Smart physical models
- Combines both hydraulic and thermodynamic models
- Defines time lags and heat propagation
- Fills in the blanks with AI, based on available sensor data
Stationsplein 45, Unit D2.112, 3013 AK Rotterdam
Transform your district heating network with our powerful Digital Twin
Start saving energy and
reduce emissions with Gradyent
Heating networks become more complex
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
- Few central heat sources
- Higher temperatures
- Lower efficiency
Vision of modern networks
- Multiple decentral heat sources
- Low temperatures
- High efficiency
In the meantime, many district energy networks have old or even outdated control systems due to legacy in hard & software with limited or no dynamic optimization.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
- Legacy software, often built in-house
- Limited insights into drivers of network efficiency
- Stability only, no optimization
Modern Control Systems
- Complex and dynamic modeling, made easy
- Continuous visibility and transparency
- AI powered intelligence
- Automated dynamic optimization and controls
The power of the Gradyent Digital Twin
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.
Digital Twin
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!
Maximum value
from all data
- Utilizes a holistic approach from heat sources to end customers and everything in between
- Emphasizes combining different data sources, sensors, smart meters, and more
- Creates a valuable Digital Twin based on a limited set of data
Fill the blanks with AI
- Optimizes your network with Artificial Intelligence
- Employs rapid setup as AI learns from your historic network data
- Dynamically forecasts and optimizes in real-time
- Automatically adapts as your network expands over time
Secure & flexible
setup
- No system replacement necessary
- Always updated
- Secure access from anywhere
- Calculation power used to support our Digital Twin
Results in:
- 30% lower heat losses
- 10% lower CO2 emissions
- 20% lower capex
Setup in less than 2 months
Our customers
Used by some of the largest District Heating networks in Europe
Simulate.
Automate. Gain.
Transform your heating network with the power of the Gradyent Digital Twin
- Simulate, analyze and automate controls
- Allow a holistic approach from heat sources to end customers and everything in between
- Optimize temperature, hydraulics, dispatch & peaks
- Intuitive interface to really understand your network
- Easy setup in less than 2 months
Platform
Our platform creates value for the following application areas.
Temperature
Reduce heat losses, enable low temp heat sources
Hydraulics
Reduce pump costs & resolve pressure issues
Dispatch
Best possible deployment of heat sources & buffers
Smart Meters
Put smart meter data to work
Demand response
Benefit from network storage, optimize demand
Temperature
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.
Hydraulics
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.
Dispatch
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.
Smart Meters
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).
Demand response
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.
Solutions
Flexible solutions to utilize our platform based on your needs
Simulate & Improve
A Digital Twin from your network based on historical data, identifies issues and spots optimization opportunities.
Connect & Gain
A live read connection from your network into our Digital Twin allows you to live spot opportunities as a decision support system.
Automate Control
Connected to our platform, we will provide the most optimal settings to your SCADA system, any time, all the time.
Design & Expand
New or expansion plans simulate the future with our Digital Twin and allow you to validate scenarios in the most realistic way.
Partners
Our Mission – making sustainable impact on heating networks
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
Do you want to make an impact on your network?
Start saving energy and reduce emissions.
Team
Hervé Huisman
CEO & Founder
- Serial entrepreneur, former director at ASML and manager at McKinsey.
- Led large operational-, IT- and strategy programs at energy and tech companies
- Passionate about making real sustainable impact in the world
Team
Robert Vrancken
CTO & Founder
- Serial entrepreneur, previously Principal at Boston Consulting and CTO tech startup
- Experienced in tech, digital analytics and AI in energy
- PhD on fluid dynamics
- Passionate about scaling new technologies
Team
Niclas Kuipers
CCO
- Experienced director for several AI and tech start- and scale-ups.
- Prior, experience with multiple transformation programs at energy and tech companies
- Passionate about developing sustainable business with impact
Team
Peter Hulshof
COO & CFO
- Was principal at Boston Consulting Group and developer at Ortec
- Lead large scale change and execution projects in tech and energy sectors
- PhD in Applied Math
Team
Freek Smelt
Director Business Development
- Serial entrepreneur, former Business development lead at Essent
- Owns and runs several ventures in clean energy & sustainability
- Passionate about building great teams
Team
Ivo Fugers
AI Lead | Data Scientist
- Prior Senior Data scientist at ORTEC, one of the world’s leaders in optimization software and analytics solutions
Team
Kiana Afzali
Consultant and Solutions Engineer
- MSc of “Complex Systems Engineering and Management”
- Experienced in analysis of complex energy infrastructures
- Passionate about finding smart solutions for energy transition
Team
Joost Stam
AI Engineer
- Background in Applied Physics and Applied Mathematics, specializing in optimization and data science
- Experience in sustainable supply-chain optimization and smart energy systems
- Passionate about the energy transition and making real impact quickly
Team
Want to join our team?
Have a look at the open vacancies via the arrow below.
Get in touch
We would like to hear from you. Here is how you can reach us.
info@gradyent.ai
+31 10 3070 301
