System-level models for Smart Grid simulations and their integration into a campus Micro Grid model

The shift toward renewable energy sources implies the widespread diffusion of erratic and non dispatchable distributed generation. This requires the installation of energy storage systems that can store the energy in excess and give it back when there is a deficit of production. Proper sizing of the components of a Smart Grid (SG), as well as studying the introduction of new components is not a trivial task. Offline simulation models and Digital Twins open the way for new smart tools for SG planning, development, and live automated control. In this perspective, it is necessary to implement system level models with tight execution time constraints to be able to run in real time or even faster. In this thesis, a system level approach for a campus level Micro Grid (MG) is presented. The model allows simulations on widely varying time scales and evaluation of the electrical, economic, and environmental performance of the MG. A library of MG components is presented, namely photovoltaic (PV) generation with MPPT control, battery energy storage system (BESS), loads, and electric vehicle charging stations. The model of a heat pump-based building heating/cooling system is included coupling the dynamic thermal model with the electric grid model. The campus MG model is used to perform simulations under different scenarios for the estimation of the overall economic and environmental impacts, and to study the evolution of the system in islanded-mode operation. Nano Grid (NG) modeling activities based on the same library of components are also included in the dissertation. In particular, the model of a NG is developed to study the effectiveness of a smart soiling sensor prototype for PV plants. In addition, the presented simulation approach is used to properly size the power system to supply a fleet of electric vehicles by means of PV generation supported by a BESS.