SciTransfer
RESONANCE · Project

Software for Automating Energy Savings and Grid Flexibility in Smart Buildings

energyPilotedTRL 7

Imagine your home appliances could talk to the power grid to find the cheapest time to run. This system acts like a smart conductor, coordinating electric cars and heaters to save money without you lifting a finger. It uses a mix of physics and AI to predict exactly how much energy your devices need, making the whole process automatic.

By the numbers
20
partners
6
member states for piloting
70%
industry ratio in consortium
The business problem

What needed solving

Developing software to manage energy flexibility is currently too expensive and slow. Companies struggle to make smart appliances communicate with energy markets in a way that is predictable and standard-compliant.

The solution

What was built

A software suite consisting of three service catalogues (Resource Manager, Customer Energy Manager, and Aggregation/Market Integration) and two marketplaces for data and services.

Audience

Who needs this

Smart home device manufacturersEnergy aggregatorsEV charging network operatorsDistrict heating providersGrid operators
Business applications

Who can put this to work

Energy Utilities
enterprise
Target: Grid Operators

If you are a Grid Operator dealing with unstable power loads — this project developed a standard-compliant software system that allows for deterministic demand response. This ensures a more predictable grid by coordinating flexible assets across 6 member states.

Consumer Electronics
mid-size
Target: Smart Appliance Manufacturers

If you are a manufacturer dealing with high development costs for smart features — this project developed a modular architecture and modeling pipeline. This reduces the effort needed to make devices like HVAC systems and white goods compatible with energy markets.

Automotive
any
Target: EV Charging Infrastructure Providers

If you are a charging provider dealing with peak load spikes — this project developed Resource Managers for electric vehicles. This allows chargers to interact with market incentives to optimize charging times and maximize customer benefits.

Frequently asked

Quick answers

How does this reduce development costs?

The project uses a modular system architecture and an automated machine learning pipeline combined with physics-based modeling. This significantly lowers the effort and cost required to create compliant energy management software.

Can this be scaled across different regions?

Yes, the solution is being validated through large scale piloting in 6 member states. This demonstrates its ability to work across various market settings and consumer sectors.

What is the IP or licensing model?

Based on available project data, the project focuses on standard-compliant solutions (EN 50491-12), but specific licensing terms are not provided.

Does it comply with industry regulations?

Yes, the software is specifically designed to be compliant with the EN 50491-12 standard family for next-generation demand-side flexibility management.

How is the software integrated into existing systems?

Integration is handled via a plug-and-play deployment model using three software catalogues (RM, CEM, and AMIC) and two marketplaces for data and services.

Consortium

Who built it

The project is heavily industry-driven, with a 70% industry ratio comprising 14 companies, including 8 SMEs. This strong commercial presence, combined with 20 partners across 7 countries, suggests the results are designed for immediate market application rather than pure academic research.

How to reach the team

Contact TEKNOLOGIAN TUTKIMUSKESKUS VTT OY in Finland

Next steps

Talk to the team behind this work.

Contact us to connect with the RESONANCE consortium for licensing the CEM software catalogues.