Analysing Green Urban Clusters through a Multi-Node Dynamic Model and a Detailed User-Driven Approach

In the context of the energy transition, the efficient management of energy flows in buildings and urban clusters is a crucial challenge for reducing carbon emissions and enhancing resource sustainability. Advanced energy management models provide essential tools for optimizing the integration of renewable energy sources and storage systems, contributing to more effective planning and dynamic energy consumption management. The objective of this study is to develop a multi-node model aimed at managing energy flows in buildings and clusters, offering a dynamic tool capable of representing each individual user in detail, rather than limiting itself to a macro-level, single-node, systemic approach. The novelty of the research lies in such a disaggregated approach that will provide useful insights to understand the optimal investment and operation of each consumer within the system rather than obtaining aggregated results for the whole system. The model enables an hourly time resolution for a techno-economic optimization and it is structured in two modules: (I) a Simulation Module to assess energy consumption using reduced-order building models able to obtain the electricity and thermal demand based on detailed consumer behaviour; and (II) a multi-node optimisation model based on linear programming that considers renewable energy generation and storage for electricity, heating and hydrogen aiming at identifying the best investments and the most efficient operational strategies. The proposed approach effectively integrates hourly load simulation with technical solution analysis, providing an advanced and flexible decision-making tool for the planning and implementation of distributed energy systems without losing the details of each consumer of the system. The model will be applied to a relevant case study in Italy so as to test and validate its functionalities while analysing the added value that such a disaggregated approach can provide. The results of such a model will be useful in supporting the planning of more sustainable distributed energy systems and enhancing the efficient use of renewable resources at building and district level.