With the proposal and continuous deepening of the "double carbon" goal, the country's emphasis on energy management has gradually strengthened. Following the development concept of "innovation, coordination, green, openness and sharing", it is required to promote resource conservation, build a clean, low-carbon, safe and efficient energy system, and reduce energy consumption.
As a large energy consumer, the steel industry is one of the key industries for energy conservation and emission reduction. However, affected by comprehensive factors such as technical level, process equipment and management level, there is still a certain gap between the average energy efficiency level and the advanced level of the mainland steel industry, in addition to equipment updates and process upgrades, it is also necessary to use intelligent, informatization and other means to upgrade and transform to promote the realization of energy conservation and consumption reduction goals.
(T@Energy Smart Energy Management System)
In view of the common problems in the steel industry such as energy consumption and emissions are not easy to supervise, the transparency of the production process is low, the production plan is difficult to coordinate, the equipment operation monitoring is missing, and there are information islands between the systems, Kangpai Intelligent has developed a smart energy management system, using the Internet of Things technology, big data algorithm analysis technology and digital twin technology, combined with the process links and energy consumption characteristics of steel production, to create a smart energy management platform in the steel industry.
The intelligent energy management system realizes the automatic collection, storage and uploading of real-time data of the factory, strictly controls the production plan, improves the efficiency of the production process, reduces energy consumption and emissions, helps the energy management of steel manufacturing plants to change to high efficiency, energy saving, green and environmental protection, and promotes the achievement of the "double carbon goal".
Project objectives
1. Build a data storage center, complete the AI analysis of enterprise data, and realize the docking and sharing of energy consumption data;
2. Build a factory data collection ring network, complete localization deployment, and realize automatic data collection and upload;
3. Real-time monitoring of production operation status, reduce operation and maintenance costs, and improve work efficiency;
4. Provide various energy consumption data analysis to provide data support for energy audit work;
5. Assist the management to fully grasp the use of various energy sources, and promote the planning and implementation of energy conservation assessment.
Project overview
T@Energy intelligent energy management system, through the collection of energy consumption and operation information of each energy consumption monitoring point, the formation of energy consumption classification, sub-itemization, sub-regional statistical analysis, unified energy scheduling, optimization of energy media balance, improve environmental protection quality, reduce the comprehensive energy consumption of enterprises and improve labor productivity, to provide customers with scientific energy management means, to help customers use energy more effectively, to achieve "energy-saving management, green efficiency".
System architecture
The architecture design mainly takes the data acquisition system and the data application system as the core, and builds a comprehensive energy management platform, which is mainly divided into four parts: field device layer, network communication layer, server layer, and energy efficiency management application layer.
System functionality
01. Improvement of energy control
Departmental energy consumption sharing KPIs, high energy consumption equipment efficiency maintenance monitoring, unit production energy consumption tracking, carbon emission management.
02. Comprehensive energy consumption analysis and AI prediction and early warning
Use big data crawlers to establish various analytical models, calculate energy consumption per unit of product, and establish reasonable energy efficiency targets to monitor energy consumption. Set the target value of the regression analysis based on the product and make predictive early warnings.
03. Opportunity identification, quantification and energy saving monitoring
Real-time energy consumption monitoring of energy consumption units, quantitative analysis and monitoring of energy savings and waste, identification of energy saving opportunities, through management improvement and technological transformation, saving energy expenditure.
04. Carbon emissions and forecasting functions
For the total emissions of enterprises and the accounting of emissions of various processes, process units, key energy-using equipment, etc., to meet the carbon emission calculation and forecasting needs of different industries and different situations.
05. Energy expert system
Based on big data, through the calculation of different types of energy data, a knowledge base of more than 2,000 kinds of solutions has been formed, on the basis of which there are power supply and distribution expert systems, boiler expert systems, motor expert systems, steam expert systems, water supply and drainage expert systems and compressed air, oxygen nitrogen argon expert systems, etc.