A feast of artificial intelligence is under way. On July 6, the 2023 World Artificial Intelligence Conference with the theme of “Connecting the world and generating the future” opened in Shanghai. As the overall solution provider of intelligent manufacturing for process industry, Zhongcong Technology helps the green, low-carbon and sustainable development of process industry with advanced AI technology, products and solutions. Dr. Yu Haibin, senior Vice President of China Control Technology, was invited to participate in the conference’s “Intelligent Aid Dual Carbon Traces” 2023 Intelligent Trend Forum, sharing the latest practice of China Control technology in related fields, and discussing the cutting-edge trends of artificial intelligence and dual carbon technology, carbon neutrality, and ESG topics with industry professionals.

At the forum, Dr. Yu Haibin focused on the “135 customer value innovation model” as the core, combined with the deep accumulation of the “dual carbon” strategy of the central control technology, made a special report from the perspective of professional product technology, “optimal” design, extremely “intelligent” operation – Low-carbon transformation of AI empowered process industry “, and participated in the roundtable dialogue of the forum.

The most “optimal” design, extremely “intelligent” operation

In the report sharing session, Dr. Yu Haibin combined the low-carbon needs of the process industry from process research and development, design to operation, from the two key dimensions of process research and development design and production and operation stage, in-depth elaborated the latest practice of central control technology supported by AI technology to help factories save energy and reduce carbon. He believes: “In the process industry enterprises in the process research and development and design stage, the focus is on catalyst and equipment research and development and process design; In the production and operation phase, the key is to realize intelligent operation through supply chain, planning, scheduling, and operational optimization.”

1// Process development and design phase

Taking process research and development as an example, catalyst research and development technology is the core technology of low-carbon process. Through the industrial catalyst research and development platform of in-process technology, efficient catalysts can be selected, greatly shorten the catalyst research and development cycle, and reduce experiment costs and trial and error times. With the help of machine learning algorithm, central control technology can effectively predict the path and product type of catalytic reaction process. Prediction of catalyst performance by big data analysis, including selection of catalyst and optimization of catalytic reaction conditions; Through high throughput calculation, catalyst materials with medium and high performance can be quickly selected and optimized.

The optimization design of energy-saving and low-carbon process processes involves professional software tools and platforms. In 2022, Zhongcon Technology has released the Process industrial Process Simulation and Design Platform (APEX) for process industries, which strongly supports process design engineers to carry out process optimization analysis and energy-saving process design, and assists energy-saving equipment selection. Assist to carry out the bottleneck analysis of plant energy saving, and help engineers find the direction of energy saving technical reform. With the process mechanism model established by APEX, the operation of the device under different working conditions is simulated, and a large number of device operation simulation data is generated, providing unlimited data sources for the training of industrial AI models.

2// Production and operation phase

In the plant operation stage, Dr. Yu Haibin combines different business application scenarios, This paper focuses on the optimization of supply chain, planning and scheduling, operation, process plant, reduction furnace, MCS plant, rotary kiln, utility system, control steam power system, control refrigeration and circulating water system, and control air pressure system with the help of artificial intelligence and big data technology Advanced applications in many key links and fields, such as collaborative management, accurate prediction of energy demand, accurate prediction of carbon emission quota surplus and shortage, effectively help process industrial enterprises to achieve energy saving and carbon reduction.

For example, in the operation process of the device, in the face of different industries and different characteristics of the production device, Dr. Yu Haibin pointed out: “Some devices are easy to establish a mechanism model and can be optimized based on the mechanism model, some mechanism models are not clear and must be optimized based on big data models, but even the optimization control based on the mechanism model also needs to rely on data verification, steady-state detection and other data analysis methods to assist, so AI also plays an important role in the operation optimization of the device.” ”

Another example is in the thermal power production system, based on a large number of historical steam consumption data on the user side, the central control technology can accurately predict the steam demand, and through the coal consumption, steam consumption, power generation data online calibration of boiler, turbine and pipe network model parameters, optimize the calculation of wind-coal ratio, the optimal steam supply temperature and pressure, linkage control system, issue control instructions, optimize the operation. It can effectively reduce coal consumption for heating and power supply. Based on the above technology, in the application practice of a large enterprise, with the help of the mechanism model of AI auxiliary equipment, the central control technology helps it to achieve a stable pressure operation rate of the steam supply network by 16.63%, and the steam production of tons of coal has increased by more than 0.7%, greatly reducing coal consumption.