The idea behind this thesis stems from the need to optimize the sizing of collective self-consumption systems and renewable energy communities. By considering the increasing importance of end consumers and their contribution to climate neutrality goals, these initiatives are emerging as promising solutions. However, due to their complexity and the presence of multiple conflicting objectives, it is necessary to develop suitable optimization approaches. In this context, the thesis proposes a Multi-Objective Optimization Problem based on Game Theory. Traditional Multi-Objective methods are inadequate for effectively managing the numerous objective functions involved (going from multi to many objectives), whereas the proposed method demonstrates greater capability in handling a higher number of objectives.