Energy Efficiency Improvement and Intelligent Optimization of Electric Arc Furnace Electrical Automation Control System

Energy Efficiency Improvement and Intelligent Optimization Method for Electrical Automation Control System of Metallurgical Industry Electric Arc Furnace

Abstract: This article discusses the ways to improve energy efficiency and intelligent optimization of electric arc furnace electrical automation control systems in the metallurgical industry. It discusses the position of electric arc furnaces in the metallurgical industry and the impact of electrical automation control systems on energy efficiency. It analyzes the current energy efficiency status and existing problems of the system, and provides a path for energy efficiency improvement from hardware upgrades, control strategy optimization, monitoring system improvement, and other aspects. It explores intelligent optimization methods from the perspectives of intelligent algorithm application, collaborative control optimization, adaptive adjustment mechanism, remote operation and maintenance management, and provides reference for the development of electric arc furnace electrical automation control systems. 

Keywords: metallurgical industry; arc furnace; Electrical automation control system; Energy efficiency improvement; Intelligent optimization

The metallurgical industry is a key basic industry of the national economy, and electric arc furnaces play an important role in it, undertaking tasks such as scrap steel smelting and alloy production. The electrical automation control system is the center of stable operation and efficient production of electric arc furnaces, and its performance directly affects the energy efficiency level of electric arc furnaces. The energy issue is becoming increasingly prominent, and environmental protection requirements are continuously increasing. Improving the energy efficiency of electric arc furnace electrical automation control systems, achieving intelligent optimization, has become an inevitable requirement for the sustainable development of the metallurgical industry. However, there are many problems with energy efficiency in the current electric arc furnace electrical automation control system, such as energy waste and insufficient control accuracy, which urgently require in-depth exploration and technological innovation.

1、 Energy Efficiency Improvement Method for Electrical Automation Control System of Metallurgical Industry Electric Arc Furnace

（1） Hardware upgrade optimization improves system energy efficiency foundation

The hardware equipment of the electric arc furnace electrical automation control system is the foundation for the normal operation of the entire system. Upgrading and optimizing it can effectively improve the energy efficiency level of the system. On the one hand, by replacing with high-efficiency and energy-saving transformers, the no-load loss and load loss of the new transformer have decreased compared to the past. In the process of transmitting electrical energy, energy loss can be reduced and the utilization rate of electrical energy can be improved. On the other hand, advanced power control devices such as intelligent power modules are used, which have the advantages of fast response speed, high control accuracy, and low losses. They can achieve more precise control of the power output of electric arc furnaces, thereby avoiding unnecessary energy consumption.

（2） Optimizing control strategies to achieve precise energy efficiency control

The control strategy is a key part of the electrical automation control system for electric arc furnaces, and improving the control strategy can achieve accurate control of paired energy efficiency. The traditional constant power control strategy has limitations in dealing with complex working conditions. By using intelligent power allocation control strategy, the power output of each phase can be adjusted according to the current working conditions and process requirements of the electric arc furnace, so that the electric arc furnace can maintain the best energy efficiency level at different times. Moreover, by incorporating fuzzy control algorithms, the control parameters can be automatically adjusted based on fuzzy variables such as arc length and current fluctuations, enhancing the system's adaptability to complex operating conditions and reducing energy losses caused by improper control.

（3） Improve the monitoring system to strengthen energy efficiency feedback and regulation

Improving the monitoring system is an important guarantee for improving the energy efficiency of the electric arc furnace electrical automation control system. Install multiple sensors in key areas of the electric arc furnace to monitor real-time parameters such as arc current, voltage, power, temperature, etc., and transmit these data to the control center. By analyzing the monitoring data, energy efficiency issues such as local overheating and unreasonable power allocation can be detected in a timely manner during system operation. According to the monitoring results, immediately adjust the control strategy and equipment operating parameters to achieve dynamic adjustment of energy efficiency. Establish an energy efficiency evaluation index system, implement quantitative evaluation of the energy efficiency level of electric arc furnaces, and provide a basis for further improvement of the system.

2、 Intelligent optimization method for electrical automation control system of metallurgical industry electric arc furnace

（1） Intelligent algorithm deep application optimization system parameter operation

The application of intelligent algorithms in the electrical automation control system of electric arc furnaces has brought new avenues for intelligent optimization of the system. Genetic algorithms have strong global search capabilities and can be used to improve control parameters of electric arc furnaces, such as electrode adjustment speed, power allocation ratio, and so on. By performing search and evaluation on many parameter combinations, genetic algorithms can find the parameter combination that maximizes the energy efficiency of the electric arc furnace, thereby improving the system's operating parameters. Neural network algorithms can mimic and learn the operating rules of electric arc furnaces, predict the future situation of electric arc furnaces based on real-time input data, and then adjust control strategies in advance. Estimate the melting time and power demand of the electric arc furnace based on information such as raw material composition and temperature, adjust the power output in advance, and prevent energy waste. Particle swarm optimization algorithm and other algorithms also play a key role in improving the control parameters of electric arc furnaces. By continuously iterating to explore the best answer, the system's operational efficiency and energy efficiency level can be improved.

（2） Multi link efficient linkage collaborative control and optimization integration

The electric arc furnace electrical automation control system includes many links and equipment, and collaborative control optimization integration can achieve efficient linkage between various links. Coordinate the electrical control system of the electric arc furnace with the raw material supply system, flue gas treatment system, etc., adjust the supply quantity and speed of raw materials in a timely manner according to the operation of the electric arc furnace, ensure that the electric arc furnace is always in the most suitable raw material supply state, and reduce energy waste caused by shortage or excessive raw material supply. Coordinate the operation of the flue gas treatment system, adjust the operating parameters of the treatment equipment according to the amount and composition of flue gas generated by the electric arc furnace, thereby improving the efficiency of flue gas treatment and reducing energy consumption. By leveraging collaborative control optimization and integration, breaking through information barriers between various links, achieving resource sharing and collaborative work, and improving the energy efficiency level of the entire electric arc furnace production system.

（3） Constructing an adaptive regulation mechanism that adapts to complex working conditions and changes

Electric arc furnaces encounter various working conditions in actual operation, such as fluctuations in raw material composition, changes in grid voltage, and so on. By establishing an adaptive adjustment mechanism, the operating parameters of the electric arc furnace system can be adjusted to achieve the most energy-efficient state. The adaptive adjustment mechanism is to quickly calculate the latest control parameters and automatically change the operating status of the equipment. It can automatically increase the power output of the electric arc furnace, ensuring that the arc can burn continuously and stably; The raw material composition and processing parameters can ensure the quality of melting and reduce energy consumption.

（4） Implementing intelligent and efficient maintenance solutions through remote operation and maintenance management

Remote operation and maintenance management is a key direction for intelligent optimization of electric arc furnace electrical automation control systems. After creating a remote monitoring platform, it is possible to achieve remote monitoring of the operation status of the electric arc furnace, diagnose and warn of operation and maintenance faults, detect hidden problems as early as possible, and deal with them to prevent further faults from occurring. Operation and maintenance management can also achieve remote debugging and upgrading of equipment. When the system needs to be improved or updated, close the operation to improve operation and maintenance efficiency. Moreover, the remote operation and maintenance management platform will accumulate a lot of operational data, providing data support for further improvement and enhancement of the system, thereby achieving intelligent and efficient maintenance of the electric arc furnace electrical automation control system.

（5） Integrating digital twin technology to achieve simulation driven intelligent decision optimization

In the intelligent optimization process of electric arc furnace electrical automation control system, the integration of digital twin technology is a highly promising means. By constructing a virtual simulation model that is highly consistent with the physical electric arc furnace system and synchronizing the operational data collected by sensors in real-time to the digital twin platform, holographic reconstruction and dynamic tracking of the operating status of the electric arc furnace can be achieved. In a virtual environment, operation and maintenance personnel and control systems can perform real-time simulation calculations and predictive analysis on key parameters such as temperature changes, arc stability, electrode movement, and power consumption during the smelting process. They can identify potential operational risks and energy consumption anomalies in advance and test the effectiveness of different optimization schemes before making actual adjustments, thereby reducing trial and error costs.

For example, in the process of switching between different processes for high carbon steel and low carbon steel, the digital twin model can simulate the melting time, temperature rise rate, and power consumption changes under different parameter settings based on the type of raw materials and energy consumption model, helping the system intelligently select the most energy-efficient control curve. This technology also supports simulation driven intelligent decision-making. By coupling with AI algorithms and combining real-time production data and historical operating rules, it automatically recommends energy-saving operation strategies and equipment operating rhythms, promoting the transformation of the entire control system from "passive regulation" to "active predictive optimization".

3、 Conclusion

The energy efficiency improvement and intelligent improvement of the electrical automation control system for electric arc furnaces in the metallurgical industry are key means to promote the development of the metallurgical industry towards a green and efficient direction. By updating and improving hardware devices, adjusting control strategies, and perfecting monitoring systems, as well as utilizing intelligent algorithms, integrating collaborative control improvements, forming adaptive adjustment mechanisms, and implementing remote operation and maintenance, the energy efficiency level of the electric arc furnace electrical automation control system can be effectively enhanced, achieving intelligent and efficient operation of the electric arc furnace. In the future, with the continuous development and innovation of technology, the energy efficiency improvement and intelligent improvement methods of electric arc furnace electrical automation control systems will continue to be perfected and developed, thus adding new vitality to the sustainable development of the metallurgical industry.

References

[1] Research on the Application of Intelligent Technology in Electrical Engineering and Its Automation Control [J]. Zhang Guilong Automation Applications, 2024 (S2)

[2] Research on Intelligent Electrical Control System in Metallurgical Enterprises under the Background of Industry 4.0 [J]. Wang Liangwei Metallurgy and Materials, 2023 (11)