EVELIXIA Autonomous District Decision Support Toolbox

From UBITECH ENERGY team, we are pleased to share the latest developments on Task 4.4, regarding the EVELIXIA Autonomous District Decision Support Toolbox, part of Work Package 4 dedicated to Intelligent B2G (Building-to-Grid) and G2B (Grid-to-Building) Services. Led by UBITECH ENERGY, significant progress has been made, marking a critical milestone as we approach the halfway point of this task, with its completion scheduled for June 2026.

The objective of Task 4.4 is to develop a robust decision support system that seamlessly integrates the EVELIXIA District Digital Twin from Task 4.3, enhancing its capabilities through advanced optimization frameworks. This toolbox aims to empower grid stakeholders, including DSOs, energy aggregators, and retailers, by providing strategic insights and actionable recommendations for district-level investment decisions.

In recent months, collaboration has intensified through regular weekly meetings with our partners from CERTH, focusing specifically on enhancing functionalities within the integrated innovative solutions and EVELIXIA services. Several testing scenarios have been prepared and evaluated, facilitating the validation and refinement of the methodologies and tools involved. Moreover, successful offline data exchanges between the different integrated services have streamlined the workflow. The first version of the public deliverable D4.3, which encapsulates initial findings and methodologies, has been successfully submitted at the end of March 2025.

The Grid Investment Planning Assistant tool has demonstrated promising results in initial test-runs using a modified IEEE 33-bus test system reduced to a simplified 5-bus network. This assessment involved detailed load flow analyses, scenario comparisons, and robust financial evaluations employing Net Present Value (NPV) and Benefit-Cost Ratio (BCR) methodologies. The parametric analysis exploring variables such as discount rate and demand growth has provided valuable insights into investment viability.

The Multi-vector Network Manager tool has successfully tested its optimization capabilities for harnessing flexibility potential from distributed energy resources (DERs) and building operations. The framework, designed to minimize operational costs and curtailment of renewable energy sources (RES), effectively utilized linear programming to manage grid congestion. Pre- and post-optimization analyses validated the effectiveness of flexibility provision, demonstrating substantial benefits in grid congestion management.

Multi-vector Network Manager: Pre and Post-Optimization power flow results for the network under study.

Significant strides have been made with the Aggregated Demand Portfolio Manager tool. Utilizing advanced Reinforcement Learning techniques, this service efficiently aggregates and optimizes demand-side flexibility. By processing demand forecasts, flexibility bounds, DSO requests, and price signals, IS13 has generated practical recommendations ensuring both thermal comfort and cost efficiency, effectively identifying and managing periods without DSO requests.

Aggregated Demand Portfolio Manager: Results

Looking forward, immediate next steps include establishing structured data exchanges with the EVELIXIA Services Broker, and continuous refinement of the toolbox’s functionalities in line with EVELIXIA use cases and stakeholder feedback from DSOs and TSOs. We remain committed to keeping all stakeholders informed and involved as we advance in achieving our ambitious objectives.