Evaluation and optimisation of an energy community: an open-source tool

This master's thesis deals with the concepts of Collective Self-Consumption and Energy Communities, which represent a way for final customers to share energy that is locally generated by renewable and high efficiency sources. Despite the long history of `energy sharing' projects in Europe, the introduction of collective self-consumers and Energy Communities in the European and National regulations is quite a revolutionary event that may, to a certain extent, disrupt the traditional way of producing and consuming energy. The idea behind this work is to support the users, which are the main focus of this new and evolving context, with a free and open-source tool to provide quick and easy-to-grasp evaluations of the performances of a configuration where energy is shared among an aggregate of households through collective self-consumption. The tool optimises the operation of a photovoltaic system combined with a storage system (battery) for a number of typical days that are representative for each month of the year. Assessments about the monthly and/or yearly performances are provided, both for fixed-size or variable-size (parametric) analysis of the photovoltaic and of the battery. The evaluations are performed in terms of self-sufficiency and self-consumption rates, which are useful indicators of the energy that is shared over, respectively, the total consumption and the total production of energy. Among the peculiarities of the tool is the generation of the consumption profiles for the aggregate of household customers, using probabilistic methods. In the light of these considerations, starting from a brief overview on the `energy sharing' projects in Europe, the recently-introduced framework for Energy Communities is presented, both at a European and Italian level. Afterwards, the routine followed in the tool is widely described, with the aim of providing a documentation for the code too. Hence, both the physical equations used and the algorithms implemented are presented. The latter are written in the programming language Python, which is also free and open-source. The tool is then used to simulate one potential configuration, in order to show and discuss the results that it provides. Lastly, the development platform GitHub is briefly introduced, which hosts a repository where the tool is easily and freely available to potential users and contributors.