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For district heating operators

Are you a district heating network operator?

Would you like to increase the number of customers connected to your heating network, while using your current assets?

Then why not implement our self-learning district energy controller?

STORM uses the thermal mass of the building itself to respond to peaks in heat demand.

STORM enables you to connect more heat customers to your existing network while continuing to guarantee your production capacity without additional investments in infrastructure and production resources.

Your benefits

  • Increase the number of connected heat customers with existing heat production and distribution
  • Lower investment costs in new networks or network branches
  • Make use of existing assets: infrastructure and buildings
  • Optimisation of production mix
  • Greater financial yield thanks to CHP and heat pump inspection advice
  • Field-tested in the Netherlands, Sweden, France, and Belgium

Why implement STORM into your district heating network?

In the Mijnwater demo site in Heerlen (NL) STORM achieved the following results:

  • Capacity improvement of 42.1% = 48,000 homes that can be additionally connected to the network
  • Peak heat reduction of 17.3%
  • CO2 emission reduction of 6 kiloton/year

The Växjö demo site in Rottne (Sweden) achieved:

  • Electricity procurement reduction of 6%
  • Peak heat reduction of 12.7%

Download the article about our two demonstration sites

STORM - Testing and performance evaluation in two demonstration sites

STORM features

Peak shaving: heat demand is shifted from peak times to off-peak times when cheaper sustainable energy is available

Autonomous: self-learning and adaptive algorithms ensure that there is no need for expert intervention in order to reconfigure and make adjustments

Truly scalable: can connect to large and small heat networks, with connections to few or many buildings. Can easily scale to multiple heat networks. 

Easy integration: can be quickly and easily integrated with substations of several manufacturing brands

News

Demand side management in reach for every district heating network with STORM controller

23/06/2022

District heating networks suffer from high peak demand leading to inflated operational costs. High supply and return temperatures in the distribution network can cause up to 20% of the heat to be lost.

A unique and dynamic test environment for batteries and thermal systems

10/06/2022

Developers of products or systems powered by batteries, or of equipment for heating and cooling, for example, can turn to VITO/EnergyVille for a wide range of tests that meet all their possible questions and needs.

Heating networks: collective heating of buildings and houses

31/05/2022

In the field of heating and cooling with heating networks, Flanders is facing a catching-up proces

Intelligent algorithms add significant value to the heat network in Paris-Saclay

23/05/2022

The STORM District Energy Controller that uses advanced Artificial Intelligence (AI) based algorithms was deployed on the district heating network in Paris-Saclay in November 2021.

Crossbreed and VITO/EnergyVille sign letter of intent for cooperation on STORM District Energy Controller

21/02/2022

Runa acquires STORM for Chinese district heating market

16/11/2021

VITO and NODA bring their industry-leading technology for smart control of district heating networks to the Chinese market in collaboration with Runa, a leading heating equipment manufacturer in China. 

HeatriCity in AI4Cities

24/06/2021

VITO/Energyville was chosen as a supplier of its smart control technology for district heating networks, for the AI4Cities project.

Ennatuurlijk, making smart use of district heating networks

17/03/2021

The fact that we cannot go on heating our homes and businesses using fossil fuels forever is no secret.

The intelligent STORM controller for district heating and cooling networks unlocks energy efficiency potential

17/03/2021

The STORM project has successfully developed an innovative district heating and cooling network controller based on self-learning algorithms and artificial intelligence,  which was deployed and tested in two demonstration sites.

Flatten the curve and shift the energy demand with FLEXharvester/STORM District Energy Controller

17/03/2021

Not only the extent of the energy consumption, but also the moment of consumption affects the energy bill and the greenhouse gas emissions of large customers.

Erik De Schutter

Business Developer
STORM Controller
+32 492 977 923