AI artificial intelligence technology is an important driving force for new industrialization. With the gradual implementation of AI technology in the industrial field, the process of industrial digitization has entered a new stage – the integration of AI technology and industry knowledge will bring about a great improvement in productivity and efficiency. In the industrial field, by integrating cutting-edge technologies such as AI, big language models, and machine learning with industrial automation expertise, enterprises can achieve highly intelligent industrial automation from dimensions such as quality and output prediction, predictive maintenance, and human-machine collaboration.

 

 

 

At present, Schneider Electric has applied AI technology to specific scenarios in energy management and industrial automation, helping users accelerate energy conservation, carbon reduction, and intelligent operation. From production scheduling prediction, control of water-cooling equipment such as pumps and frequency converters, optimization of beer filtration process, optimization of automotive painting process, to energy-saving scenarios of HVAC equipment such as refrigeration and air compressors, Schneider Electric can be seen empowering users through AI technology.

 

Next, let’s take the HVAC cold station scenario as an example to see how AI technology can bring value.

 

AI optimization plan for HVAC cold station, helping users achieve optimized control and intelligent energy conservation

 

HVAC systems can control the temperature and humidity of the air and play a crucial role in fields and industries such as pharmaceuticals, electronics, critical mission facilities, and data centers. The air conditioning refrigeration station, as the cold source part of the air conditioning system, undertakes the task of providing chilled water for the air conditioning system. The low-carbon and stable operation of cold stations is related to the energy conservation of the entire air conditioning system and the overall energy efficiency of users.

 

Traditionally, enterprises usually use PID control method for single loop closed-loop control, which heavily relies on the experience of on-site operators. Due to the control system targeting a single loop, each system is regulated in isolation, lacking the ability to optimize the entire system and predict the load of the cold station, which neither achieves maximum refrigeration efficiency nor ensures safe and stable operation. In this regard, Schneider Electric’s intelligent cold station solution combines AI modeling and data analysis algorithms to build an intelligent “brain” at the system level, predict the overall load and energy consumption of the system, find global optimization control methods, and use the verified system model to find the best efficiency point for the operation of the computer room in real time. The energy-saving rate can be increased by more than 10% compared to traditional energy-saving methods.

 

At the same time, the intelligent cold station solution combines AI technology with PID control, providing effective safety and fault detection for the system without affecting existing PID control, ensuring normal operation of the system, and bringing more than 50% improvement in personnel efficiency, achieving efficient operator duty and safe and stable equipment operation. Specifically, this plan will achieve system optimization in the following four steps:

 

1. Modeling and data collection: By modeling and visualizing the cold station system, environmental data, real-time and historical system operation data, and active testing data are collected and cleaned to ensure the accuracy and completeness of data, providing data support for energy consumption analysis.

2. Accurate prediction: Utilizing AI algorithm models such as AutoML automated machine learning engines to process and calculate various data, achieving minute level prediction of refrigeration unit/station load, and helping enterprises accurately control energy demand.

3. Optimization solution: Based on the mechanism framework and deep learning technology, establish a device level performance prediction model to assist enterprises in active prediction and optimization.

4. Strategy output: By calculating and comparing tens of thousands of control parameter combinations under the same load, find the control parameter combination with the lowest system energy consumption, and output the optimal control strategy for the enterprise.

 

At present, Schneider Electric’s intelligent cold station algorithm has been successfully applied in many industries such as commercial buildings, data centers, semiconductors, and automobiles. In the HVAC energy-saving optimization project of a data center in a certain bank, Schneider Electric’s intelligent cold station solution optimizes the on-site chiller unit, adjusts the frequency control of the water pump based on temperature difference, adjusts the water supply temperature and the set value of the supply and return water temperature difference according to load demand, and provides optimization control strategies for the chiller unit in three scenarios: safe mode, low-power performance mode, and high-power performance mode. After one week of implementing the optimization strategy, the estimated effect shows that the rated operating condition performance (COP) of the refrigeration unit in the data center has increased by nearly 20%, and the average power consumption has decreased by 16.4%.

 

Driven by scenario applications, with the goal of improving quality and efficiency, and continuous optimization, the rapid development and iteration of AI technology have brought unprecedented wisdom and strength to industrial development. According to application data from Schneider Electric’s own factories and dozens of industry-leading customers, solutions based on AI technology can help users achieve annual energy consumption reductions of 5% -10% and efficiency improvements of 3% -5%.

 

As a global leader in industrial technology, Schneider Electric is committed to continuously empowering the digital transformation of various industries by integrating advanced technologies such as AI. On June 6th, Schneider Electric is about to hold the 2024 Innovation Summit with the theme of “Dual Engine Moving Forward, Digital Intelligence Emerging”. A roundtable meeting with the theme of “AI Accelerating Digital Transformation and Moving towards a New Era of Intelligence” will be held on site, showcasing more innovative technologies and successful practices for the industrial and energy sectors, and helping industry accelerate towards an efficient and sustainable future! Stay tuned.