In this second part, we evaluate the performances of our control framework by applying it to a casestudy that contains a minimum set of elements allowing to show its applicability and potentials. Weshow how the computation of the PQt profiles, belief functions, and virtual costs can be synthesized forgeneric resources (i.e., dispatchable and stochastic generation systems, storage units, loads). The metricsof interest are: quality-of-service of the network represented by voltages magnitudes and lines currentmagnitudes in comparison with their operational boundaries; state-of-charge of electric and thermalstorage devices; proportion of curtailed renewables; and propensity of microgrid collapse in the case ofrenewables overproduction. We compare our method to two classic ones relying on droop control: thefirst one with only primary control on both frequency and voltage and the second one with an additionalsecondary frequency control operated by the slack device. We find that our method is able to indirectlycontrol the reserve of the storage systems connected to the microgrid, thus maximizing the autonomy inthe islanded operation and, at the same time, reducing renewables curtailment. Moreover, the proposedcontrol framework keeps the system in feasible operation conditions, better explores the various degreesof freedom of the whole system and connected devices, and prevents its collapse in case of extremeoperation of stochastic resources. All of these properties are obtained with a simple and generic controlframework that supports aggregation and composability.