WP2 – System Requirements and Architecture
WP2 defined the ExPEDite platform’s system requirements and technical architecture, ensuring alignment with Riga’s strategic goals while enabling scalability and replicability. Activities included co-design of requirements and KPIs (T2.1) adoption of Minimum Interoperability Mechanisms (T2.2) and development of a layered system architecture with clear integration and security mechanisms (T2.3). Riga’s planning pathways to inform climate-neutral strategies were reviewed (T2.4) and reusable guidelines for sensor network consolidation were reviewed (T2.5). WP2 delivered a robust blueprint of the system requirements and architecture guiding subsequent implementation.
WP3 – Data and Knowledge Management Framework
WP3 created the data backbone for simulation (WP4) and Digital Twin (WP5). Core Data Services (T3.1) were implemented with IoT telemetry via ThingsBoard, Kafka-based messaging, multiple storage solutions and Keycloak-based access management. The Pattern Repository (T3.2) provides reusable digital models; the Data Spaces Integration Suite (T3.3) defined its architecture and NGSI-LD-based energy data model. BMS Integration (T3.4) enabled collection of building and energy data, while the District Data Fusion Engine (T3.5) delivered aggregation and anomaly detection via rule-based logic and ML prototypes. Together, these form a secure, interoperable data framework.
WP4 – Modelling and Simulation Suite
WP4 delivered interoperable tools for Positive Energy District planning and operation. T4.1 produced a TRL6 energy forecasting and flexibility tool using AI-based demand and RES prediction with optimisation for demand response. T4.2 created a GIS-integrated building stock modelling methodology, validated in Riga. T4.3 developed a SUMO-based mobility testbed. T4.4 prepared geospatial and system simulation methodology for PV, batteries, heat pumps and hydrogen. T4.5 completed a system-dynamics district heating and storage model, deployed online for interactive scenario testing. T4.6 produced cost–benefit guidelines, business model concepts and risk analysis. WP4 advanced core modelling tools and provided a comprehensive simulation suite.
WP5 – District Digital Twin
WP5 developed a 3D Digital Twin environment in Unreal Engine with a Design View for planning and Runtime View for live data. A citizen engagement mobile app prototype was released, using gamification and community inputs. The District Optimisation and Decision Support tool was built with short-term (RDME) and long-term (MCDA) planning capabilities. Preparations for AI-driven analytics and visualisation components were completed, setting the basis for advanced real-time data processing in future phases.
WP6 – PED Twin Deployment and Evaluation
WP6 prepared for deployment and evaluation of the PED Twin. Task 6.1 initiated scenario planning and training. Under T6.2 an integration server and Kafka broker were configured, and an integration matrix prepared. T6.3 progressed with Living Lab preparations, including an on-site meeting in Ostrava. Demonstration (T6.4) and evaluation (T6.5) will follow in later stages.
