The Gradyent Digital Twin is specially designed for heating networks. In this case, a digital twin is a virtual simulation of a physical heating network. This allows for multiple simulation scenarios and analytics and therefore results in the most optimal settings for the network, any time all the time. The Gradyent platform analyses the customer heat demand on a granular basis and combines this information with the hydraulic and thermo-dynamic losses within the network. This is the optimal input for different heat sources within the network. The Gradyent Digital Twin matches customer demand and heat production in the most optimized way, resulting in lower energy losses and emission reductions! 

A common issue for District Heating networks is that heat losses are too high. This is driven by too high temperatures in the system. Additionally, we often see that it is difficult to oversee the critical constraint of the network. By simulating the grid and advanced granular demand forecasts, new insights (e.g. forward temperatures) can be found while typical constraints (e.g. minimal temperature at consumers) are always met. In some cases, the hydraulics of the system are considered a given. Although sometimes unpredictable, pressure issues at lower temperatures occur, or unreliable pump operation results in trips. Using our holistic and dynamic modelling approach, new opportunities arise by improving both pressure and flows, leading to energy savings. Approximately 50% of all energy consumption in the world is used for heating and cooling. District heating networks are a large portion of this. At Gradyent, we have the ambition to assist District Heating companies in applying new technologies as our Digital Twin to strongly reduce energy consumption.