The ENERGATE Project team successfully presented two scientific papers at the 6th International Conference in Electronic Engineering & Information Technology (EEITE 2025), held on 4–6 June 2025 in Chania, Crete.

Assessing Investment Risks in Energy Efficiency Projects Using AHP for Group Decision Making

Authors: I. Andreoulaki, A. Papapostolou, V. Marinakis
📄 Read on IEEE Xplore

This study addresses the challenges of financing energy efficiency projects in buildings, where the high upfront costs often discourage investors despite long-term benefits.
The paper identifies 14 critical risks associated with energy efficiency investments and evaluates them through the Analytical Hierarchy Process (AHP) for group decision-making. Results highlight that:

• Risks related to end client credit quality and energy price volatility are the most significant.
• Stakeholders across the energy efficiency value chain perceive risks differently, reflecting diverse priorities in investment decisions.

This research provides valuable insights into how risks should be prioritized to encourage sustainable investments in building energy upgrades.

ML-Based Decision Support System for Energy Efficiency Retrofits

Authors: D. Stoian, K. Kefalas, I. Andreoulaki, K. Papapostolou, V. Marinakis
📄 Read on IEEE Xplore

This paper focuses on the role of machine learning in guiding energy renovation strategies. The study proposes a decision support system that helps stakeholders identify the most effective retrofit measures based on past project data.
Key findings include:

• Random Forest and LightGBM algorithms achieved the highest predictive accuracy for identifying optimal retrofit actions.
• The system estimates not only energy savings but also CO2 reduction impacts.
• The work demonstrates the potential of AI-driven tools in scaling up energy management solutions and supporting informed decision-making in the building sector.