Multi-Agent Test Environment for Next Generation Buildings

Gebäudetechnik

The mate4buildings project creates a real environment for multi-agent systems in building technology to optimise energy management through decentralised, scalable and resource-efficient solutions. Intelligent agents for buildings are created using hybrid methods from machine learning and linear/non-linear optimisation.

Acronym

mate4buildings

Project running time

01/09/2024 - 31/08/2027

Projectbudget in EUR

899.465

The mate4buildings project is developing technologies for the efficient integration of renewable energies in the building sector. Intelligent energy management solutions that utilise flexibility on the consumer side and network energy sectors play a central role here. Traditional, centrally organised optimisation strategies are reaching their limits as networking increases, which is why innovative approaches are needed. Multi-agent-based optimisation processes offer a decentralised alternative. They are based on the interaction of autonomous units (agents) and facilitate the integration of existing and new systems.

In building technology, multi-agent systems are still in the development phase, as the infrastructure for trialling them is lacking. In particular, there is a lack of real-life laboratories that enable all relevant technologies to work together under real conditions. The project will create such an infrastructure for building and neighbourhood applications. To this end, hardware and software for various types of agents - such as room, façade, ventilation or heat pump agents, etc. - are being developed and integrated into different building types. - and integrated into different types of buildings. Hybrid methods from machine learning and linear and non-linear optimisation processes guarantee scalable and resource-efficient solutions.

The real-world laboratory strengthens existing R&D expertise in building technology, promotes national and international cooperation, supports the regional economy, research-led teaching and the implementation of Burgenland's RTI strategy.

Highlights:

Multi-agent systems as decentralised optimisation approaches for energy management
Real-world laboratory for the further development and market readiness of multi-agent systems in building technology
Use of hybrid methods (machine learning, optimisation processes) for efficiency and scalability
Strategic importance for Burgenland: strengthening research, business and education