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Autonomous control and optimization for district heating networks powered by AI

Digitalize your networks, with STORM!

  • Integrates seamlessly in substations using IoT
  • Contains self-learning data-driven algorithms that can scale
  • Requires minimal expert intervention enabling autonomous operation  

Benefits

For solution providers

  • Available as SaaS application on VITO’s FLEXharvester powered by MS Azure 
  • Accelerated Go-to-Market through the energy flexibility platform FLEXharvester!
  • Also integrates in your own cloud or on-premise data solution with ease
  • Extensive training available from VITO’s team of district heating experts
  • Supported by VITO’s technology roadmap for the next 5 to 10 years

For network operators

  • Reduces peak heat load and CO2 emissions by up to 20% 
  • Unlocks existing thermal storage capacity in your network at minimal investments
  • Customizable control objectives according to your business needs, e.g. flatten the load curve
  • Field-tested on multiple networks across the Netherlands, Sweden, France, and Belgium
  • Extensible to provide end-to-end optimal control from production to buildings

 

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

Ennatuurlijk, making smart use of district heating networks

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

Intelligent controller for district heating and cooling networks unlocks energy efficiency potential

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

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.

Our pilot partners

Veab-logo
Ennatuurlijk-logo
Mijnwater-logo
Paris-Saclay-logo
Logo-Vito
Logo-EnergyVille

Erik De Schutter

Business Developer