Industrial energy intelligent prediction scheduling optimization technology: Improving the level of energy system management and control to implement the concept of energy conservation and emission reduction to the end

From June 13th to 19th is the 32nd National Energy Conservation Publicity Week in my country. The theme of this year's propaganda week is "green low carbon, energy conservation first". As a pillar industry of the national economy, industry is also the main proportion of energy consumption and exhaust emissions. Under the "dual carbon" goal, reasonable and effectively improving industrial energy utilization and reducing emissions have become the focus of the country and the world's industrial development. In the selection results announced by the Geneva International Invention Exhibition, Zhao Yan, Wang Wei, Han Zhongyang, Jin Feng, Chen Long and other teachers such as the Department of Electronic Information and Electrical Engineering of Dalian University of Technology "Industrial Energy System Multi -time Forecast and Intelligent Schedule "Optimized technology" won the International Gold Award in one fell swoop.

Professor Zhao Yan's team has long been committed to research in the direction of complex industrial process control and industrial artificial intelligence applications. As early as 2008, the team of Professor Zhao Yan paid attention to many problems in energy utilization in the industrial system, and launched related research by mechanism, data, and knowledge mixed -driving instead of simply manual deployment. Concentrated research helps more companies to achieve energy conservation and emission reduction, cost reduction and efficiency. From a single time scale point to predict the multi -time -scale interval forecast, from the undertaking of a single project to the popularity of industrial enterprises and parks, from customized development to platform promotion, in the direction of this actual service of industrial production, teams in the team, team The personnel have been studying for more than ten years.

In the context of the relatively fixed production process and equipment, starting with artificial intelligence and industrial big data analysis, these technologies have been started, and solutions are formed through the optimization of model algorithms, which has become a feasible method for reducing industrial energy consumption emissions. Through long -term on -site surveys, the team has determined the optimization of trends prediction and dispatching as the core of this technology, that is, based on prediction, optimize the computing energy balance scheduling scheme, thereby reducing the dependence and limitations of artificial experience, while achieving the optimization effect, while the optimization effect is achieved It can also meet the urgent needs of enterprises.

How to put the theory into practice to achieve the expected application effect is the difficulty of technical personnel to overcome. In order to improve the intelligence level of the system and the applicability of scene applications, on -site surveys cannot be ignored. Two or three -month field survey is even more "commonplace" for teachers. In repeated investigations, it is difficult to collect information provided by the personnel provided by the site personnel. The experience of different objects is different, the words are different, and the thinking is jumping. The content of the developers understands the computers and editing into software, and it also requires a strong integration application capabilities. In addition, how to face different application scenarios, basic equipment, energy media, response duration, etc. to implement corresponding prediction specific model construction, and give prediction results at an appropriate time scale; Knowledge and reasonable expression, integration, and use also need to continue to study breakthroughs. In order to ensure the implementation of the theory in actual operation, the main members of the team basically have their own special technologies, and continue to follow up within a period of time after software development. In the process of practical application, the team personnel are also constantly renewing the technology. While taking into account the basic needs of most factories, they also investigate and miss the situation of various factories. The huge role played by this technology in actual production has produced a demonstration effect, which has derived the strong needs of more enterprises.

The project has accumulated technical accumulation during leisure, and the research and application is made during the implementation of the project. The team members continued to implement this rhythm, completed the product version iteration, and the technology matured. Nowadays, the average accuracy of the multi-time-scale prediction model of the industrial energy system is more than 90%. The scheduling optimization technology can be 1.5-2%of the site energy conservation. Related software has been applied in more than ten industrial enterprises and parks. In addition, the team also takes the lead to undertake the national key research and development plan "Key Scientific Problems of Transformation Technology" special "industrial park multi -energy stream comprehensive control and collaborative optimization" project, hosting or participating in a number of national natural sciences that are optimized for industrial system operation optimizations and optimizations Fund key projects, national key research and development plans and other projects. The research results have also been successfully applied to production reality. The cumulative income increase of revenue for enterprises has obtained significant social and economic benefits. Facing the main battlefield of the national economy, team members practice "innovation technology, serve the country, and benefit the people". The purpose. "Our goal has always served the actual industry. What technology we need to develop and develop," said the person in charge of the project. "Said the person in charge of the project.

Of course, the team members have more ideas for the development of this technology. Continuously promote the localization process of technology, and implement the targetedness of different parks in order to achieve better practical results; in the process industry, continue to expand the scope of business to form an overall solution of coverage plans, scheduling, operation, and control. Based on the actual situation, give more specific and reasonable suggestions; under the guidance of the two carbon policies issued by the state, while increasing energy conservation and emission reduction, it will be studied in the direction of "realizing green and low carbon transformation". Related parts such as carbon flow have been further explored to actively respond to the country's ecological strategy. The team members will continue to take root in this technology field, continue to respond to the actual needs of the main battlefield of the industrial national economy, promote product platformization and intelligent technology innovation, and do not neglect on this scientific research road.

Content source: Dalian University of Technology News Network

Edit: Zhang Tianzheng

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