CN113467296A - Method for analyzing and improving energy efficiency of magnesite industry - Google Patents
Method for analyzing and improving energy efficiency of magnesite industry Download PDFInfo
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Abstract
The invention provides a method for analyzing and improving energy efficiency in the magnesite industry. The data acquisition module acquires energy consumption data and energy consumption quality data of the energy efficiency monitoring area, sends the original data to the data acquisition terminal and uploads the original data to the data service center. The data service center calculates, classifies, counts, builds and stores the data; creating user management data by combining information such as enterprises and equipment files; the energy efficiency monitoring center carries out comprehensive monitoring, analysis and diagnosis on the energy use condition of the monitored area through data provided by the data service center. By carrying out real-time data acquisition and online monitoring on the operation condition of the whole production period, the operation state of equipment and the like, the comprehensive perception of enterprise energy consumption and energy consumption is realized, and the technical means of big data statistical analysis is combined and applied, so that the generation efficiency is improved and the production cost of enterprises is reduced.
Description
Technical Field
The invention relates to the technical field of energy management, in particular to a method for analyzing and improving energy efficiency in the magnesite industry.
Background
With the development of our country from energy-intensive economy to energy-saving economy, energy consumption supervision for industrial enterprises becomes an important means in the process of economic transformation. At present, magnesite industry enterprises generally have the problems of large energy consumption and energy waste in the production process, and the reasons for the problems are mainly that no reliable technical means is available to support monitoring and management of industrial energy consumption, and no energy consumption evaluation system suitable for the enterprises is established, so that the unfavorable situations that energy consumption is difficult to monitor, the energy-saving effect is difficult to evaluate and energy-saving transformation is difficult to carry out are caused. Traditional energy consumption statistics and management mode often can only be carried out through the manual work to the audit of electricity, water, heat, coal, oil lamp energy cost document, and the shortcoming of this kind of statistics lies in: 1. the global energy utilization condition can not be mastered at any time; 2. lack of persistence: statistics are carried out every year, and a long-term effective monitoring system is lacked; 3. management is performed through human experience, and scientificity and accuracy are lacked. The defects cause inaccuracy of energy consumption data statistics, so that the energy utilization characteristics of an enterprise cannot be completely described, and more bases cannot be provided for work such as energy audit, energy consumption analysis and diagnosis and the like.
The magnesite mineral resources in China are rich, the industry is prosperous, but the magnesite industry in China is always in a development stage with high energy consumption due to the problems of extensive energy management, more potential safety hazards of equipment and the like. Therefore, an effective energy efficiency monitoring and analyzing technology is needed to improve the energy utilization efficiency of the magnesite industry and realize the energy management optimization of the magnesite industry, so that the production cost of enterprises is reduced.
Disclosure of Invention
In order to solve the technical problems in the background art, the invention provides a method for analyzing and improving the energy efficiency of the magnesite industry, which realizes the comprehensive perception of the energy consumption and the energy consumption of an enterprise by acquiring and monitoring the running condition of the whole production period, the running state of equipment and the like in real time, and finally achieves the purposes of improving the generation efficiency and reducing the production cost of the enterprise by combining the technical means of big data statistical analysis. Meanwhile, the national policy call for energy conservation, emission reduction and green development is made.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for analyzing and improving energy efficiency in the magnesite industry is realized by the following system, and comprises the following steps: the system comprises a data acquisition module, a data service center and an energy efficiency monitoring center.
The data acquisition module consists of a data acquisition unit and a data acquisition terminal, the data acquisition unit acquires energy consumption data and energy consumption quality data of the energy efficiency monitoring area and sends the original data to the data acquisition terminal, and the data acquisition terminal preprocesses the received original data and uploads the processed data to the data service center through the Internet or a private enterprise network according to a specified format.
The data service center calculates, classifies, counts, establishes files and stores the data uploaded by the data acquisition module; and (3) creating user management data by combining information such as enterprises and equipment files, summarizing all data, and then establishing an energy efficiency management database to provide data support for a data query and energy efficiency monitoring center.
The energy efficiency monitoring center comprehensively monitors, analyzes and diagnoses the energy use condition of a monitored area through data provided by the data service center; establishing an energy efficiency analysis algorithm model combining enterprise scale, energy types and production process characteristics, and realizing preventive maintenance functions such as real-time online energy consumption monitoring, energy consumption fault early warning and energy consumption quality early warning; according to the energy efficiency analysis result, automatically diagnosing the abnormal or fault reason, generating a repair or improvement measure suggestion, outputting an energy efficiency analysis report, and transmitting the analysis result data and the report data to a data service center for archiving and storing to obtain historical data.
Furthermore, the system comprises a data acquisition layer, a data operation layer, a data query layer and a statistical analysis layer; the data acquisition layer completes the acquisition of energy consumption and production related data by protocol butt joint of the intelligent energy meter and the automatic system data port equipment, supports modes such as manual input and the like to acquire required data, and uploads the acquired data to the data operation layer; the data operation layer is responsible for processing the uploaded energy consumption data, counting energy consumption, accounting energy consumption cost and the like, storing and managing energy consumption equipment files, alarm records, maintenance records and energy consumption records, and providing a data source for the data query layer; the data query layer documents various energy consumption data and generates various energy consumption statistical reports after performing classification calculation according to time periods, units, processes, lines, finance and the like according to the data provided by the data operation layer, provides query at any time and provides data support for the statistical analysis layer; after the data query layer data is acquired, the statistical analysis layer comprehensively displays the energy consumption analysis data, the diagnosis evaluation data, the early warning data and the like in the form of a portal and a statistical chart, and issues the acquired information, the analysis diagnosis information and the decision information in real time or at regular time.
Further, the method comprises a data acquisition method, which specifically comprises the following steps:
compiling automatic acquisition tasks according to the requirements of different services on the acquired data, wherein the automatic acquisition tasks comprise task names, task types, acquisition groups, acquired data items, task execution starting and ending time, acquisition periods, execution priorities and normal acquisition supplementing frequency information, managing the execution of various acquisition tasks and checking the task execution condition;
1) collecting data type items
The data items collected by the system include:
electric energy data: the total electric energy indicating value, each rate electric energy indicating value, the total electric energy, each rate electric energy and the maximum demand;
alternating current analog quantity: voltage, current, active power, reactive power, power factor;
working condition data: collecting working condition information of a terminal and metering equipment;
statistical data of power quality out-of-limit: out-of-limit statistical data such as voltage, current, power factor, harmonic wave and the like;
event record data: event record data recorded by the terminal and the electric energy meter;
other data: cost control information;
2) collection mode
a) Timed auto-acquisition
Automatically acquiring terminal data according to a time interval set by an acquisition task, wherein the time, interval, content and object of automatic acquisition can be set; when the timing automatic data acquisition fails, the master station should have automatic and manual complementary acquisition functions to ensure the integrity of data;
b) random call and test
Manually calling and testing data at any time according to actual needs; if the event alarm occurs, important data related to the event is recalled and tested immediately for event analysis;
c) active reporting
In the data transmission of the full-duplex channel and the data exchange network channel, allowing a terminal to start a data transmission process, namely active reporting for short, immediately reporting an important event to a master station, and reporting data to the master station at regular time according to the set of a regular sending task; the master station should support the collection and processing of actively reported data.
Further, the method also comprises the following steps:
1) harmonic analysis
The harmonic data of key equipment is acquired through energy consumption terminal acquisition equipment and uploaded to a platform for analysis, and the serious harmonic condition can be automatically marked and early warned; an energy-saving expert gives improvement suggestions aiming at problems;
2) energy prediction
Historical and real-time data in the energy big data are used, the operation characteristics, natural conditions and the like of the system are combined, multi-time scale prediction of different loads is realized through preprocessing of load data, day-ahead, day-in-day hour-level and real-time minute-level cold, heat and electricity load prediction of a user energy system is realized, a scheduling plan of the multi-energy flow system in day-ahead, day-in-day and real-time different time scales is arranged, meanwhile, support is provided for safety analysis of the multi-energy flow system, and safety and stability of the system are kept; the method mainly comprises the following steps: the functions of real-time (minute-level) prediction of the multi-energy load, short-term (hour-level or day-ahead) prediction of the multi-energy load and medium-long term prediction of the multi-energy load are realized;
3) energy consumption early warning
Setting an alarm grade and an alarm item, setting the alarm grade to five grades, and representing the alarm grade by different colors; the alarm grade and the display color can be uniformly set by an administrator; the alarm items can be divided into energy consumption unit index alarm, regional energy consumption total alarm, regional power consumption alarm, regional unit product energy consumption alarm and regional unit output value energy consumption alarm according to different division levels;
4) energy saving analysis
Designing a product structure energy-saving calculation and analysis functional module according to a GB/T13234-2009 enterprise energy-saving calculation method and an IPMVP authentication regulation, and designing an energy-saving technical improvement energy-saving evaluation functional module based on a project boundary defining technology based on main associated parameter analysis and a standard energy consumption technology based on condition parameter regression theory;
5) analysis of carbon emissions
The energy consumption physical quantity and the energy saving physical quantity reported to the system by an energy consumption unit are called, the GWP gas emission quantity and the emission reduction flow of the energy consumption unit of the park are calculated and summarized according to the GWP gas (CO2 emission, NOx emission, CHx emission and the like) emission factor coefficient in the IPCC national greenhouse gas emission guide, and the calculation results of the GWP gas emission quantity and the emission reduction quantity are compared and analyzed according to the two levels of the park and the enterprise; the method is prepared for the construction of a subsequent carbon emission trading platform, on one hand, the carbon emission and the emission reduction amount can be measured and calculated by an energy consumption unit in an auxiliary mode, and on the other hand, the carbon emission and the emission reduction amount of the energy consumption unit can be verified by an energy-saving governing department.
Further, the energy consumption early warning comprises two levels, specifically as follows:
1) regional energy consumption prediction early warning
Monitoring, alarming, predicting and analyzing added value energy consumption, total energy consumption, single energy consumption, energy saving, unit product energy consumption and unit output value energy consumption of the industrial park, and archiving sample data of the staged data;
2) energy unit prediction early warning
Monitoring and alarming indexes such as energy consumption, power consumption, total industrial output value, unit product energy consumption, unit output value energy consumption and the like of key energy consumption units; when the index exceeds the limit, the alarm is given in three levels according to the ratio of the limit exceeding, namely, first level (yellow), second level (orange) and third level (red), and the alarm range can be set by a system administrator; the alarm content of the prompt can be sorted according to the excess amount, and the system can automatically extract the reason explanation in the energy unit direct report as the comment.
Compared with the prior art, the invention has the beneficial effects that:
1) efficient use of energy
Through the collection monitoring, processing, analysis, statistics, diagnosis and storage of energy data, the enterprise can master the running state and the energy consumption condition of energy utilization equipment in real time, and the energy utilization efficiency is continuously improved by optimizing and adjusting the energy, the equipment and the production process in time according to the analysis and diagnosis information.
2) Long-term efficient operation of energy-consuming equipment
The enterprise energy utilization condition is complex and comprises a plurality of energy utilization devices and a plurality of energy utilization conditions. The energy management system classifies the energy-using equipment in the project and measures the energy-using equipment independently. The system can clearly check the integral energy utilization condition of an enterprise, can check the running condition of the energy utilization equipment in real time, can timely find, predict and process the fault condition of the energy utilization equipment, and ensures that the equipment is in a normal running state.
3) The operation and maintenance level of operation and maintenance personnel is improved, and the operation and maintenance cost is reduced
Aiming at the construction of an energy efficiency management system in the magnesite industry, the method has practical significance for improving the energy management level. The enterprise operation and maintenance personnel inquire the equipment operation condition at any time through the system, so that the energy operation management is simplified, the management pressure of daily management personnel is reduced, the labor productivity is improved, and the possibility of misoperation of the operation and maintenance personnel is reduced to a certain extent.
Drawings
FIG. 1 is a schematic diagram of the system architecture of the present invention;
FIG. 2 is a schematic diagram of the system application architecture of the present invention.
Detailed Description
The following detailed description of the present invention will be made with reference to the accompanying drawings.
A method for analyzing and improving energy efficiency of the magnesite industry is shown in figure 1, and is realized by the following system, and comprises the following steps: the system comprises a data acquisition module, a data service center and an energy efficiency monitoring center.
The data acquisition module consists of a data acquisition unit and a data acquisition terminal, the data acquisition unit acquires energy consumption data and energy consumption quality data of the energy efficiency monitoring area and sends the original data to the data acquisition terminal, and the data acquisition terminal preprocesses the received original data and uploads the processed data to the data service center through the Internet or a private enterprise network according to a specified format.
The data service center calculates, classifies, counts, establishes files and stores the data uploaded by the data acquisition module; and (3) creating user management data by combining information such as enterprises and equipment files, summarizing all data, and then establishing an energy efficiency management database to provide data support for a data query and energy efficiency monitoring center.
The energy efficiency monitoring center comprehensively monitors, analyzes and diagnoses the energy use condition of a monitored area through data provided by the data service center; establishing an energy efficiency analysis algorithm model combining enterprise scale, energy types and production process characteristics, and realizing preventive maintenance functions such as real-time online energy consumption monitoring, energy consumption fault early warning and energy consumption quality early warning; according to the energy efficiency analysis result, automatically diagnosing the abnormal or fault reason, generating a repair or improvement measure suggestion, outputting an energy efficiency analysis report, and transmitting the analysis result data and the report data to a data service center for archiving and storing to obtain historical data.
System architecture
The invention installs data collectors (or installs on energy meter/instrument) for all front-end equipment of monitoring area and equips data collecting terminal according to the number of collectors of each monitoring area. And the data acquisition unit and the data acquisition terminal perform mutual data interaction by adopting an RS485 communication protocol standard. And then, completing the establishment of software and hardware communication network environments of the data acquisition module, the data service center and the energy efficiency monitoring center through advanced technologies such as an internet communication technology, an internet of things technology, a cloud service and the like, namely completing the establishment of a system architecture.
Front-end equipment: the system comprises energy consumption meters for acquiring various energy consumption conditions, an environment detector for acquiring environment data, an electric energy quality detector for acquiring electric energy quality and automatic system data port equipment.
A data acquisition module: the data service center is used for acquiring original data and sending the acquired original data to the data service center; the data acquisition module consists of a data acquisition unit and a data acquisition terminal.
A data acquisition unit: the method is used for collecting the energy consumption data of the original enterprise.
A data acquisition terminal: the system is used for preprocessing and uploading the acquired raw data.
A data service center: the data acquisition module is used for identifying, analyzing, classifying, calculating, counting and storing the data of the data acquisition module.
Energy efficiency monitoring center: the energy efficiency analysis and diagnosis system is used for monitoring, analyzing and diagnosing data of the data service center in real time and automatically generating an energy efficiency analysis and diagnosis report.
As shown in fig. 2, the application architecture of the system includes a data acquisition layer, a data operation layer, a data query layer, and a statistical analysis layer; the data acquisition layer completes the acquisition of energy consumption and production related data by protocol butt joint of the intelligent energy meter and the automatic system data port equipment, supports modes such as manual input and the like to acquire required data, and uploads the acquired data to the data operation layer; the data operation layer is responsible for processing the uploaded energy consumption data, counting energy consumption, accounting energy consumption cost and the like, storing and managing energy consumption equipment files, alarm records, maintenance records and energy consumption records, and providing a data source for the data query layer; the data query layer documents various energy consumption data and generates various energy consumption statistical reports after performing classification calculation according to time periods, units, processes, lines, finance and the like according to the data provided by the data operation layer, provides query at any time and provides data support for the statistical analysis layer; after the data query layer data is acquired, the statistical analysis layer comprehensively displays the energy consumption analysis data, the diagnosis evaluation data, the early warning data and the like in the form of a portal and a statistical chart, and issues the acquired information, the analysis diagnosis information and the decision information in real time or at regular time.
A data acquisition layer: core function of the data acquisition module.
Data processing layer and data query layer: and the data service center core function.
Statistical analysis layer: the core function of the energy efficiency monitoring center.
The energy consumption data comprises: and enterprise energy consumption data such as electric energy consumption data, electric energy quality data and the like.
The energy consumption fault early warning comprises the following steps: power alarm data, over-capacity operation alarm, power quality alarm data, etc.
The energy consumption analysis data comprises: and energy consumption historical operation data of each front-end device.
The energy consumption quality data comprises: the method comprises the steps that current operation data of the power quality of each front-end device and historical operation data of the power quality of each front-end device are obtained;
the user management data: enterprise archive information, equipment archive information;
the energy efficiency management database comprises: all the data mentioned above.
Secondly, a data acquisition method comprises the following specific steps:
and compiling automatic acquisition tasks according to the requirements of different services on the acquired data, wherein the automatic acquisition tasks comprise task names, task types, acquisition groups, acquired data items, task execution starting and ending time, acquisition periods, execution priorities and normal acquisition supplementing time information, managing the execution of various acquisition tasks and checking the task execution condition.
1) Collecting data type items
The data items collected by the system include:
electric energy data: the total electric energy indicating value, each rate electric energy indicating value, the total electric energy, each rate electric energy and the maximum demand;
alternating current analog quantity: voltage, current, active power, reactive power, power factor;
working condition data: collecting working condition information of a terminal and metering equipment;
statistical data of power quality out-of-limit: out-of-limit statistical data such as voltage, current, power factor, harmonic wave and the like;
event record data: event record data recorded by the terminal and the electric energy meter;
other data: and (4) fee control information.
2) Collection mode
a) Timed auto-acquisition
Automatically acquiring terminal data according to a time interval set by an acquisition task, wherein the time, interval, content and object of automatic acquisition can be set; when the timing automatic data acquisition fails, the master station should have automatic and manual complementary acquisition functions to ensure the integrity of data.
b) Random call and test
Manually calling and testing data at any time according to actual needs; if the event alarm occurs, important data related to the event is recalled and tested immediately for event analysis.
c) Active reporting
In the data transmission of the full-duplex channel and the data exchange network channel, allowing a terminal to start a data transmission process, namely active reporting for short, immediately reporting an important event to a master station, and reporting data to the master station at regular time according to the set of a regular sending task; the master station should support the collection and processing of actively reported data.
Thirdly, the method also comprises the following steps:
1) harmonic analysis
The harmonic data of key equipment is acquired through energy consumption terminal acquisition equipment and uploaded to a platform for analysis, and the serious harmonic condition can be automatically marked and early warned; and the energy-saving expert gives improvement suggestions aiming at the problems.
2) Energy prediction
Historical and real-time data in the energy big data are used, the operation characteristics, natural conditions and the like of the system are combined, multi-time scale prediction of different loads is realized through preprocessing of load data, day-ahead, day-in-day hour-level and real-time minute-level cold, heat and electricity load prediction of a user energy system is realized, a scheduling plan of the multi-energy flow system in day-ahead, day-in-day and real-time different time scales is arranged, meanwhile, support is provided for safety analysis of the multi-energy flow system, and safety and stability of the system are kept; the method mainly comprises the following steps: the prediction function of the multi-energy load comprises the functions of multi-energy load real-time (minute level) prediction, multi-energy load short-term (hour level or day-ahead) prediction and multi-energy load medium-long term prediction.
3) Energy consumption early warning
Setting an alarm grade and an alarm item, setting the alarm grade to five grades, and representing the alarm grade by different colors; the alarm grade and the display color can be uniformly set by an administrator; the alarm items can be divided into energy consumption unit index alarm, regional energy consumption total alarm, regional power consumption alarm, regional unit product energy consumption alarm and regional unit output value energy consumption alarm according to different division levels.
The energy consumption early warning comprises two levels, specifically as follows:
1) regional energy consumption prediction early warning
Monitoring, alarming, predicting and analyzing added value energy consumption, total energy consumption, single energy consumption, energy saving, unit product energy consumption and unit output value energy consumption of the industrial park, and archiving sample data of the staged data;
2) energy unit prediction early warning
Monitoring and alarming indexes such as energy consumption, power consumption, total industrial output value, unit product energy consumption, unit output value energy consumption and the like of key energy consumption units; when the index exceeds the limit, the alarm is given in three levels according to the ratio of the limit exceeding, namely, first level (yellow), second level (orange) and third level (red), and the alarm range can be set by a system administrator; the alarm content of the prompt can be sorted according to the excess amount, and the system can automatically extract the reason explanation in the energy unit direct report as the comment.
4) Energy saving analysis
The method comprises the steps of designing a product structure energy-saving calculation and analysis functional module according to a GB/T13234-2009 enterprise energy-saving calculation method and an IPMVP authentication regulation, and designing an energy-saving technical improvement energy-saving evaluation functional module based on a project boundary defining technology based on main associated parameter analysis and a standard energy consumption technology based on condition parameter regression theory.
5) Analysis of carbon emissions
The energy consumption physical quantity and the energy saving physical quantity reported to the system by an energy consumption unit are called, the GWP gas emission quantity and the emission reduction flow of the energy consumption unit of the park are calculated and summarized according to the GWP gas (CO2 emission, NOx emission, CHx emission and the like) emission factor coefficient in the IPCC national greenhouse gas emission guide, and the calculation results of the GWP gas emission quantity and the emission reduction quantity are compared and analyzed according to the two levels of the park and the enterprise; the method is prepared for the construction of a subsequent carbon emission trading platform, on one hand, the carbon emission and the emission reduction amount can be measured and calculated by an energy consumption unit in an auxiliary mode, and on the other hand, the carbon emission and the emission reduction amount of the energy consumption unit can be verified by an energy-saving governing department.
6) Device energy efficiency diagnostics
The energy consumption of enterprises is mainly embodied on energy utilization equipment, and an energy efficiency diagnosis module of key energy utilization equipment is added, so that the enterprises can know the energy consumption level of the energy utilization equipment of the unit at any time and find out the laggard out equipment in time. By calculating the energy utilization efficiency of the energy utilization equipment, deviation analysis is carried out, weak links of energy utilization are found, and the system automatically gives improvement measures.
The above embodiments are implemented on the premise of the technical solution of the present invention, and detailed embodiments and specific operation procedures are given, but the scope of the present invention is not limited to the above embodiments. The methods used in the above examples are conventional methods unless otherwise specified.
Claims (5)
1. A method for analyzing and improving energy efficiency in magnesite industry is characterized in that the method is realized by the following system, and comprises the following steps: the system comprises a data acquisition module, a data service center and an energy efficiency monitoring center;
the data acquisition module consists of a data acquisition unit and a data acquisition terminal, the data acquisition unit acquires energy consumption data and energy consumption quality data of an energy efficiency monitoring area and sends the original data to the data acquisition terminal, and the data acquisition terminal preprocesses the received original data and uploads the processed data to the data service center through the Internet or a private enterprise network according to a specified format;
the data service center calculates, classifies, counts, establishes files and stores the data uploaded by the data acquisition module; creating user management data by combining enterprise and equipment archive information, summarizing all data, and then establishing an energy efficiency management database to provide data support for a data query and energy efficiency monitoring center;
the energy efficiency monitoring center comprehensively monitors, analyzes and diagnoses the energy use condition of a monitored area through data provided by the data service center; establishing an energy efficiency analysis algorithm model combining enterprise scale, energy type and production process characteristics, and realizing the functions of real-time online energy consumption monitoring, energy consumption fault early warning and energy consumption quality early warning preventive maintenance; according to the energy efficiency analysis result, automatically diagnosing the abnormal or fault reason, generating a repair or improvement measure suggestion, outputting an energy efficiency analysis report, and transmitting the analysis result data and the report data to a data service center for archiving and storing to obtain historical data.
2. The method for magnesite industry energy efficiency analysis and improvement as claimed in claim 1, wherein the system includes a data acquisition layer, a data operation layer, a data query layer, a statistical analysis layer; the data acquisition layer completes the acquisition of energy consumption and production related data by protocol butt joint of the intelligent energy meter and the automatic system data port equipment, supports a manual input mode to acquire required data, and uploads the acquired data to the data operation layer; the data operation layer is responsible for processing the uploaded energy consumption data, counting energy consumption, accounting energy consumption cost, storing and managing energy consumption equipment files, alarm records, maintenance records and energy consumption records, and providing data sources for the data query layer; the data query layer is used for filing various energy consumption data and generating various energy consumption statistical reports after performing classification calculation according to time periods, units, processes, lines and finances according to the data provided by the data operation layer, so that query at any time is provided, and data support is provided for the statistical analysis layer; after the data query layer data is obtained, the statistical analysis layer comprehensively displays the energy consumption analysis data, the diagnosis evaluation data and the early warning data in the form of a portal and a statistical chart, and issues the acquisition information, the analysis diagnosis information and the decision information in real time or at regular time.
3. The method for energy efficiency analysis and improvement in the magnesite industry according to claim 1, wherein the method comprises a data acquisition method, and specifically comprises the following steps:
compiling automatic acquisition tasks according to the requirements of different services on the acquired data, wherein the automatic acquisition tasks comprise task names, task types, acquisition groups, acquired data items, task execution starting and ending time, acquisition periods, execution priorities and normal acquisition supplementing frequency information, managing the execution of various acquisition tasks and checking the task execution condition;
1) collecting data type items
The data items collected by the system include:
electric energy data: the total electric energy indicating value, each rate electric energy indicating value, the total electric energy, each rate electric energy and the maximum demand;
alternating current analog quantity: voltage, current, active power, reactive power, power factor;
working condition data: collecting working condition information of a terminal and metering equipment;
statistical data of power quality out-of-limit: statistical data of voltage, current, power factor and harmonic out-of-limit;
event record data: event record data recorded by the terminal and the electric energy meter;
other data: cost control information;
2) collection mode
a) Timed auto-acquisition
Automatically acquiring terminal data according to a time interval set by an acquisition task, wherein the time, interval, content and object of automatic acquisition can be set; when the timing automatic data acquisition fails, the master station should have automatic and manual complementary acquisition functions to ensure the integrity of data;
b) random call and test
Manually calling and testing data at any time according to actual needs; if the event alarm occurs, important data related to the event is recalled and tested immediately for event analysis;
c) active reporting
In the data transmission of the full-duplex channel and the data exchange network channel, allowing a terminal to start a data transmission process, namely active reporting for short, immediately reporting an important event to a master station, and reporting data to the master station at regular time according to the set of a regular sending task; the master station should support the collection and processing of actively reported data.
4. The method for energy efficiency analysis and improvement in magnesite industry as claimed in claim 1, wherein the method further comprises the following steps:
1) harmonic analysis
The harmonic data of key equipment is acquired through energy consumption terminal acquisition equipment and uploaded to a platform for analysis, and the serious harmonic condition can be automatically marked and early warned; an energy-saving expert gives improvement suggestions aiming at problems;
2) energy prediction
Historical and real-time data in the energy big data are used, the operation characteristics and natural conditions of the system are combined, the load data are preprocessed, multi-time scale prediction of different loads is realized, the cold, heat and electricity load prediction of the user energy system at the day-ahead, day-in-day hour level and real-time minute level is realized, a scheduling plan of the multi-energy flow system at the day-ahead, day-in-day and real-time different time scales is arranged, meanwhile, support is provided for the safety analysis of the multi-energy flow system, and the safety and stability of the system are kept; the method mainly comprises the following steps: the functions of real-time (minute-level) prediction of the multi-energy load, short-term (hour-level or day-ahead) prediction of the multi-energy load and medium-long term prediction of the multi-energy load are realized;
3) energy consumption early warning
Setting an alarm level and alarm items, setting the alarm level to be five levels, and representing the alarm level by different colors; the alarm level and the display color can be uniformly set by an administrator; the alarm items can be divided into energy consumption unit index alarm, regional energy consumption total alarm, regional power consumption alarm, regional unit product energy consumption alarm and regional unit output value energy consumption alarm according to different division levels;
4) energy saving analysis
Designing a product structure energy-saving calculation and analysis functional module according to a GB/T13234-2009 enterprise energy-saving calculation method and an IPMVP authentication regulation, and designing an energy-saving technical improvement energy-saving evaluation functional module based on a project boundary defining technology based on main associated parameter analysis and a standard energy consumption technology based on condition parameter regression theory;
5) analysis of carbon emissions
The energy consumption physical quantity and the energy saving physical quantity reported to the system by an energy consumption unit are called, the GWP gas emission quantity and the emission reduction flow of the energy consumption unit of the park are calculated and summarized according to the GWP gas (CO2 emission, NOx emission and CHx emission) emission factor coefficient in the IPCC national greenhouse gas emission guide, and the calculation results of the GWP gas emission quantity and the emission reduction quantity are compared and analyzed according to the two levels of the park and the enterprise; the method is prepared for the construction of a subsequent carbon emission trading platform, on one hand, the carbon emission and the emission reduction amount can be measured and calculated by an energy consumption unit in an auxiliary mode, and on the other hand, the carbon emission and the emission reduction amount of the energy consumption unit can be verified by an energy-saving governing department.
5. The method for analyzing and improving the energy efficiency of the magnesite industry according to claim 3, wherein the energy consumption early warning comprises two levels, specifically as follows:
1) regional energy consumption prediction early warning
Monitoring, alarming, predicting and analyzing added value energy consumption, total energy consumption, single energy consumption, energy saving, unit product energy consumption and unit output value energy consumption of the industrial park, and archiving sample data of the staged data;
2) energy unit prediction early warning
Monitoring and alarming the energy consumption, the power consumption, the total industrial output value, the energy consumption of unit product and the energy consumption index of unit output value of key energy consumption units; when the index exceeds the limit, the alarm is given in three levels according to the ratio of the limit exceeding, namely, first level (yellow), second level (orange) and third level (red), and the alarm range can be set by a system administrator; the alarm content of the prompt can be sorted according to the excess amount, and the system can automatically extract the reason explanation in the energy unit direct report as the comment.
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