CN115983582A - Data analysis method and energy consumption management system - Google Patents
Data analysis method and energy consumption management system Download PDFInfo
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Abstract
The invention provides a data analysis method and an energy consumption management system, and belongs to the technical field of energy consumption management. The invention comprises the following steps: periodically extracting energy consumption data of energy using the determined energy type or energy name, and periodically extracting production data obtained in the production process of the production process, the production department and the production module; comparing the acquired data with the data in the data source, and if the acquired data is different from the data in the data source, executing data acquisition again until data synchronization is achieved; and carrying out data cleaning, data sorting, data modeling and data analysis on the synchronized data. The invention adopts a data analysis method to realize the high-efficiency management of energy consumption, can intuitively know various energy consumption conditions of different products of an enterprise, master production data and trends such as product yield, total output and the like, and ensure that the enterprise can carry out energy consumption management according to preset requirements.
Description
Technical Field
The invention relates to the technical field of energy consumption management, in particular to a data analysis method and an energy consumption management system.
Background
The enterprise comprehensive energy efficiency management system is an enterprise management system which is developed by combining an informatization technology and energy consumption management aiming at industrial production enterprises, and mainly provides a whole set of solution for energy consumption management, electric energy quality and energy consumption safety monitoring for the enterprises. But there is no energy consumption management system developed for customer needs at present.
Chinese patent CN105654393A discloses an energy efficiency management service system for a power distribution network park, and the functional modules of the system mainly comprise six primary functional modules of distribution network data acquisition and monitoring, distribution network analysis and control, distribution network automation, energy efficiency management, distribution network equipment evaluation and energy consumption optimization; the energy efficiency management module comprises six secondary function modules, namely energy consumption data acquisition, energy consumption data statistics, energy consumption data analysis, energy consumption data evaluation, energy consumption early warning and energy consumption prediction; the distribution network equipment evaluation module has various energy consumption evaluation standards and is used for periodically evaluating the total energy consumption level, the subareas, the item-dividing energy consumption level and the equipment energy consumption condition of a production line and a building; carrying out correlation analysis of multi-dimensional information by using distribution network monitoring information, enterprise energy consumption information and production information, and providing intelligent service for monitoring and analysis of a distribution network and energy efficiency management of a park; however, when the energy consumption information and the production information are used for analysis, data are not synchronously processed, and the real-time performance of the data cannot be guaranteed.
Chinese patent CN114584574B discloses a data synchronization method, apparatus, computer device and storage medium, which pull a database log of an index database in real time through a log pull component, and analyze index information of data to be synchronized from the database log; acquiring node state information of each server node in a plurality of server nodes, and determining a plurality of data types and data capacity of each data type; extracting target file data from the file storage server according to the index information, the file attribute information, the plurality of data types and the data capacity; although the real-time performance of data synchronization can be improved, a log pull component needs to be designed to pull data in a database in real time.
Disclosure of Invention
In order to solve the technical problems in the prior art, the invention provides a data analysis method and an energy consumption management system, which extract energy consumption data of energy at regular time and extract production data obtained by production processes, production departments and production modules in the production process at regular time by determining the energy using the energy type or the energy name; comparing the extracted data with the data in the data source, and if the extracted data is different from the data in the data source, executing the steps again until the data synchronization is achieved; and carrying out data cleaning, data sorting, data modeling and data analysis on the synchronized data. The invention realizes the high-efficiency management of energy consumption, can also intuitively know the energy consumption conditions of different products of an enterprise, master the production data and trends such as product yield, total output value and the like, and lead the enterprise to carry out the energy consumption management according to the requirement of the national 'double-carbon' policy.
The invention provides a data analysis method, which comprises the following steps: determining target data, extracting data at fixed time, synchronizing data and processing data;
target data determination: determining the type and name of energy to be collected, and determining the production process, production department and production module involved in the production process;
and a data timing extraction step: determining energy using the energy type or the energy name, extracting energy consumption data of the determined energy at regular time, and extracting production data obtained in the production process of the production process, the production department and the production module at regular time;
and a data synchronization step: comparing the extracted data with the data in the data source, and if the extracted data is different from the data in the data source, executing the steps again until the data synchronization is achieved;
and (3) data processing: and carrying out data cleaning, data sorting, data modeling and data analysis on the synchronized data.
Preferably, the production data includes product yield, industry increment value, and industry gross value.
Preferably, the indicators of the energy consumption data and the production data specifically include: the value of the data, the value validity identification, the data type and the data source.
Preferably, the data synchronization step specifically includes the following steps:
and comparing the regularly extracted data with data in a data source of the end equipment to ensure that the extracted data is the latest data, and if the comparison is unsuccessful, performing the regularly extracted data again.
Preferably, the data synchronization step specifically includes the following steps:
comparing the latest data in the acquisition time field in the data table extracted at regular time with the latest data in the acquisition time field in the data table in the end equipment, and if the time is the same, entering a data processing step; if the time is different, the data extraction is carried out again, and the data extracted before is deleted.
Preferably, the data processing step specifically includes the steps of:
a data cleaning step: deleting abnormal data in the energy consumption data and the production data; the abnormal data comprises data with negative numerical value, error identification of numerical value validity, abnormal data type and abnormal data source;
data arrangement: carrying out data classification on the cleaned data and carrying out data sorting according to the selected fields;
a data modeling step: establishing an energy consumption data management model and a production data management model;
and (3) data analysis step: and analyzing the energy consumption data by using the energy consumption data management model, and analyzing the production data by using the production data management model.
Preferably, the data cleansing specifically includes:
deleting data with invalid data validity field;
deleting data which does not meet the requirements of the data acquisition source, the data acquisition frequency and the data acquisition range field;
data whose field data value is negative is deleted.
Preferably, the cleaned data is reordered according to the collection time rule in the data processing.
Preferably, the energy consumption data analysis is specifically: analyzing energy consumption panorama, energy consumption trend, energy consumption monitoring condition and energy consumption composition structure; the production data analysis specifically comprises: and analyzing the product yield, the industrial increment value and the industrial total yield value to obtain the production trend.
Preferably, the energy consumption data and the production data support one or more of SQL, OPC, modbus, DL/T645 and CJ/T188 protocols.
Preferably, the method further comprises the step of data visualization: the data visualization processing specifically comprises: and real-time monitoring and displaying the energy consumption data in a chart form.
The invention provides an energy consumption management system, which adopts any data analysis method to carry out energy consumption management, and comprises the following steps: the energy consumption monitoring system comprises data acquisition equipment, an energy consumption monitoring module and an energy consumption management module;
the data acquisition equipment, the energy consumption monitoring module and the energy consumption management module are connected through the Internet;
the data acquisition equipment determines the type and name of energy to be acquired and production procedures, production departments and production modules involved in the production process, determines the energy using the type or name of the energy, extracts the energy consumption data of the determined energy at regular time and obtains the production data of the production procedures, the production departments and the production modules in the production process;
the energy consumption monitoring module compares the extracted data with data in a data source, if the extracted data is different from the data in the data source, the steps are executed again until the data synchronization is achieved, and then data cleaning and data arrangement are carried out;
and the energy consumption management module performs data modeling and data analysis on the sorted data.
Preferably, the data acquisition device comprises data acquisition means; and the data acquisition tool extracts the energy consumption data of the energy at regular time and the production data obtained in the production process of the production process, the production department and the production module.
Preferably, the extraction frequency of the data timing extraction is determined according to the data acquisition frequency of the data acquisition tool and the design requirement of the energy consumption management module.
Preferably, the energy consumption monitoring module comprises a data access execution module and a data processing module; the data access execution module receives energy consumption data and production data, the data processing module compares the extracted data with data in the data source until the data are synchronous, and then the data are cleaned and sorted and transmitted to the energy consumption management module.
Preferably, the energy consumption management module comprises an energy consumption management function module and a production management function module; the energy consumption management function module establishes an energy consumption data management model and carries out energy consumption data analysis according to the energy consumption data management model; and the production management functional module establishes a production data management model and carries out production data analysis according to the production data management model.
Preferably, the energy consumption data analysis is specifically: analyzing energy consumption panorama, energy consumption trend, energy consumption monitoring condition and energy consumption composition structure; the production data analysis specifically comprises: product yield, industry increment value, industry gross value and production trend were analyzed.
Preferably, the energy consumption management module performs data visualization processing on the sorted data.
Compared with the prior art, the invention has the following beneficial effects:
1. the data analysis method adopts a data synchronization step, compares the acquired data with the data in the data source, and if the acquired data is different from the data in the data source, executes the data acquisition step again until the data synchronization is achieved; the latest data is ensured, and the real-time performance of the data is ensured.
2. The data analysis method adopts a data cleaning step to delete abnormal data in the energy consumption data and the production process data; the abnormal data comprises data with negative numerical value, error identification of numerical value validity, abnormal data type and abnormal data source; abnormal, blank, invalid and repeated data are eliminated, the problem of insufficient system computing capacity caused by huge data quantity and complex data types acquired by an intelligent acquisition tool is solved, the abnormal, blank, invalid and repeated data are eliminated, a decision maker can conveniently and rapidly mine effective information from complex, large and multidimensional energy consumption and production data, and the decision efficiency of a user is improved; the system operation speed is improved, and the system timeliness is guaranteed.
3. The energy consumption management system comprises data acquisition equipment, an energy consumption management module and a production management module; the energy consumption management module establishes an energy consumption data management model and carries out energy consumption data analysis according to the energy consumption data management model; the production management module establishes a production data management model and carries out production data analysis according to the production data management model; the system can help customers to obtain an energy consumption and production business view with rich and comprehensive data; the method has a user-friendly interface and a service application program, so that a non-technical user can acquire more accurate and timely information.
Drawings
FIG. 1 is a flow chart of one embodiment of a data analysis method of the present invention;
FIG. 2 is a flow chart of another embodiment of a data analysis method of the present invention;
FIG. 3 is a block diagram of an embodiment of an energy management system of the present invention;
FIG. 4 is a block diagram of an embodiment of an energy management platform of an energy management system of the present invention.
Detailed Description
The following describes a specific embodiment of a data analysis method and an energy consumption management system according to the present invention in detail with reference to fig. 1-4.
Example 1
Referring to fig. 1, the data analysis method of the present invention will be described in detail below, according to an embodiment of the present invention.
The invention provides a data analysis method, which comprises the following steps: determining target data, extracting data at fixed time, synchronizing data and processing data;
target data determination: determining the type and name of energy to be collected, and determining the production process, production department and production module involved in the production process;
and a data timing extraction step: determining the energy using the energy type or the energy name, extracting energy consumption data of the energy at regular time, and extracting production data obtained in the production process of the production process, the production department and the production module at regular time;
and a data synchronization step: comparing the extracted data with the data in the data source, and if the extracted data is different from the data in the data source, executing the steps again until data synchronization is achieved;
a data processing step: and carrying out data cleaning, data sorting, data modeling and data analysis on the synchronized data.
Example 2
Referring to fig. 2, the data analysis method of the present invention will be described in detail below, according to an embodiment of the present invention.
The invention provides a data analysis method, which comprises the steps of target data determination, data timing extraction, data synchronization, data cleaning, data sorting, data modeling and data visualization;
a target data determination step: determining the type and name of energy to be collected, and determining the production process, production department and production module involved in the production process; taking the collected data as an example, fields included in a table for storing the collected data model include a primary key ID, a data name (data _ name), a data code (data _ code), a data value (data _ value), a collection time (stat _ data), a data collection source (input _ type), a data collection frequency (stat _ type), a data validity (valid), a data collection range (scope), and the like; the data format of the data coding field is 'XX-XX-XX-XXXXXXX-XX', and the data coding field is used for distinguishing production procedures, procedure units, key energy consumption equipment types, key energy consumption equipment numbers, acquisition object types, energy classification items and application codes. The data coding refers to the national standard of the standard, the type and name of the energy to be collected, the related process, department, module and other information are determined, and the target data can be determined through the data coding.
And a data timing extraction step: determining the type and name of energy to be collected, extracting energy consumption data of the determined energy at regular time, and extracting production data obtained in the production process of the production process, the production department and the production module at regular time; wherein the production data comprises product yield, industry increment value and industry total output value; the indexes of the energy consumption data and the production process data specifically comprise: the value, the value validity identification, the data type and the data source of the data; the acquisition frequency is determined according to the data acquisition frequency of an intelligent acquisition tool and the design requirement of a platform for data acquisition; the step of extracting the data at regular time specifically comprises the following steps:
data timing extraction: and extracting energy consumption data from the end equipment according to the requirements, wherein the acquisition frequency is comprehensively determined according to the data acquisition frequency and the design requirements of the field acquisition tool in the figure 1.
And a data synchronization step: comparing the acquired data with the data in the data source, and if the acquired data are different from the data in the data source, executing the steps again until data synchronization is achieved; the data synchronization step specifically comprises the following steps:
comparing the regularly extracted data with data in a data source of the end equipment to ensure that the extracted data is the latest data, and if the comparison is unsuccessful, executing the regularly extracted data again;
in this embodiment, the data synchronization step specifically includes the following steps:
comparing the latest data in the acquisition time field in the data table extracted at regular time with the latest data in the acquisition time field in the data table in the end equipment, and if the time is the same, entering a data processing step; if the time is different, data extraction is carried out again, and the data extracted before is deleted.
A data cleaning step: deleting abnormal data in the energy consumption data and the production data; the abnormal data comprises data with negative numerical values, error numerical value validity identification, abnormal data types and abnormal data sources;
the data cleaning specifically comprises the following steps:
deleting data whose data validity (valid) field is invalid;
deleting data with fields of data acquisition source (input _ type), data acquisition frequency (stat _ type) and data acquisition range (scope) which do not meet requirements;
data whose field data value is negative is deleted.
In this embodiment, the cleaned data is reordered according to the acquisition time as a rule in the data processing.
Data arrangement: carrying out data classification on the cleaned data and carrying out data sorting according to the selected fields;
a data modeling step: establishing an energy consumption data management model and a production data management model; taking power consumption data as an example, the power consumption data includes power consumption and total power consumption values of each process, all data with power characteristics (codes of energy classification items in data codes are 023300) in the data with data codes are screened out, reordering is carried out according to a collection time (stat _ data) as a rule, and the power consumption value of each hour, day, month or each time period can be obtained by classification calculation according to the time characteristics (collection time) of the data. Similarly, data models for different types of energy sources can be established by using the characteristics of the data.
And (3) data analysis step: analyzing the energy consumption data by using the energy consumption data management model, and analyzing the production data by using the production data management model;
data visualization step: and real-time monitoring and displaying the energy consumption data in a chart form. The specific implementation manner of data visualization is as follows: the front end of the software adopts the element UI framework component, the API method and attribute encapsulation of the element UI framework component are complete, and the method has the advantage of excellent visual design. According to the invention, the energy consumption management system can display the consumption trend and the comparison of various energy sources by utilizing the visualization function.
Wherein, the energy consumption data and the production data support one or more of SQL, OPC, modbus, DL/T645 and CJ/T188 protocol.
Example 3
Referring to fig. 3-4, the energy consumption management system of the present invention is described in detail below, according to one embodiment of the present invention.
The invention provides an energy consumption management system, which uses any data analysis method to carry out energy consumption management, and comprises the following steps: the energy consumption monitoring system comprises data acquisition equipment, an energy consumption monitoring module and an energy consumption management module; the data acquisition equipment, the energy consumption monitoring module and the energy consumption management module are connected through the internet.
The data acquisition equipment comprises a data acquisition tool, an energy type and an energy name which need to be acquired, and a production process, a production department and a production module which are involved in the production process are determined, then the energy using the energy type or the energy name is determined, the data acquisition tool extracts energy consumption data of the determined energy at regular time, and production data obtained by the production process, the production department and the production module in the production process are transmitted to the energy consumption monitoring module; the extraction frequency of the data timing extraction is determined according to the data acquisition frequency of the data acquisition tool and the design requirement of the energy consumption management module.
The energy consumption monitoring module comprises a data access execution module and a data processing module; the data access execution module receives the energy consumption data and the production data, the data processing module compares the extracted data with the data in the data source until the data are synchronous, and then the data are cleaned and sorted and transmitted to the energy consumption management module.
The energy consumption management module comprises an energy consumption management function module and a production management function module; the energy consumption management function module establishes an energy consumption data management model and carries out energy consumption data analysis according to the energy consumption data management model; the production management function module establishes a production data management model and carries out production data analysis according to the production data management model; and then, real-time monitoring and displaying the energy consumption data in a chart form according to the energy consumption profile and trend of the client.
The energy consumption data management model stores a table of acquired energy consumption data, and the table comprises fields including a main key ID, a data name (data _ name), a data code (data _ code), a data value (data _ value), acquisition time (stat _ data), a data acquisition source (input _ type), data acquisition frequency (stat _ type), data validity (valid), a data acquisition range (scope), and the like, wherein the data format of the data code field is XX-XX-XX-XXXXXXXXXXXXX-XXX used for distinguishing production processes, process units, key energy consumption equipment types, key energy consumption equipment numbers, acquisition object types, energy classification items, and application codes. The data coding refers to the national standard of the standard, the type and name of the energy to be collected, the related process, department, module and other information are determined, and the target data can be determined through the data coding. The types of energy consumption data in the invention comprise: solid fuel, coke breeze, electricity, natural gas, and the like.
The energy consumption data analysis process comprises the following steps: taking a solid fuel as an example, the data code (data _ code) is '00-00-0000-023900-11', in the invention, data with the data code meeting the requirement is extracted, the data of a certain day is determined according to the acquisition time (stat _ data) (in the invention, data is acquired once in 15 minutes by default), and the data in the day is accumulated to obtain the solid fuel consumption data of the day. By selecting a date range, solid fuel consumption for a week or month may be analyzed. With the same method, energy consumption data (nut coke, electricity, natural gas, etc.) of other energy sources can be analyzed. Energy consumption data and energy consumption trend data of various energy sources in the period can be obtained by calculating and analyzing the energy consumption data of the selected period, and the energy consumption panorama, the energy consumption trend, the energy consumption condition monitoring and the energy consumption composition structure displaying are completed in a chart form by utilizing a platform visualization technology.
The table for storing the collected production data in the production data management model includes fields such as a primary key ID, a data name (data _ name), a data code (data _ code), a data value (data _ value), a collection time (stat _ data), a data collection source (input _ type), a data collection frequency (stat _ type), a data validity (valid), and a data collection range (scope). The data format of the data coding field is 'XX-XX-XX-XXXXXXXX-XX', and the data coding field is used for distinguishing production procedures, procedure units, important energy consumption equipment types, important energy consumption equipment numbers, acquisition object types, classification items and application codes. The data coding refers to the national standard of the standard, the type and name of the production data to be collected, the related process, department, module and other information are determined, and the target data can be determined through the data coding. The production data types related in the invention comprise total steel amount, industrial production value, ton steel comprehensive energy consumption and the like.
The production data analysis process comprises the following steps: taking the total amount of steel as an example, the data _ code is '00-00-0000-040200-71', in the invention, data meeting the requirement of the data code is extracted, data of a certain day is determined according to the acquisition time (stat _ data) (in the invention, data are acquired once in 15 minutes by default), and the data in the day are accumulated to obtain the total amount of steel on the day. By selecting the date range, the total amount of steel for a week or month can be analyzed. Other types of production data may be analyzed using the same method. And calculating and analyzing the production data of the selected period to obtain basic data of various energy consumption values in the period, and displaying the product yield, the industrial added value, the industrial total output value and the production trend in a chart form by utilizing a platform visualization technology.
The energy consumption data analysis specifically comprises the following steps: analyzing the energy consumption panorama, the energy consumption trend, the energy consumption monitoring condition and the energy consumption composition structure; the production data analysis specifically comprises: product yield, industry increment value, industry gross value and production trend were analyzed.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (18)
1. A method of data analysis, comprising: determining target data, extracting data at fixed time, synchronizing data and processing data;
target data determination: determining the type and name of energy to be collected, and determining the production process, production department and production module involved in the production process;
and a data timing extraction step: determining the energy using the energy type or the energy name, extracting energy consumption data of the determined energy at regular time, and extracting production data obtained in the production process of the production process, the production department and the production module at regular time;
and a data synchronization step: comparing the extracted data with the data in the data source, and if the extracted data is different from the data in the data source, executing the steps again until the data synchronization is achieved;
and (3) data processing: and carrying out data cleaning, data sorting, data modeling and data analysis on the synchronized data.
2. The method of claim 1, wherein the production data includes product yield, industry increment value, and industry gross value.
3. The data analysis method according to claim 1, wherein the indicators of the energy consumption data and the production data specifically comprise: the value of the data, the value validity identification, the data type and the data source.
4. The data analysis method according to claim 3, wherein the data synchronization step specifically comprises the steps of:
and comparing the regularly extracted data with data in a data source of the end equipment to ensure that the extracted data is the latest data, and if the comparison is unsuccessful, performing the regularly extracted data again.
5. The data analysis method according to claim 4, wherein the data synchronization step specifically comprises the steps of:
the latest data in the acquisition time field in the data table extracted regularly is compared with the latest data in the acquisition time field in the data table in the end equipment, and if the time is the same, the data processing step is carried out; if the time is different, the data extraction is carried out again, and the data extracted before is deleted.
6. The data analysis method according to claim 3, wherein the data processing step specifically comprises the steps of:
data cleaning: deleting abnormal data in the energy consumption data and the production data; the abnormal data comprises data with negative numerical values, error numerical value validity identification, abnormal data types and abnormal data sources;
data arrangement: carrying out data classification on the cleaned data and carrying out data sorting according to the selected fields;
modeling data: establishing an energy consumption data management model and a production data management model;
and (3) data analysis: and analyzing the energy consumption data by using the energy consumption data management model, and analyzing the production data by using the production data management model.
7. The data analysis method of claim 6, wherein the data cleansing specifically comprises:
deleting data with invalid data validity field;
deleting data of which the data acquisition source, the data acquisition frequency and the data acquisition range field do not meet the requirements;
data whose field data value is negative is deleted.
8. A method according to claim 6, wherein the cleaned data is reordered according to the collection time rules in the data conditioning.
9. The data analysis method according to claim 6, wherein the energy consumption data analysis is specifically: analyzing energy consumption panorama, energy consumption trend, energy consumption detection condition and energy consumption composition structure; the production data analysis specifically comprises: and analyzing the product yield, the industrial increment value and the industrial total yield value to obtain the production trend.
10. A data analysis method according to claim 1, wherein the energy consumption data and production data support one or more of SQL, OPC, modbus, DL/T645 and CJ/T188 protocols.
11. A method of data analysis according to claim 1, further comprising the step of data visualization: the data visualization processing specifically comprises: and real-time monitoring and displaying the energy consumption data in a chart form.
12. An energy consumption management system for performing energy consumption management by using the data analysis method according to any one of claims 1 to 11, comprising: the energy consumption monitoring system comprises data acquisition equipment, an energy consumption monitoring module and an energy consumption management module;
the data acquisition equipment, the energy consumption monitoring module and the energy consumption management module are connected through the Internet;
the method comprises the steps that a data acquisition device determines the type and name of energy to be acquired and production processes, production departments and production modules involved in the production process, determines the energy using the type or name of the energy, and extracts energy consumption data of the energy at regular time and production data obtained by the production processes, the production departments and the production modules in the production process;
the energy consumption monitoring module compares the extracted data with data in a data source, if the extracted data is different from the data in the data source, the steps are executed again until the data synchronization is achieved, and then data cleaning and data arrangement are carried out;
and the energy consumption management module performs data modeling and data analysis on the sorted data.
13. The energy consumption management system of claim 12, wherein the data collection device comprises a data collection tool; and the data acquisition tool extracts the energy consumption data of the energy at regular time and the production data obtained by the production process, the production department and the production module in the production process.
14. The energy consumption management system of claim 13, wherein the extraction frequency of the data extraction is determined according to the data collection frequency of the data collection tool and the design requirement of the energy consumption management module.
15. The system according to claim 12, wherein the energy consumption monitoring module comprises a data access execution module and a data processing module; the data access execution module receives the energy consumption data and the production data, the data processing module compares the extracted data with data in a data source until the data are synchronous, and then the data are cleaned and arranged and then transmitted to the energy consumption management module.
16. The energy consumption management system according to claim 15, wherein the energy consumption management module comprises an energy consumption management function module and a production management function module; the energy consumption management function module establishes an energy consumption data management model, and performs energy consumption data analysis according to the energy consumption data management model; and the production management functional module establishes a production data management model and carries out production data analysis according to the production data management model.
17. The energy consumption management system according to claim 12, wherein the energy consumption data analysis specifically is: analyzing energy consumption panorama, energy consumption trend, energy consumption monitoring condition and energy consumption composition structure; the production data analysis specifically comprises: product yield, industry increment value, industry total output value and production trend are analyzed.
18. The energy consumption management system according to claim 12, wherein the energy consumption management module performs data visualization processing on the sorted data.
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