Optimization for the design of renewable energy communities

The evolution of the challenges linked to climate change and the growing energy demand have driven the adoption of innovative approaches in the energy sector. Renewable energy communities (RECs) emerge as a permanent solution, allowing the production, distribution, and consumption of electricity from renewable sources at a local level, downsizing the electricity distribution network and reevaluating the concept of locality, community and energy efficiency. This master's thesis focuses on the design and optimization of such communities by means of a software written in Python that exploits algorithms and automation approaches in order to reduce working time and simplify the overall process.Throughout this work, the following key areas were explored: ●??Design of the energy production plant from renewable sources, specifically photovoltaic technology. It includes optimizing the arrangement of the modules, simulating the annual producibility with an hourly timestep and reporting graphs and technical diagrams; ●??Sizing of the electrical loads of the users, guaranteeing a specific degree of detail based on the power inventory of the electrical loads, simulating the demand for electricity on an hourly basis; ●??Study of the combinations of users within the renewable energy community, analyzing the energy response by means of graphic tables dedicated to the individual energy vectors, to obtain the combination of users capable of optimizing the amount of shared energy and the consequent economic return. The developed tool was tested in a real case study, thus being able to evaluate the actual functionality and the impact that the use of such software has on saving hours worked and on ease of work. The results of this thesis demonstrate that the application of a tool created using Python for the design of renewable energy communities can lead to efficient and economically advantageous solutions, without affecting the professionalism and degree of detail of the labour output. This thesis contributes to the evolution of methodologies for designing renewable energy communities and offers a framework for further research and practical applications in the field of energy engineering.