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Yuon ControlHeating Control System

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​Yuon optimizes the district heating network and predicts the exact energy demand. This adjusts the heat generation capacity to match the demand, efficiently utilizing thermal storage capacities. It provides an overview of the network, reduces the need for peak heat, and enhances understanding of the system. Our solution can be used for both new and existing networks.

 
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​Our learning and self-optimizing system optimizes the entire district heating network.

  • ​increases network capacity
  • ​reduces peak loads
  • ​provides transparency

​increases network capacity
​Our learning and self-optimizing system reduces the energy consumption per building and throughout the entire district heating network.

​breaks peak loads
​Accurate consumption prediction optimizes the load without compromising comfort on the consumer side and reduces CO2 emissions.

​provides transparency
​Real-time energy consumption measurement, proactive control, and automatic system monitoring enable overall control and optimized system management. 

 

​Optimized overall control with dashboard

​The optimized overall control of the district heating network is in your hands, with a click on your personalized dashboard. Automatic error detection alerts you to possible errors in your network, remote interventions are enabled, and billing processes are simplified.

 

​Intelligent and self-learning algorithm

​Through our intelligent and self-learning algorithm and the underlying concept of Model Predictive Control, the required energy demand is predicted based on various factors such as weather data. Our system knows every building in the network in the form of digital twins and automatically learns the thermal dynamics of the buildings using machine learning.

 

Model Predictive Control

​Through our smart control based on Model Predictive Control and the optimized network capacity of the district heating network, there are fewer peak loads and load optimization on the consumer side without compromising comfort.

Digital Twin

​We create a building model for each building and understand the thermal properties of the structure.

Machine Learning

​Continuous and automatic development of the building model based on our data.

Connected Network

​Our system is online, enabling automatic error detection, remote control, and simplified system management.

Model Predictive Control

​We can predict the required heating power and optimize its control.