Schneider Electric: Three arrows launched simultaneously, leveraging AI technology to accelerate energy transformation

Date: Nov 29, 2024 Views: 765

　　The rapid development of artificial intelligence (AI) technology is knocking on the door of change in various industries with surging innovative momentum. At the same time, the energy transformation, which has attracted much attention under the background of the "dual carbon" goal, is also changing with each passing day under the empowerment of digital technology. Benefiting from more comprehensive and accurate data measurement and collection methods, energy data is becoming increasingly rich and complete, which provides an important decision-making basis for enterprises' energy conservation, emission reduction, and consumption reduction, and also lays a solid data foundation for the application of artificial intelligence in energy transformation.

　　So, what role does artificial intelligence play in the process of energy transformation? Schneider Electric, a global expert in digital transformation in energy management and automation, looks forward to the development trend of this innovative direction.

　　Three arrows are fired at the same time, and artificial intelligence promotes the acceleration of energy transformation

　　As a leading company that has been deeply engaged in digital transformation for a long time, Schneider Electric has always paid close attention to the positive role of emerging technologies such as AI in the process of energy transformation. At the 2024 World Artificial Intelligence Conference, Zhang Lei, Vice President of Schneider Electric, Head of Digital Innovation Business in China, and Head of Schneider Electric (China) Software R&D Center, said: "At present, artificial intelligence has become an important driver for developing new quality productivity and promoting energy transformation, and plays an important role in reducing carbon emissions, optimizing energy demand, and improving operational efficiency.

　　Zhang Lei, Vice President of Schneider Electric, Head of Digital Innovation Business in China, and Head of Schneider Electric (China) Software R&D Center, was interviewed by the media at the World Artificial Intelligence Conference.

　　First, in terms of reducing carbon emissions, artificial intelligence can optimize the operating processes of energy-intensive industries such as industrial manufacturing, buildings, and transportation to achieve energy conservation and carbon reduction. For example, a public service facility of a heating company can effectively predict heating demand by using Schneider Electric's regional energy system and artificial intelligence loads, thereby optimizing energy use, reducing operating and maintenance costs, and effectively reducing carbon emissions.

　　Second, in terms of energy demand optimization, artificial intelligence can ensure the efficiency of energy use and cleverly avoid peak demand periods by optimizing the management of microgrids and electric vehicle charging stations. In this regard, Schneider Electric's artificial intelligence algorithms can continuously analyze data from generators, electric vehicle charging stations, batteries, backup generators, HVAC systems, lighting systems, uninterruptible power supply systems, combined power generation and heating systems, and efficiency metering to dynamically optimize energy supply and demand.

　　Finally, in terms of improving operational efficiency, artificial intelligence can help companies conduct data analysis, predictive maintenance, and process optimization to reduce the occurrence of failures and significantly improve equipment performance and energy efficiency. For example, Schneider Electric uses artificial intelligence algorithms to find the laws in the company's production process. On the premise of meeting production safety, it can find the optimal solution for the global equipment combination and parameters in the production process, thereby helping companies achieve energy saving and efficiency improvement.

　　Assisting the transformation of the demand side, making AI modeling "twice the result with half the effort"

　　With the continuous deepening of the construction of the new energy system, especially on the demand side, the process of terminal energy cleanliness and low carbonization is changing with each passing day, and AI technology is bound to become an indispensable support for promoting energy transformation.

　　An important reason is that most of the processes that generate energy consumption, whether it is industrial processes such as manufacturing processes or heating and cooling processes in buildings, need to be modeled and continuously optimized to achieve energy consumption reduction. That is, only by establishing a process model can the key influencing factors of energy consumption be analyzed in principle, abnormal energy consumption phenomena can be discovered and repaired, and targeted response plans can be formulated, thereby effectively reducing energy demand.

　　However, in many cases, due to the complexity of the process, it has become impractical to build models based solely on the basic laws of physics. Taking the building industry as an example, to build a complete building energy consumption model, not only does it require a large team of experts, but the details that need to be considered are also numerous.

　　In the face of such thorny modeling problems, artificial intelligence can "take a different approach" and provide a more efficient solution. For example, using machine learning technology within the scope of artificial intelligence, you can start with measured data and build a predictive model through learning, thereby achieving the effect of "getting twice the result with half the effort".

　　Zhang Lei pointed out that at present, applications that use AI technology to reduce energy consumption have been widely used in various industrial scenarios such as building heating and cooling, seawater desalination, home energy optimization or district heating systems. In time, the role and effect of such applications in energy transformation will inevitably be more widely and significantly exerted.

　　Practice and empowerment are equally important, and innovation is used to promote sustainable development

　　It is better to act than to talk. Zhang Lei introduced that today, artificial intelligence has become an important growth point for Schneider Electric's business. Whether it is the AI research and development layout that has been widely laid out in China and even around the world, or the integrated innovation carried out with ecological partners in various industries, Schneider Electric has been able to deeply integrate AI technology with a wide range of application scenarios as early as possible, and has taken the lead in becoming a "practitioner" and "enabler" of promoting energy transformation with AI technology.

　　A vivid example is that Schneider Electric's Wuxi factory has become a world-class "end-to-end lighthouse factory" through digital transformation. The EcoStruxure Microgrid Energy Advisor used in the project has greatly improved the performance of energy scheduling based on intelligent AI algorithms, and has achieved the ability to predict energy consumption and local production on the day before. With the help of this factor, the lighthouse factory has achieved 100% green electricity consumption while ensuring 100% safe and reliable operation of the system, and the average cost per kilowatt-hour of the factory operation stage has been reduced by 7%.

　　At the same time, Schneider Electric also actively plays the role of an "enabler", actively helping industry users to cope with energy efficiency challenges with artificial intelligence. Take the cooperation between Swire Properties and Schneider Electric as an example. When relying solely on traditional building automation systems, which have already faced energy-saving bottlenecks, Schneider Electric, based on a digital energy management platform and using AI algorithms, helped Swire Properties to forecast cold and hot loads, optimize cold station start-stop strategies, and optimize seawater group control strategies, raising the forecast accuracy to more than 95% and achieving more than 5% energy savings.

　　For another example, in the HVAC energy-saving renovation project of Dalian Bank Data Center, Schneider Electric optimized the terminal precision air conditioners in the computer room based on AI algorithms and machine learning, enabling them to dynamically output cooling according to actual needs, and made global improvements to the cold station control system, ultimately achieving a good effect of saving 31% of electricity consumption in the terminal air conditioning system and an estimated 20% increase in the cold station cooling efficiency.

　　Looking to the future, with the emerging technological iteration innovation and deepening of application, AI technology will surely write a bold and colorful chapter in the chapter of green and sustainable development with a more in-depth brushstroke. Schneider Electric will also work more closely with ecological partners from various industries, using artificial intelligence technology as a powerful engine to continue to inject strong momentum into promoting energy transformation and sustainable development in the entire society.

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