This work presents a two-stage stochastic Mixed Integer Linear Programming model for the optimization of the design of an aggregated energy system (AES) (i.e., multi-energy systems, microgrids, energy districts, etc.) serving a university campus featuring electricity and heating demands. The off-grid system design is obtained by considering a set of representative periods for both demands by means of a carefully modified k-medoids algorithm. N-1 reliability is also considered in the model, by introducing the concept of "break-down scenarios" that allows the solution of the problem to be able to meet the user demands for every possible contingency in which one of the AES's units fails. The effect of including N-1 reliability in the model is then showed by comparing the optimal design obtained by considering such approach against one with no break-down scenarios.
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