Artificial Intelligence | Machine Learning | Natural Language Processing Gradyent | Transform District Energy Networks


Enterprise, Renewable Energy, Energy Management, Energy Supply Management Utrecht , Netherlands

Gradyent

Artificial Intelligence | Machine Learning | Natural Language Processing


Gradyent | Transform District Energy Networks

Gradyent

Renewable Energy, Energy Management, Energy Supply Management


Utrecht , Netherlands

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.

 

 

B2B

1 to 25

Series A

$12.09M

Scaling Up

2019

 
 

Renewables Energy

10% Lower CO2 Emissions
30% Lower Heat Losses
20% Lower Capex

Increase Efficiency

 
 

Analytics
Service

Yes

Active

 
 

   Machine Learning
   Natural Language Processing


Energy Management Tools

Energy Management Tools


Video

Video

Text

Text

Structured

Structured

 

   Software


Google Cloud

Google Cloud

Python

Python

C/C++

C/C++

AWS

AWS

SQL

SQL

Azure

Azure

Mongo DB

Mongo DB


Machine Learning Algorithm

Machine Learning Algorithm

Deep Learning Algorithm

Deep Learning Algorithm

 
 

Jun 2022

  • Gradyent Partnered with Uniper

Apr 2022

  • Helen has Built an Energy Platform with Gradyent
 
 

View All

Business Development Representative

Rotterdam

Solution Lead

Rotterdam

Solutions Engineer

Rotterdam

DevOps Engineer

Rotterdam

 

AI/ML Professionals

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4

1

$10.1M

Company was founded 2019 and it took almost 3 years (Aug 2022) to raise first external round

 
 

Date

Round

$ Raised

Investors

08/16/2022

Series A

$10.1M

Capricorn Partners, ENERGIIQ, Helen Ventures, Eneco Vantures

Date : 08/16/2022

Round: Series A

$ Raised: $10.1M

Investors: Capricorn Partners, ENERGIIQ, Helen Ventures, Eneco Vantures

 

Investors

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Robert Vrancken


Robert Vrancken
Founder & CTO

Hervé Huisman


Hervé Huisman
Founder & CEO

Freek Smelt

Freek Smelt
Co-Founder

Michel Koning

Michel Koning
Chief Commercial Officer

Lizzy Veldt

Lizzy Veldt
Chief of Staff

 
 

Potential Customers

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