking, K=1±0.03 can be set; and for steel rolling, K=1±0.05 can be set. Example
[0025] Please refer to the attached drawings of the specification. This embodiment provides a method for a long-process steel enterprise to quickly identify abnormal power consumption. Take a long-process steel enterprise as an example; 1. The comprehensive power consumption of a ton of steel in the whole process is A=450kWh / ton of steel. A is divided into B according to the production process. 1 -B n, such as the comprehensive power consumption per ton of steel for coking B 1 =20kWh / ton steel, comprehensive power consumption per ton of sintered steel B 2 =20kWh / ton steel, comprehensive power consumption per ton of steel in other processes B n . The relevant parameters meet condition B 1 -B n The sum is equal to A.
[0026] 2. The total power consumption of the coking process is divided by the output of the coking process to obtain the comprehensive power consumption per ton of coking process C = 70kWh / ton of coke. C is divided into D according to the power-consuming equipment. 1 -D n , such as the comprehensive power consumption of coking dust removal fan per ton of output D 1 =20kWh / ton of coke, comprehensive power consumption of coking circulating water pump per ton of production D 2 =10kWh / ton of coke, other equipment comprehensive power consumption per ton D n . The relevant parameters meet the condition D 1 -D n The sum is equal to C.
[0027] 3. When the comprehensive power consumption per ton of steel in the whole process is A=480kWh / ton of steel, it is judged as abnormal power consumption. Through step 1, it can be determined which processes have abnormal power consumption. Assuming that there is an abnormality in the coking process, through step 2, it can be located which energy-consuming equipment has abnormal power consumption.
[0028] 4. Since the electricity consumption per ton of steel is most affected by steel output, there are abnormalities in the comprehensive electricity consumption per ton of steel A for the entire process and the comprehensive electricity consumption per ton of steel B for each process. However, the comprehensive electricity consumption per ton of output C at the process level and the comprehensive electricity consumption per ton of output D at the equipment level are normal, and it is impossible to determine whether there are abnormalities on site.
[0029] Based on the above situation, taking the coking processes as an example, the energy consumption load curve of the coking process is constructed through historical data with days as the dimension.
[0030] 5. The historical data includes the coking output X and the daily electricity consumption of coking, and the daily comprehensive electricity consumption per ton of coke C is calculated. In order to reduce the impact of ambient temperature, the above data are divided into two groups according to winter (May-October) and summer (January-April and November-December).
[0031] 6. Perform linear fitting on the coking output X and the comprehensive electricity consumption per ton of coke C in several summer groups to obtain fitting curve 1: C=aX+b, where a is generally a negative number. If a is a positive number, it can be judged that the historical data is wrong and needs to be recalculated.
[0032] 7. Set the constant K and substitute it into the fitting formula C=aX+b*K. The constant K of the coking process is 1±0.015. Fitting curve 2: C=aX+b*1.015, fitting curve 3: C=aX+b*0.985.
[0033] The above method is more suitable when the data in the data group is less than 200 pairs. When the data in the data group is greater than 200 pairs, X can be divided into several reasonable intervals, and a different constant K is set for each interval, which can more accurately determine the power consumption.
[0034] The plane can be divided into four areas through the above three fitting curves. Figure 2 .
[0035] Interval 1: C>aX+b*1.015, Interval 2: aX+b*1.015≥C>aX+b, Interval 3: aX+b≥C>aX n +b*0.985, interval four aX+b*0.985≥C.
[0036] Substituting the daily coking output X into the fitting formula C=aX+b, we can quickly determine which range the corresponding ton coke comprehensive power consumption C is in. Range 1 is judged as very poor power consumption index, range 2 is judged as poor power consumption, range 3 is judged as qualified power consumption, and range 4 is judged as excellent power consumption.
[0037] At the same time, you can set a scoring coefficient for each interval, such as interval one is -2 points, interval two is -1 point, interval three is +1 point, and interval four is +2 points. The scoring system can be used to quickly identify electricity usage over a period of time.
[0038] When taking different data sets from the same process, different fitting curves can be obtained. Figure 3 The C process fitting curve 1 represents production mode 1, and the C process fitting curve 2 represents production mode 2. When the output of the C process is in the range of 6950-7150, the C process fitting curve 2 is significantly lower than the C process fitting curve 1, which is convenient for selecting the most suitable production mode according to different working conditions. 8. Use the spreadsheet tool to plot the above parameters and models into a visual chart, and bring the daily output and per-ton consumption of each process into the chart. This will allow you to quickly determine whether there are any abnormalities in the daily electricity consumption of each process, and ultimately determine whether there are any abnormalities in the company's electricity consumption.
[0039] The above describes the method for quickly identifying abnormal power consumption in a long-process steel enterprise in an embodiment of the present invention. The following describes the device for quickly identifying abnormal power consumption in a long-process steel enterprise in an embodiment of the present invention. Figure 4 In the embodiment of the present invention, the device for quickly identifying abnormal power consumption in a long-process steel enterprise includes: Data extraction module 401 is used to extract the comprehensive power consumption per ton of steel at the process level in the historical production data of the enterprise; extract the comprehensive power consumption per ton of production at the equipment level in the historical production data of the enterprise; The abnormal power consumption positioning module 402 is used to determine whether the power consumption is normal by using the comprehensive power consumption per ton of steel in the whole process and the comprehensive power consumption per ton of steel at the process level when the steel production is normal; if the power consumption is abnormal, the abnormal power consumption process and abnormal power consumption equipment are located by drawing a Pareto chart method; The data group division module 403 is used to divide the historical power consumption data of the enterprise's normal power consumption into several data groups according to preset conditions when the steel production is abnormal; The fitting curve drawing module 404 is used to draw a scatter point model of the process output and the process-level comprehensive power consumption per ton in the data group, and output a fitting curve: the process-level comprehensive power consumption per ton = a*process output + b, and the daily process output is brought into the fitting curve to obtain the corresponding actual process-level comprehensive power consumption per ton; The abnormal power consumption judgment module 405 is used to judge the abnormal power consumption of the process today according to the actual process-level comprehensive power consumption per ton of production and the process-level comprehensive power consumption per ton of production; The visualization chart generation module 406 is used to draw a visualization chart through a table tool, and bring the daily output and electricity consumption per ton of each process into the chart.
[0040] above Figure 4 From the perspective of modular functional entities, a device for quickly identifying abnormal power consumption in a long-process steel enterprise in an embodiment of the present invention is described in detail. The electronic equipment in an embodiment of the present invention is described in detail from the perspective of hardware processing.
[0041] Figure 5 7 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device 700 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 710 (for example, one or more processors) and a memory 720, and one or more storage media 730 (for example, one or more mass storage devices) storing application programs 733 or data 732. Among them, the memory 720 and the storage medium 730 can be temporary storage or permanent storage. The program stored in the storage medium 730 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the electronic device 700. Furthermore, the processor 710 may be configured to communicate with the storage medium 730 to execute a series of instruction operations in the storage medium 730 on the electronic device 700.
[0042] The electronic device 700 may also include one or more power supplies 740, one or more wired or wireless network interfaces 750, one or more input and output interfaces 750, and / or one or more operating systems 731, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. It will be appreciated by those skilled in the art that Figure 5 The structure of the electronic device shown does not constitute a limitation on the electronic device, and may include more or less components than shown in the figure, or combine some components, or arrange the components differently.
[0043] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of a method for quickly identifying abnormal power consumption in a long-process steel enterprise.
[0044] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, device, or unit can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.
[0045] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the whole or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.
[0046] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A method for quickly identifying abnormal power consumption in a long-process steel enterprise, characterized in that: The method for quickly identifying abnormal power consumption in a long-process steel enterprise includes: Obtain the company's historical production data and extract the comprehensive power consumption per ton of steel in the entire process and the comprehensive power consumption per ton of production at the process level; Extract the comprehensive power consumption per ton of steel at the process level from the company's historical production data; extract the comprehensive power consumption per ton of production at the equipment level from the company's historical production data; When steel production is normal, the power consumption is judged to be normal by the comprehensive power consumption per ton of steel in the whole process and the comprehensive power consumption per ton of steel at the process level; if the power consumption is abnormal, the abnormal power consumption process and abnormal power consumption equipment are located by drawing the Pareto chart method; When steel production is abnormal, the historical power consumption data of the enterprise's normal power consumption is divided into several data groups according to preset conditions; Draw a scatter point model of the process output and the process-level comprehensive power consumption per ton in the data group, and output a fitting curve: process-level comprehensive power consumption per ton = a*process output + b. Substitute the daily process output into the fitting curve to obtain the corresponding actual process-level comprehensive power consumption per ton; According to the actual process-level comprehensive power consumption per ton of output and the process-level comprehensive power consumption per ton of output, determine the abnormal power consumption of the process today; Use the table tool to draw a visual chart and include the daily output and electricity consumption per ton of each process into the chart.
2. The method for quickly identifying abnormal power consumption in a long-process steel enterprise according to claim 2 is characterized in that: Also includes: When steel production is normal, the power consumption is judged to be normal through the comprehensive power consumption per ton of steel in the whole process and the comprehensive power consumption per ton of steel at the process level; If the power consumption is normal, then the enterprise’s power consumption is normal for the day.
3. The method for quickly identifying abnormal power consumption in a long-process steel enterprise according to claim 1, characterized in that: The method of locating abnormal power consumption processes and abnormal power consumption equipment by drawing a Pareto diagram includes: Build a company-level power consumption Pareto chart based on the comprehensive power consumption per ton of steel in the entire process and the comprehensive power consumption per ton of steel at the process level to locate processes with abnormal power consumption; The equipment-level comprehensive power consumption per ton of output of the abnormal power consumption process is extracted and combined with the comprehensive power consumption per ton of output of the process to construct the process-level power consumption Pareto chart of the process to locate the abnormal power consumption equipment.
4. The method for quickly identifying abnormal power consumption in a long-process steel enterprise according to claim 3 is characterized in that: The comprehensive electricity consumption per ton of steel in the whole process = total electricity consumption of the whole enterprise / steel output, comprehensive electricity consumption per ton of steel at the process level = electricity consumption of the process / steel output, comprehensive electricity consumption per ton of production at the process level = electricity consumption of the process / output of the process, comprehensive electricity consumption per ton of production at the equipment level = electricity consumption of the equipment / output of the process in which the equipment is located.
5. The method for quickly identifying abnormal power consumption in a long-process steel enterprise according to claim 4, characterized in that: The comprehensive electricity consumption per ton of steel in the entire process is the sum of the comprehensive electricity consumption per ton of steel at each process level, and the comprehensive electricity consumption per ton of production at the process level is the sum of the comprehensive electricity consumption per ton of production at each equipment level.
6. The method for quickly identifying abnormal power consumption in a long-process steel enterprise according to claim 5, characterized in that: The abnormal power consumption of the process today according to the actual process-level comprehensive power consumption per ton of production and the process-level comprehensive power consumption per ton of production includes: Set constant K, which includes the upper limit (maximum value) K1 and the lower limit (minimum value) K2. Substitute K into the fitting formula: process-level comprehensive electricity consumption per ton of output = a*process output + b*K; when the actual process-level comprehensive electricity consumption per ton of output is greater than a*process output + b*K1, the electricity consumption of the process today is abnormal.
7. A device for quickly identifying abnormal power consumption in a long-process steel enterprise, used in the method for quickly identifying abnormal power consumption in a long-process steel enterprise as claimed in any one of claims 1 to 6, characterized in that: The device for quickly identifying abnormal power consumption in a long-process steel enterprise includes: The historical data acquisition module is used to obtain the company's historical production data and extract the comprehensive power consumption per ton of steel in the entire process and the comprehensive power consumption per ton of production at the process level; The data extraction module is used to extract the comprehensive power consumption per ton of steel at the process level from the company's historical production data; extract the comprehensive power consumption per ton of production at the equipment level from the company's historical production data; The abnormal power consumption positioning module is used to determine whether the power consumption is normal through the comprehensive power consumption per ton of steel in the whole process and the comprehensive power consumption per ton of steel at the process level when the steel production is normal; if the power consumption is abnormal, the abnormal power consumption process and abnormal power consumption equipment are located by drawing a Pareto chart; The data group division module is used to divide the historical power consumption data of the enterprise's normal power consumption into several data groups according to preset conditions when the steel production is abnormal; The fitting curve drawing module is used to draw the scatter point model of the process output and the process-level comprehensive power consumption per ton in the data group, and output the fitting curve: the process-level comprehensive power consumption per ton = a*process output + b. The daily process output is brought into the fitting curve to obtain the corresponding actual process-level comprehensive power consumption per ton; The abnormal power consumption judgment module is used to judge the abnormal power consumption of the process today based on the actual process-level comprehensive power consumption per ton of production and the process-level comprehensive power consumption per ton of production; The visualization chart generation module is used to draw visualization charts through table tools, and bring the daily output and electricity consumption per ton of each process into the chart.
8. An electronic device, comprising a memory and at least one processor, wherein instructions are stored in the memory; The at least one processor calls the instructions in the memory to enable the electronic device to execute each step of the method for quickly identifying abnormal power consumption in a long-process steel enterprise as described in any one of claims 1-6.
9. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the steps of the method for quickly identifying abnormal power consumption in a long-process steel enterprise as described in any one of claims 1-6 are implemented.