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The heating ventilation and air conditioning system is the largest energy consumer in modern buildings, and its energy consumption ratio is often as high as 40%-60%. The traditional operating mode based on fixed set points and simple timing control can no longer meet the pursuit of ultimate energy efficiency under the “double carbon” goal. Furukawa Cloud Technology’s smart heat energy-saving system came into being. It is no longer an isolated RW Escorts controller, but a building thermal system “smart brain” that integrates the Internet of Things, big data and artificial intelligence technology.
1. System architecture: three-layer technology stack to achieve closed-loop optimization
A mature smart heat transfer system is usually built on a three-layer technology stack of perception control layer, edge computing layer and cloud platform layer.
1. Perception control layer: the “senses and limbs” of the system
This layer is responsible for the collection of data from the entire system and the execution of final control instructions.
Surrounding Rwandans Sugardaddy situation awareness: arrange high-precision temperature and humidity sensors, CO₂ concentration sensors, illumination sensors and even occuPancy sensors build a complete monitoring network of indoor and outdoor environmental parameters.
Equipment status awareness: Install smart meters, flow meters, pressure sensors and thermometers on key equipment such as chillers, water pumps, cooling towers, air-conditioning boxes, valves and other key equipment to collect their operating efficiency, load rate and start-up and stop status in real time.
Intelligent actuator: Using frequency converters and intelligent regulating valves as the “limbs” of the system Rwanda Sugar to accurately execute the optimized control strategy.
Rwanda Sugar Daddy 2. Edge computing layer: local “nerve center”
Edge gateway is the key to ensuring the timeliness and reliability of the system.
Data aggregation and protocol conversion: Collect data from different brands and different protocol devices, and uniformly convert them into standard formats for upload.
Real-time control and strategy execution: running the core control logic locally, even when the network is disconnected from the cloud, the system can be basically running stably and execute the issued optimization strategies.
Edge AI: It has preliminary data analysis capabilities and can perform local and rapid anomaly diagnosis and real-time tuning.
3. Cloud platform layer: the global “decision-making brain”
The cloud is responsible for the storage, in-depth analysis and global optimization of massive data.
Data warehouse: Use time series database to efficiently store massive operational data.
AI algorithm engine: This is the core competitiveness of the system, with multiple built-in intelligent algorithm models.
Rwanda Sugar Daddy Visualization and interaction: Through the Web interface, it provides managers with a panoramic visual view of system energy efficiency, comfort, and equipment health status.
Rwanda Sugar Daddy 2. Core technology: from “experience control” to “model prediction control”
1. Global optimization based on model prediction control
This is the core technology of the system. MPC no longer only reacts based on current conditions, but is based on building thermodynamic models and weather forecast data to predict building load, outdoor temperature and humidity for a period of time in the future (such as 24 hours), and use this as a basis., and find out the equipment operation strategy with the lowest total energy consumption in the future period.
Optimization objects Rwanda Sugar Daddy objects: chiller start-stop combination, water supply temperature setting, water pump frequency, fresh air valve opening, etc.
Solution goal: Minimize the total energy consumption (electricity, gas, etc.) of the system under the condition of meeting the comfort constraints of all regions.
Technical advantages: It can make full use of the “thermal inertia” of the building to achieve “early storage of cold/heat and flat peak valley filling”, avoid peak electricity prices, and achieve a win-win situation of economy and energy efficiency.
2. Chiller group control and load distribution
The system uses algorithms to calculate the total cooling load of the building in real time, and based on the efficiency curve of each unit, dynamically decides which units to turn on and how to optimally distribute the load among them to ensure that the units always operate in the high-efficiency range and avoid “big horse carts”.
3. Adaptive comfort model and on-demand supply
Abandoning the fixed temperature set point, Rwanda Sugar introduces a predictive average voting number model, comprehensively considering temperature, humidity, wind speed, wearing thermal resistance, exercise intensity and other factors, static Rwanda Sugar Daddyadjusts surrounding state parameter settings. Combined with people counting sensors, it can realize on-demand supply of “automatically open when people come and automatically close when people walk” in spaces such as conference rooms, eliminating unnecessary energy consumption.
4. Equipment health prediction and maintenance
By analyzing the current and vibration data of key equipment such as water pumps and fans, machine learning models are used to provide early warnings of bearing wear, impeller fouling and other failures, to achieve predictive maintenance, prevent inefficient operation and sudden shutdowns of equipment, and improve the long-term energy efficiency of the system from the maintenance level. The technical essence of the smart heat circulation energy-saving system is to build a digital twin that is synchronously mapped and bidirectionally interactive with the physical heat circulation system.
It is driven by data, transforming the heat transfer system from a “big energy consumer” that relies on fixed rules to an “efficiency engine” that can sense the surrounding conditions, predict the future, and continuously optimize itself. This is not only an upgrade of the management strategy, but also a profound revolution in the construction energy management paradigm, providing a solid technical foundation for the company to achieve the goals of sustainable operation, cost reduction and efficiency improvement.
Review and Editor Huang Yu
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