In the face of the "deep freeze" of the steel industry, China's steel sector has undergone significant adjustments under the new circumstances. Reducing costs and increasing efficiency has become the trend for large energy-consuming enterprises, with energy conservation and consumption reduction being the top priority. The production activities of modern rolling mills are now showing a more pronounced trend towards intelligence, which necessitates a higher level of management for electrical equipment within the plants. Emphasis is placed on the maintenance and management of electrical equipment to ensure effective energy conservation and consumption reduction during operations. The Baogang Rail Beam Plant, facing severe market conditions, has delved deep into its potential, continuously strengthening fundamental management, vigorously implementing benchmarking and upgrading, and improving the quality of rail products, persistently waging a battle for cost reduction and efficiency improvement. Starting from January 2017, the rail beam plant has been experimenting with a daily wage standard for energy conservation and consumption reduction, which requires the electrical workshop to refine the differences between actual and per-ton steel electricity costs from a lean electricity perspective, thereby providing a guiding principle for energy conservation and consumption reduction.
1 Software Function Application
The steel rolling mill commenced operations on January 23, 1969, and is one of China's key producers of rail and section steel. Through continuous introduction of advanced equipment, elimination of outdated processes, and technological upgrades, the factory has transformed into a modern facility. It now boasts two production lines: the 1# medium-sized rolling production line, which began operation in September 2006, and the 2# large-sized rolling production line, which started in January 2013. The annual production capacity is 2.1 million tons. For instance, the 2# line's 10kV power supply system at the electrical automation department is supplied by the 51# substation, split into four circuits. The 1# and 2# incoming lines power the auxiliary drive, the 3# incoming line powers the BD1 and BD2 main drives, and the 4# incoming line powers the CCS main drive.
In 2015, the rail beam factory achieved an electrical consumption level of 82.1 kW-h/t steel, with an average annual consumption of 89 kW*h per ton of steel. Due to the larger total installed capacity of Line 2, the electrical consumption per ton of steel is higher than that of Line 1. These figures reflect the rail beam factory's electrical consumption in 2015. However, this year's completion rate is 31.2 yuan/t, and the Electrical Automation Department must implement effective measures. The above comparative data are from the new electricity monitoring platform introduced by the rail beam factory.
To control energy costs, manage energy scheduling, formulate energy-saving and consumption-reduction plans, conduct statistical analysis and management of energy consumption levels and distribution, ensure the continuous economic operation of the energy system, lower energy use costs, and properly manage electrical power, our factory has introduced a power management software. This software features electricity metering, time-of-use billing management, power demand management, energy consumption analysis, energy efficiency monitoring, energy efficiency assessment, energy efficiency display, energy-saving equipment management, an energy-saving knowledge base, multiple energy and production data collection and forwarding functions, electricity quality management, and power failure diagnosis and analysis capabilities.
1.1 Data Collection
The 10 kV data collection records all full electrical data for each loop, including U, I, kW, kvar, PF, f, kWh, kvarh, etc., with time tags. It also collects abnormal alarm signals and non-electrical signals, gathering all information from the power energy efficiency monitoring terminals, event sequence record information, and other signals. It is capable of conducting periodic scanning and inspections of all power energy monitoring terminals in the station, with customizable data collection cycles. All collected data should be marked with complete data quality status and stored in the database.
Figure 1 General Management Machine Database
1.2 Data Integrity Management and Data Capture
In response to data loss caused by unexpected power outages in the pre-data collection server, the data collection program should possess comprehensive data integrity verification capabilities, capable of automatically compensating for missing data. The data collection server with protocol conversion should support data storage for no less than 30 days. In the event of an unexpected power outage leading to data loss, the system will automatically resume data transmission from the breakpoint upon recovery, ensuring data integrity. The monitoring software should also feature a primary and backup database, with data consistency checks and synchronization functions to guarantee the integrity and consistency of the primary and backup database data.
Figure 2: Database Maintenance Tool
1.3 Operation Monitoring and Control Function
(1 Telemetry, Telesignaling, Telemetering, Telemetering Control, Telemetering Adjustment, Telemetering Surveillance)
The management software features basic functions such as remote telemetry, signaling, control, adjustment, and visualization, meeting the requirements of power system countermeasures. It includes corresponding interlock and accident prevention measures, as well as prompts for information and status of selected controlled objects, operator and supervisor login, confirmation of the terminal and number of controlled objects, and a series of control execution processes. Remote control and remote adjustment have comprehensive operation password verification and supervisor mechanisms, allowing flexible setting of different operation permissions. Operations can only be carried out after logging into a control-privileged workstation and entering the operation password by the operator. Operators must have the corresponding operation permissions and can only operate on a single device at a time.
Figure 3: Daily Route Monitoring Report Curve
(2) Single-line, Single-point Monitoring
The management software features a rich data presentation interface, supporting various data display methods such as tables, bar graphs, curves, simulated dials, and more. It provides intuitive graphical interfaces for various power system elements, including primary system structure diagrams, transformer monitoring charts, and line operation monitoring maps. For line monitoring, a combination of charts, graphics, and data can be used to display the basic information of 10 kV lines, real-time operating data, real-time and historical power curves, and show the cumulative electricity saved year-to-date and rankings. It also presents annual cumulative reactive power and monthly cumulative reactive power data.
(3) Equipment Online Status Monitoring
Figure 5: Monthly Route Monitoring Report
The monitoring terminal of electrical equipment is structured to directly display the overall communication architecture. It presents essential information, operational status, key energy consumption parameters, and power quality of various critical energy-consuming equipment in the plant area through dynamic animations. It shows the online status of all energy-saving devices, providing a basis for equipment maintenance. It monitors server status and communication links, using network topology diagrams to oversee servers, enabling real-time health monitoring of the master station system. It promptly identifies risks within the system, including CPU load, memory usage, disk storage, and network I/O. By analyzing statistics of point data collection, it assesses the stability of communication links and further identifies the causes of data collection breakpoints.
Figure 6: Daily Route Monitoring Report
1.4 Basic Data Query and Comparative Analysis
The system can display and analyze basic information, trend curves, and event waveforms of power energy efficiency monitoring terminals. By placing the basic information of each node's device, events, waveform analysis, and trend curves on the same interface, users can view relevant information simultaneously. It allows users to conveniently navigate to the corresponding function pages to view detailed information as needed, providing a better user experience. The system offers query and analysis capabilities for any measurement point of energy-saving devices (fixed-point data, statistical data), and can export the data in Excel format.
1.5 Equipment Operation Analysis and Offline Equipment Statistics
We calculate the daily and monthly operation rates, daily and monthly operating hours, and annual operating hours of energy-saving equipment, and present them in the form of reports. We also track the operation status of energy-saving equipment, displaying the details of non-operational equipment in a list format, with separate statistics for daily and monthly cycles.
The management software features real-time online monitoring of device communication status, displaying the communication status, start time, and update time of monitored devices in a list format. Users can clearly grasp the communication status and data update time of monitoring device nodes, as well as the offline status of energy-saving equipment.
Figure 7: Sample Daily Report
1.6 Energy Efficiency Analysis Report
By displaying post-commissioning low-voltage side voltage, current, active and reactive power, power factor, as well as pre-commissioning power factor, power factor improvement rate, and load factor in a tabular format, we analyze the power factor improvement. We also record the daily maximum and occurrence time, minimum and occurrence time of power factor at installation points of substation or lines, the time when power factor is greater than 0.95 and less than 0.9, and the average power factor. The reporting function of the demand-side power software should include: daily, weekly, monthly, annual, and time-slot reports. Dynamic report templates. Various cross-time period reports and related value and difference reports. Sampling data on the reports can be modified by authorized personnel.
Implementation of Battery Capacity Analysis and Statistics
The rail beam factory has traditionally used manual data entry from electricity meters to record and summarize power consumption across various regions, which resulted in significant errors due to the inaccuracy of manual readings. To control power consumption, it is essential to start with the accuracy of basic data. The Electrical Automation Department has independently developed a power consumption monitoring system platform, which has achieved network monitoring of the power consumption of all factory equipment, improving the accuracy of power data collection. Through the data analysis of the power consumption analysis system, it is found that the main power-consuming equipment is the main drive equipment. Next is the equipment powered by the MCC, primarily the hydraulic system. Thirdly, the auxiliary transmission system, which includes conveyer rollers and similar equipment.
The investment in the plant's renovation is significant, so we've decided to start with the MCC system for energy control improvements. The backend data from the electrical power analysis system is directly transmitted to the factory's OA network, where it displays the electricity consumption information for each shift, facilitating real-time monitoring of production electricity usage.
Figure 8: Energy Efficiency Analysis Report
Figure 9: Energy Consumption Inquiry System
Figure 10: Overall Overview Table
Through our electricity consumption monitoring platform, we can also calculate the actual cost per ton of steel in electricity, the cost per shift per ton of steel, and the hourly electricity consumption based on production output and electricity usage. Special定额 items can also be accounted for and statistically analyzed through the electricity query function.
