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 â€œbreak-down scenariosâ€ that allows the solution of the problem to be able to meet the user demands for every possible contingency in which one of the AESâ€™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.
Keywords multi-energy systems, microgrid, optimization, MILP, stochastic programming, reliability