To promote the urban energy transition while dealing with increasing population growth and living standards, an impressive effort has been devoted by governments and international organizations to setting-up programmes for the sustainable development of cities and communities. This has led to the concepts of low carbon communities to be achieved through energy efficiency and renewable-based options, properly implemented within the urban space for the efficient energy cooperation of its objects. 

To this aim, proper modelling tools allow identifying refurbishment priorities and developing novel energy management schemes (EMS), business models and concepts for self-sufficient urban districts or communities, by exploiting the potentials of local renewable energy sources (RES) and energy storage systems (ESS).

New challenges are imposed to cities, including the increasing demand of climate-resilient planning and robustness towards unexpected scenarios (among which pandemic and international crises of last two years are examples).

Among the available techniques, there is no unique methodology to perform urban energy modelling of energy districts. Indeed, the modelling and simulation of districts has yet to be fully understood and it requires additional research effort despite the growth in physics-based modelling tools (e.g. CityBES, UMI, UrbanOPT, CityGML) noticed in the last years. Although these software are key tools for assessing city and district energy policies, they are focused on specific typology of buildings and sub-systems of an energy district, being often used in co-simulation to broaden the domains of investigation. 

To explore the interaction among multiple buildings and the other energy objects, physically or virtually connected in an urban area, it is advisable to consider the building-level modelling resolution because of the different buildings’ demands varying across time and space, by also considering other energy domains to account for the interaction among all district users (e.g. buildings, electric vehicles) and their coordination with energy networks, generation systems and storages.

The design and the proof-of-concept of novel urban energy management schemes and energy-related business models (e.g.peer-to-peer, collaborative energy sharing, demand-side energy management) and, more in general, of new paradigms in which urban energy objects act as collaborative users associated to human activities aiming at a common target (e.g. minimise emissions or energy costs) requires the use of multi-level and multi-domain simulation tools to be developed for simulation and optimization purposes. 

The ultimate goal is to provide design and operation guidelines, necessary for the technological and regulatory development of sustainable urban areas and for providing co-benefits to citizens and local authorities.