Trust-EC

Bundesministerium für Innovation, Mobilität und Infrastruktur

und dem Klima und Energiefonds

vertreten durch die Österreichische Forschungsförderungsgesellschaft mbH (FFG)

Universtät für Bodenkultur Institut für Sicherheits- und Risikowirtschaften

FH OÖ Forschungs- und Enwicklungs GmbH

Sonnenplatz Großschönau GmbH

Software Competence Center Hagenberg GmbH

Initial Situation and Problem Statement

The increasing deployment of renewable energy sources and the emergence of energy communities are driving a growing decentralization of the energy system. At the same time, AI-based optimization and control methods are becoming increasingly important for efficiently coordinating energy flows and ensuring grid stability.

However, a key challenge currently exists: there is a lack of standardized and practical frameworks for the deployment of responsible Artificial Intelligence (AI) within energy communities. In particular, the following aspects remain insufficiently addressed:

• Lack of standards for ethical and regulatory requirements (e.g., EU AI Act, GDPR)
• Unclear evaluation criteria for trustworthiness, transparency, and fairness of AI systems
• Limited knowledge regarding the scalability of decentralized AI approaches in the energy sector
• Insufficient analysis of societal, environmental, and technical interactions
• Lack of methodological integration of AI into real-world energy community structures

These gaps hinder both the development and the acceptance of AI-based solutions within the energy sector.

Objectives and Methods

The objective of TRUST-EC is to develop a comprehensive conceptual and technical framework for the responsible deployment of AI in energy communities.

The main project objectives are:

• Definition of technical, ethical, and regulatory requirements for AI in energy communities
• Development of a structural and assessment framework for responsible AI (including TRUSTED-AI compatibility)
• Analysis of the scalability and technical feasibility of decentralized AI approaches
• Investigation of societal, environmental, and systemic impacts
• Derivation of a roadmap for future research and implementation projects

Methodologically, the project follows an interdisciplinary approach based on:

• Stakeholder workshops for requirements analysis
• Risk and system analyses to identify critical factors
• Development of use cases and KPI-based evaluation models
• Simulation of decentralized AI approaches (e.g., Federated Learning)
• Impact and interaction analyses at system, societal, and environmental levels
• Iterative validation with experts and industry partners

Expected Results

The TRUST-EC project will deliver the following key outcomes:

• A structured requirements catalogue for responsible AI in energy communities
• A conceptual framework for the development and assessment of AI systems in the energy sector
• Methods for analyzing scalability, robustness, and technical feasibility
• A comprehensive impact and interaction assessment covering technology, environment, and society
• Identification of trade-offs and mitigation strategies for AI-based energy systems
• A strategic roadmap for future research and implementation projects

By achieving these outcomes, TRUST-EC will provide an essential foundation for the secure, transparent, and socially accepted deployment of AI in future energy communities.