Optimal energy management and performance evaluation of an Integrated Mobility System: the "Life for Silver Coast" case study

Nowdays, Climate Change and Global Warming are very relevant issues and Humankind relies on Renewable Energy Sources (RESs) for mitigating environmental impacts. RESs exploitation implies the adoption of a Distributed Energy Generation (DEG), implemented through local electrical grids called Microgrids (MGs). The intent of harvesting as much as energy possible, dealing with the RESs unpredictable nature, makes researchers develop suitable ICT systems (Energy Management Systems or EMSs). Smart Grids (SGs) are systems composed of many MGs, thanks to which a whole urban area can perform an efficient energy management. Energy Communities, made up of companies, research centres and Universities strive to design and realize SGs, in a sustainable development vision. In this context, the sustainable mobility system realized in the "LIFE for Silver Coast" European Project is a very good test bench for EMSs synthesis. In fact, Electric Vehicles (EVs) and charging stations will be integrated in the Project Area and managed through proprietary EMSs. In addition, the achieved knowhow can be used by the Energy Community to develop Smart Grids, not only in the same area. In this thesis, the Evolutionary Fuzzy System (EFS) paradigm is applied for the synthesis of an EMS. In particular, a double-step optimization Hierarchical Genetic Algorithm (HGA) procedure is implemented for reducing the computational cost. The resulting Fuzzy Inference System- Genetic Algorithm (FIS-GA) is tested for the onboard optimal energy management of the LIFE "Valentino" Class e-boat, with the purpose of implementing the same EMS in a residential MG. In addition, an application based on Life Quality indicators related to mobility systems is presented.