A MULTI-OBJECTIVE OPTIMIZATION TO ASSESS ECONOMIC BENEFIT DISTRIBUTION AND IMPACT OF ENERGY COMMUNITIES

摘要

In this work we perform an analysis of the energy communities as forms of collective self-consumption. We have created a program which is combined with a genetic algorithm to perform a multi-objective optimization (MOO) of an EC. The decision variables of the optimization are the PV and the battery investments of each EC member and the adopted business model. The optimization aims at (i) maximizing the cost savings thanks to the EC, (ii) minimizing the percentage of fossil fuel production and (iii) minimizing the value of a Faimess Index which measures the fairness of the benefit distribution. The novelty of this work consists in focusing at the same time on the global benefit for the entire energy community and the profit of each participant of the EC, which do not always progress at the same time. EC benefits are not only economic, therefore this work also focuses on encouraging renewable energy consumption, by minimizing fossil fuel production purchased from the grid. A scenario which is convenient from an economic and environmental perspective is not always applicable if it doesn't guarantee savings for all the EC members; almost 74% of RES consumption can be achieved while ensuring global satisfaction.