EXUS as Partner
Enabling Positive Energy Districts through Digital Twins
Cities consume 65% of the world’s energy supply and are responsible for 70% of the CO2 emissions, hence sharing a lot of the responsibility for climate change. We are faced with the challenge of redesigning our existing cities to make them more sustainable, resilient, inclusive and safe.
ExPEDite aims at creating and deploying a novel digital twin, allowing for real-time monitoring, visualization and management of district-level energy flows. A suite of replicable modelling tools will enable stakeholders to analyze planning actions towards positive energy in a cost-effective fashion, aiding their evidence based decision-making process. The tools will be able to model the district’s energy production and demand, optimize for flexibility and simulate mobility and transport. By employing gamification and co-creation approaches, the project will enhance public awareness and engagement in energy efficiency. The project will culminate in the publication of practical guidelines, reusable models, algorithms, and training materials to aid other cities to replicate the digital twin for their districts, fostering widespread adoption of sustainable energy practices.
01/2024 – 12/2026
Project duration
6,671,375.00 €
Overall Budget
Topic
Impact
· Increased number of (tangible) city planning actions for positive clean energy districts using the (proto-)PED design, development and management digital twin tools (based on pre-market research learnings) using open-standards based components which can be reused elsewhere.
· Increased integration of existing smaller scale management systems (e.g. Building management systems) with open-standards based operational city platforms using sectorial data (e.g. building data, mobility, urban planning, etc.).
· Enhanced data gathering approaches with identification of relevant multidimensional data sets (e.g. meteorological, load profile, social, geo-spatial, etc.) high-resolution real-time data streams (e.g. renewable energy production, energy consumption), and relevant forecasting data, drawing also on the work of common European data spaces.
· Increased number of city planning departments / approaches using common data and (replicable) elements and processes.
· Consolidated city sensor network specifications, complemented by appropriate data gathering approaches for soft data.
· Improved performance of AI based self-learning systems for optimization of positive clean energy districts and bottom-up complex models.
· Enhanced innovation capacity of local/regional administrations and accelerated uptake of shared, smart and sustainable zero emission solutions.
RIGAS TEHNISKA UNIVERSITATE (RTU - Coordinator) (Latvia)
ETHNICON METSOVION POLYTECHNION (NTUA) (Greece)
UNIVERSITA DEGLI STUDI DI PADOVA (UNIPD) (Italy)
UNIVERSIDADE CATOLICA PORTUGUESA (UCP) (Portugal)
VSB - TECHNICAL UNIVERSITY OF OSTRAVA (VSB-TUO) (Czechia)
LAUREA-AMMATTIKORKEAKOULU OY (LAU) (Finland)
Partners
EXUS (Greece)
ATOS IT SOLUTIONS AND SERVICES IBERIA SL (ATOS) (Spain)
PLEGMA LABS TECHNOLOGIKES LYSEIS ANONYMOS ETAIRIA (PLEGMA) (Greece)
FUNDACION TECNALIA RESEARCH & INNOVATION (TECNALIA) (Spain)
UPCOM CYPRUS LTD (UPCOM) (Cyprus)
DELOITTE CONSULTING SRL SOCIETA BENEFIT (DELOITTE) (Italy)
TECHNOLOGICKA PLATFORMA ENERGETICKABEZPECNOST CR ZS (TPEB) (Czechia)
RIGAS PILSETAS PASVALDIBA (RIGA) (Latvia)
RIGA MUNICIPAL AGENCY "RIGA ENERGY AGENCY" (REA) (Latvia)
THE LISBON COUNCIL FOR ECONOMIC COMPETITIVENESS ASBL (LC) (Belgium)
OPEN & AGILE SMART CITIES (OASC) (Belgium)
SIA DATI GROUP (DATI) (Latvia)