Summary:From the perspective of energy measurement and management, the basic components and functions of the energy measurement management system in steel mills are discussed. The establishment of this system will enable automatic collection, instantaneous monitoring, fault alarm, and energy flow monitoring of energy medium measurement management in steel mills; Complete functions such as report statistics, offline input, cost analysis, and forecast reference. Improving the level and intensity of measurement management work has important guiding significance for balancing and stabilizing production in steel mills, balancing the pressure and load of the company's pipeline network as much as possible, making production decisions and arrangements, scheduling and adjustments within the plant, saving and optimizing energy consumption, and ensuring the overall interests of the entire plant.

key word:Energy, metering, management, steel mills, energy management

Steel enterprises are major energy consumers, and continuously improving their own energy conservation and consumption reduction level is the goal that steel enterprises have always pursued. Steel mills are an important component of steel companies, and their energy usage and occurrence have their own characteristics. They have high requirements for energy measurement, detection, and management. The level of measurement and management of energy usage and recovery directly affects the reasonable balance and effective operation of the company's overall energy network. However, currently, most steel mills in China do not have their own energy measurement management system, which leads to varying degrees of irrationality in the use and recovery of energy in production. Therefore, establishing a relatively complete and accurate energy measurement management system for the steel plant as soon as possible can effectively compensate for the lack of energy medium use and management in the production plant itself, meet the needs of energy medium measurement, detection, and management within the steel plant, enable it to clarify the use and consumption status of energy medium in future work and production, facilitate data organization, energy consumption analysis, production scheduling, and adjustment, and improve the utilization rate, energy economy, and rationality of energy medium. This article takes a steel plant of a certain steel group company as an example to introduce the design, composition, and functions of the energy metering management system, which has certain reference value for other steel plants.

Introduction to the Process Flow of Steel Plant 1

The basic process flow of the steelmaking plant under the steel group company is as follows: a large amount of high-temperature molten iron produced by the blast furnace of the ironmaking plant is sent to the steelmaking plant through a well insulated mixer truck. It first enters the desulfurization room of the steelmaking plant for pretreatment, and then transported to the pouring station. After slag removal, the molten iron is mixed into the converter and smelted together with scrap steel that is weighed according to the scheduling plan and first loaded into the converter. The converter smelting operation is statically controlled and calculated by a process computer, automatically completing the entire steelmaking process. The molten steel melted out of the furnace is subjected to secondary refining outside the furnace according to the specific technical requirements of different steel grades, and then produced as the final product of the steelmaking process through continuous casting or mold casting production lines - continuous casting billet or cast steel billet. The main production process is shown in Figure 1.

The main energy media consumed by steel mills include oxygen, nitrogen, argon, coke oven gas, steam, electricity, water, etc. The recovered energy media include converter gas and steam.

2. Basic content of energy metering management system

2.1 Measurement and testing of energy media

The existing energy metering and detection system of the steel plant mainly consists of three parts:

(1) Various incoming energy medium data are collected uniformly by the energy center;

(2) Some processes and equipment consume energy and medium data collected or calculated by computers (such as continuous casting, etc.);

(3) Some processes and equipment consume energy and medium data through manual meter reading (such as RH).

There are many sources of data, and some data require manual secondary calculation and processing due to pipeline intersections, making the end of month data statistics work complex and prone to errors. Even if there are problems with the data, it is difficult to find the cause. Moreover, it is difficult to detect pipeline faults and abnormalities during production, and it is impossible to eliminate hidden dangers in a timely manner.

Therefore, fundamentally solve the problem. In the original energy medium pipeline network of the steel plant, a large number of various measuring instruments and power control valves are installed to control production and measurement needs, and to detect and measure the flow rate, pressure, temperature and other quantities of various energy media. Most of these instruments are analog dashboards, with a small number of control process quantities displayed in the process machine. On the basis of the existing measuring instruments in the pipeline network, this system further improves the system configuration from the perspectives of usage, safety, and management, supplements measuring and management needs that the original system does not have, replaces existing instruments in the original system that cannot meet future usage requirements, and enables the system network to first meet the requirements of computer measurement, detection, and management in hardware. The system functional structure is shown in Figure 2.

2.1.1 Data Collection and Processing

(1) Concentrate the analog signals from scattered measurement points on the instrument onto the computer, and convert them into digital signals through anti-interference, isolation amplification, filtering, current voltage converter, and A/D conversion. Then, form 1-second average, 1-minute average, and 1-hour average according to certain requirements.

(2) By using long-distance networking systems and communication management system software and hardware, various data are sent to network servers to achieve data sharing.

2.1.2 Fault alarm and monitoring

The computer performs alarm upper and lower limit judgment on the collected data, saves the data for 1-5 minutes before and after the alarm signal, and sends it to the alarm monitor for display and automatic printing according to the network protocol. Track the main alarm parameters and correctly determine the cause of the fault based on the alarm record content and trend curve.

2.1.3 Energy Flow Chart Display

Design a set of process flow dynamic images to display process flow diagrams for various energy media, including instantaneous value display at each sampling point, cumulative value display of data collected at measuring points, etc.

After implementing the above functions, various data on energy medium consumption and recovery can be easily obtained online, and the operating status and energy consumption data of each process and main equipment can be monitored at any time. The operation time of the pipeline network can be automatically monitored to predict faults in advance and prevent them in advance.

2.2 Energy Management

The original energy medium consumption and recovery situation of the steel plant relied on manual statistics and calculations, with repetitive work, complex data, low efficiency, and easy errors, which were not in line with modern management and production pace. Report statistics, cost accounting, etc. are also manually carried out, with poor systematization and standardization. The energy metering management system can easily achieve functions such as rapid statistics, automatic reporting, and expert analysis, replacing manual labor with computers to achieve ideal accuracy and efficiency.

2.2.1 Report statistics

By using database management software, various daily, monthly, and annual energy consumption reports, as well as various energy consumption curves, are automatically generated, enabling data statistics and organization to transition from manual to computerized, improving work efficiency and accuracy.

2.2.2 Offline data input

By using a system support software that can input unmeasurable and variable parameters (such as alarm upper and lower limits, etc.), the adaptability and scalability of the system can be improved.

2.2.3 Cost Statistical Analysis

Real time monitoring of the energy consumption status of each process and major equipment, comprehensive evaluation of energy consumption for different varieties and specifications, energy cost statistics and analysis by shift, and management of energy costs. Conduct analysis and evaluation of process energy consumption and cost, and complete information transmission and communication between the steel plant and the energy center.

2.2.4 Trend Monitoring

Through the CRT screen, it is easy to display the process flow diagrams of various energy media, automatically generate trend curves or histograms, and grasp the operating status of major equipment and the consumption, occurrence, and recovery of energy media at any time, which facilitates production scheduling and adjustment.

2.2.5 Prediction Reference

Utilize statistical data and expert knowledge base to predict energy medium demand and supply planning and measures for the next year.

The implementation of the above functions greatly enhances the management of data and conditions related to the consumption and recovery of energy media, providing online reference for production decision-making, scheduling, and adjustment.

Introduction to Ankerui Industrial Energy Measurement Management System

The Ankerui Industrial Energy Measurement Management System adopts automation, information technology, and centralized management mode to implement centralized and flat dynamic monitoring and data management of the production, transmission, distribution, and consumption links of enterprises. It monitors the consumption of various types of energy such as electricity, water, gas, steam, and compressed air in enterprises. Through data analysis, mining, and trend analysis, it helps enterprises to conduct energy consumption statistics, same environment ratio analysis, energy cost analysis, energy consumption prediction, and carbon emission analysis based on various energy demands and consumption situations, energy quality, product energy consumption per unit, energy consumption of each process, and energy utilization of major energy consuming equipment. It provides basic data and support for enterprises to strengthen energy management, improve energy utilization efficiency, explore energy-saving potential, and energy-saving evaluation.

3.1 System Structure

3.2 Application Sites

Steel, petrochemicals, metallurgy, non-ferrous metals, mining, pharmaceuticals, cement, coal, logistics, railway, aviation industry, wood, chemical raw materials, as well as manufacturing of mechanical and electrical equipment, electrical products, and tools.

3.3 System Functions

3.3.1 Visual Display

Display the total energy consumption, conversion value, energy cost, energy consumption trend, proportion of sub item energy consumption, regional energy consumption comparison, as well as the current weather and pollution situation of the enterprise, and 3D display the energy consumption dynamics of important processes or sections of the enterprise.

3.3.2 Energy consumption statistics

From the dimensions of energy usage types, monitoring areas, production process/section time, sub items, etc., curve, pie chart, histogram, cumulative chart, numerical table and other methods are used to analyze enterprise energy consumption statistics, year-on-year, month on month analysis, actual performance analysis, benchmark comparison, unit product energy consumption, unit output value energy consumption statistics, identify loopholes and unreasonable areas in the energy use process, and adjust energy allocation strategies to reduce waste in the energy use process.

3.3.3 Product/Output Unit Consumption

Integrate with the enterprise MES system, generate product consumption trend charts in product consumption based on product output and energy consumption data collected by the system, and conduct year-on-year and month on month analysis. So that enterprises can adjust their production processes based on the unit consumption of products, thereby reducing energy consumption.

3.3.4 Performance Analysis

Conduct daily, weekly, monthly, annual, and * time period performance statistics for various energy usage, consumption, and conversion according to teams, regions, production lines, and sections. Compare and evaluate KPI performance indicators based on energy plans or quotas to help enterprises understand internal energy efficiency levels and energy-saving potential.

3.3.5 Energy consumption prediction

By analyzing the energy consumption of production processes and equipment in enterprises, establishing an energy consumption calculation model, and modifying the data and model based on artificial intelligence algorithms, effective decision-making basis is provided for energy conservation.

3.3.6 Operation Monitoring

The system collects data on energy consumption of regions, sections, and equipment, monitors the operating status of equipment and processes, such as temperature, humidity, flow rate, pressure, speed, etc., and supports one-time operation monitoring of power distribution systems. You can quickly browse the managed energy consumption data directly from the dynamic monitoring plan, and support querying related energy consumption by energy type, workshop, section, time and other dimensions.

3.3.7 Analysis Report

By conducting comprehensive statistical analysis on the energy utilization, line losses, equipment operation, and maintenance of enterprises on a yearly, monthly, and daily basis, users can gain a comprehensive understanding of the system's operation and provide a data foundation for them to discover equipment abnormalities, identify improvement points, and explore energy-saving potential based on energy consumption.

3.3.8 Event Alarm

Continuously monitor the operation of equipment and systems, issue alarms for communication failures, data anomalies, quota exceeding limits, abnormal process parameter exceeding limits, equipment abnormalities or failures, remind enterprises to pay attention and search for problems, and form alarm logs.

3.3.9 Mobile Support

The APP supports Android and iOS operating systems, making it convenient for users to grasp enterprise energy consumption, efficiency analysis, month on month analysis, energy consumption conversion, energy consumption prediction, operation monitoring, abnormal alarm, etc. from different dimensions such as energy classification, region, workshop, process, team, and equipment.

3.4 On site equipment selection

4 Conclusion

The establishment of the energy metering management system in the steel plant has automated the metering and detection of energy media, achieving automatic collection, instantaneous monitoring, fault alarm, and energy flow monitoring; Improved the level and intensity of management work, completed functions such as report statistics, offline input, cost analysis, and forecast reference. To achieve balanced and stable production in the steel plant, and to balance the pressure and load of the company's pipeline network as much as possible, it is of great guiding significance to make production decisions, arrangements, schedules, and adjustments within the plant, save and optimize energy consumption, and ensure the overall interests of the entire plant.

This system has broad reference value and reference value for similar steel mills.