STORM – Self-organising Thermal Operational Resource Management
The STORM project tackled energy efficiency at district level. It aimed to demonstrate that, thanks to a smart District Heating & Cooling (DHC) networks’ controller, energy savings can reach up to 30%. In that perspective, the project partners developed a controller based on self-learning algorithms, that maximised the use of waste heat and renewable energy sources in DHC networks. It was implemented in two pilot sites, at Mijnwater BV in Heerlen (NL) and Växjö Energi in Rottne (SE) in order to assess the resulting energetic, economic and environmental benefits. Through replication, dissemination and education efforts, the project outcomes were transferred to several stakeholders across the EU, and thus contributed to a wider deployment of intelligent DHC networks at the EU level.
The STORM project wanted to boost energy efficiency at district level through the use of waste heat, renewable energy sources and storage systems. It had many objectives to ensure the success:
- Research
- Building on state of the art technical developments and advanced business models
- Starting from control algorithms suited for both existing and new 4th generation DHC networks
- Using market-based multi-agent systems combined with reinforcement learning
- Applying self-learning and self-adaptive control, combining recent developments in model-based multi-agent systems and model-free controlCreating an add-on to many existing DHC network controllers and SCADA systems
- Developing an innovative controller for district heating & cooling (DHC) networks
- Balancing supply and demand in a cluster of heat/cold producers and consumers
- Integrating multiple efficient generation sources (renewable energy sources, waste heat and storage systems)
- Including three control strategies in the controller (peak shaving, market interaction, and cell balancing). Depending on the network, one or more of these strategies can be activated.
- Evaluation
- Demonstrating the benefits of smart control systems;
- Quantifying the energetic, economic and environmental benefits of the controller.
- Replicability
- Developing innovative business models needed for the large-scale roll-out of the controller at reduced costs
- Investigating exploitation possibilities to facilitate the platform market uptake
- Distributing the value amongst the different market players (producers, transporters, consumers of energy) by applying the control strategies in the controller
- Taking into account different market set-ups to replicate in other countries than the ones of the demonstrators
- Designing a scalable and performing self-learning control approach requiring limited external experts
- Increasing awareness on the need to control DHC networks in a smart way
EnergyVille's contribution
EnergyVille/VITO was the project coordinator of the H2020 STORM project and was responsible for the coordination, research and implementation activities carried out on the intelligent district heating and cooling controller. EnergyVille/VITO developed this controller in close cooperation with NODA from Sweden, a Scandinavian company and leader in intelligent energy systems. The network controller was evaluated in different seasons and implemented in 2 demo sites.
STORM-controller
In the meantime, this project has successfully ended and the STORM controller is available on the market. The STORM-controller was deployed and tested in several demonstration sites. The controller has the ambition to decrease the use of fossil fuels and increases the use of excess heat and renewable energy sources in the DHC network. Additionally, each demo site also reached a reduction of 11.000 tons/year in CO2-emissions.
