The #EEG++ project addresses a key challenge in the energy transition within the building sector: how locally generated renewable energy in residential districts can not only be produced but also efficiently consumed on-site. This challenge is driven by the increasing electrification of buildings through technologies such as heat pumps and electric mobility, as well as the need to combine the expansion of renewable energy with improved energy efficiency. While renewable  energy communities provide a regulatory framework for local energy use, a significant gap remains between annual energy balance calculations and actual real-time consumption. The central research question of the project is therefore how a residential district can be operated technically, economically, and organizationally in a way that maximizes the use of locally generated energy.

The project builds on findings from the predecessor project #EEG+, which showed that despite high photovoltaic (PV) generation, a large share of energy is fed into the public grid instead of being used locally. In response, a real-world demonstration site was established in Hart bei Graz, featuring a comprehensive energy system including PV installations, a central heat pump, a battery storage system, intelligent hot water storage units, and a renewable energy community. The objective was to transform this system into a self-consumption-optimized district through the use of IoT technologies and data-driven control, thereby creating a scalable model for plus-energy communities.

Methodologically, the project followed an integrated approach combining digital planning, technical development, real-world implementation, and user integration. The district energy system was first modeled and simulated using a dedicated planning tool. In parallel, IoT components were developed to enable real-time data acquisition and control of energy flows. These solutions were then implemented and tested in the demonstration site under real operating conditions. Additionally, a structured stakeholder and user engagement process was carried out to ensure acceptance and to incorporate user feedback into system design and operation.

The results demonstrate that combining PV generation with battery storage, thermal storage, and intelligent control can significantly increase local energy use. At the same time, the project revealed that substantial optimization potential still exists, particularly through the integration of additional flexible loads. A key finding is that self-consumption optimization is the primary lever for improving both the economic viability and efficiency of energy communities. Furthermore, it became clear that technical solutions alone are insufficient: transparency, clear communication, and active user involvement are essential for successful operation.

Looking ahead, further research is needed in areas such as advanced optimization algorithms, integration of additional flexibility options, and standardization of system interfaces. The developed solutions also show strong potential for replication and scaling to other districts. Overall, the #EEG++ project provides an important contribution to the development of integrated, digitally supported energy systems and demonstrates practical pathways for implementing plus-energy communities in real-world settings.

Project management

Dr. Stefano Coss - Arteria Technologies GmbH

Project or cooperation partners

• Ed-energiedigital GmbH
• Pink GmbH
• CEAS GmbH
• realityLabs GmbH
• Waldheimat Consulting und Projektentwicklung GmbH

Dr. Stefano Coss
Schubertstrasse 6a
A-8010 Graz
Tel.: +43 (699) 1050 9386
E-mail: Stefano.coss@arteria.at
Web: www.arteria-tech.com