A standardised GIS-based tool to automate urban scenario making for co-simulation of multi energy systems
External reference persons Pietro Rando Mazzarino (email@example.com)
Thesis type EXPERIMENTAL
Description One of the main objectives of the Energy Center LAB (EC-L) initiative consists on designing a Multi-Energy-System (MES) Co-Simulation platform able to qualitatively and quantitatively solve energetic transition scenarios . Most important aspects of the platform will be its flexibility and the possibility to assess different real or virtual scenarios. The main focus will be on Urban Multi-Energy systems and so the scenarios addressed by the platform must be characterised taking into consideration all the possible components of these macro-system. Thus the main objective of the student will be the creation of a framework for configurable and automatic scenario creation starting either from real-world or simulated dataset. This process will touch different fields of expertise due to the various scenario requirements. The scenarios will take into consideration georeferenced information about Buildings, electrical grid, district heating, distributed generations, storages and electric vehicles, as well as the deterministic or statistical characterisation of all the involved systems. The main objective of this thesis consists on designing and developing a user-friendly tool that extends the already existing EC-L co-simulation platform to easily create new urban scenarios to simulate a multi-energy system in smart grids. This tools have to visualise also the results output of the co-simulation. The scenario will contains lot of information ranging from grid physical parameters to building occupancy schedules. The student will need to understand and choose the best available technologies and standards to generate highly characterised Urban MES scenarios along with the implementation of a graphical GIS-based interface to manage the data flow.
 P. Mancarella. MES (Multi-Energy Systems): An overview of concepts and evaluation models. Energy, 65:1–17, 2014.
Deadline 03/02/2023 PROPONI LA TUA CANDIDATURA