The RESONANCE framework

Developing solutions in a plug-and-play manner

The RESONANCE Framework constitutes 3 catalogues of software libraries as well as marketplace services and tools that provide means for rapid, cost-efficient development & customization of standard-compliant Resource Manager and Customer Energy Manager solutions as well as their aggregation services into different sectors.

The Resource Manager (RM) is a software component that represents either a logical group of smart appliances e.g. Heat, Ventilation & Air Conditioning system or a single smart device.

Customer Energy Manager (CEM) is an intelligent software agent that manages smart appliances and other flexible assets in buildings to maximize consumer benefits.

Aggregation and Market Integration Catalogue provides services that can be deployed on top of existing aggregation platforms to provide mechanisms for aggregation of flexible assets from the Customer Manager.

The Data and Service Marketplaces make the data and services easily available for development, testing and tailoring of solutions through APIs, configuration and deployment tools.

pilot sites in 6 European countries

Demonstrating the RESONANCE services

Each pilot site is acting as a primary development & testing venue for one to several types of services. The results are populated to the Framework and used to replicate the services in other pilot settings with different stakeholders and constraints.

  • France

  • Germany

  • Slovenia

  • Greece

  • Sweden

  • Finland

Next-generation cross-sector Demand-Side Flexibility Management

The RESONANCE project aims at making it as easy as possible to tailor Customer Energy Manager (CEM) solutions for consumer and prosumer customers in different sectors.

The CEM represents a fundamental change to the role of consumers and prosumers from passive recipients to active participants in the cross-sector energy ecosystem. In this regard, the CEM concept has the potential to revolutionise demand-side flexibility management and enable new consumer-oriented services.

CEMs are envisioned to 1) provide a more deterministic demand response which is needed for predictability and 2) optimise consumer benefits with respect to multiple incentives and goals. To achieve this, there is a need for accurate models of the smart appliances and model predictive control techniques to automate the decision-making within the customer premises.


  • Innovative hybrid approach for modelling of flexible assets & baseline loads with minimal human effort

  • Easy-to-use solutions for integrating the hybrid models with optimal control algorithms that can be tailored for the given smart appliances, customer preferences and market setting

  • Consumer-centric Artificial Intelligence for automated demand response in a plug-and-play manner

  • Improved interoperability, trust, security and privacy

  • A modular system architecture based on the narrow-waist model for interoperability