Developing a new urban planning tool based on a data space to deploy electric vehicle (EV) charging network cost-effectively

The project seeks to tackle demand-side flexibility (DSF) challenges to improve electricity supply efficiency, resilience, quality, and reduce environmental impact. DSF involves adjusting demand, including electrified transport and heating, to enhance the integration of variable renewable energy (VRE) and support carbon neutrality by 2050. A key use case is developing a tool to plan cost-effective public EV charging networks. The project will create a secure, shared data lake, collecting data from diverse public and private stakeholders, which is currently lacking in the market. The solutions will integrate project management across stakeholders like utilities, car manufacturers, and city councils, focusing on shared KPIs—minimizing investment in the electricity grid while maximizing EV adoption to reduce GHG emissions. The approach will leverage big data, machine learning, deep learning, and generative AI to optimize decision-making and system performance. This is particularly challenging in southern European cities where the lack of space and old infrastructure hinder fast development of the charging grid.