Start saving energy and
reduce emissions with Gradyent
There is an increased pressure on both cost efficiency and emission reduction. Therefore, heating networks are trying to reduce temperatures while adding more sustainable heat sources. This results in highly complex heating networks.
Current Situation
Vision of modern networks
In the meantime, many district energy networks have old or even outdated control systems due to legacy in hard & software with limited or no dynamic optimization.
Current Control Systems
Modern Control Systems
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!
Setup in less than 2 months
Ennatuurlijk is a district heating company in the Netherlands with 40 grids and 85k connections. Learn how they want to make the Netherlands more sustainable and how the cooperation with Gradyent came into play.
Eneco is the largest district heating company in the Netherlands and one of the largest Dutch energy companies. Learn about the challenges they faced and how they tackled them together with Gradyent.
Used by some of the largest District Heating networks in Europe
Transform your heating network with the power of the Gradyent Digital Twin
Our platform creates value for the following application areas.
Reduce heat losses, enable low temp heat sources
Reduce pump costs & resolve pressure issues
Best possible deployment of heat sources & buffers
Put smart meter data to work
Benefit from network storage, optimize demand
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.
To support multiple heat sources (e.g. Geothermal) in the network and operating on lower temperatures implies questions about which heat source needs to be utilized first, second, etc. (the so-called merit order). What will become the ‘stand-still’ points then? And how does that function in times of high electricity pricing? These are complex matters but with great emissions and financial gains.
Driven by EU regulations, most of the District Heating operators have plans to invest or are already investing in smart meters. Most of the asset owners see these investments as high, mandatory, and only useful for improved invoicing processes. We also see the opportunity of using the data to granularly train the Digital Twin to an even higher extend (without compromising GDPR regulations, of course).
Peaks in the network are important drivers for the network design and therefore the costs. Currently, some operators are making complex agreements with large customers for peak shifting. With our dynamic and holistic grid approach, we can capitalize on the potential network storage to some extent without the complex agreements.
Flexible solutions to utilize our platform based on your needs
A Digital Twin from your network based on historical data, identifies issues and spots optimization opportunities.
A live read connection from your network into our Digital Twin allows you to live spot opportunities as a decision support system.
Connected to our platform, we will provide the most optimal settings to your SCADA system, any time, all the time.
New or expansion plans simulate the future with our Digital Twin and allow you to validate scenarios in the most realistic way.
Discover concrete steps that help district heating networks prepare their organization for this transformation
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. For our planet, more than 10% reduction of heat losses, results in the following.
More than 2.5 billion Megaton CO2 emissions prevented annually
More than 1 billion m³ natural gas saved annually
Sector profitability up by more than 3B€ with many networks co-owned by the public
45-70 PJ (petajoule) lower heat losses
Start saving energy and reduce emissions.
Management Team
CEO & Founder
Management Team
CTO & Founder
Management Team
CCO
Management Team
COO & CFO
Management Team
CEO & Founder
Management Team
CTO & Founder
Management Team
CCO
Management Team
COO & CFO
Get in touch
We would like to hear from you. Here is how you can reach us.
Stationsplein 45, Unit D2.112, 3013 AK Rotterdam
info@gradyent.ai
+31 10 3070 301
