Decision-making processes involving a large number of criteria are often complex problems. In general, such problems seek to meet conflicting interests, so single solutions tend not to address the preferences of all agents involved in the process. This is the case of the problem of selection models for generation of stochastic scenarios of Natural Inflow Energy (NIE), which are input to the calculation of the medium term hydrothermal dispatch in the planning of the operation of the Brazilian Electric System (BES). This paper proposes an extension of a well-established multicriteria decision support method, so that it becomes able to reveal the preference of expert committees, and from these revealed preferences to derive more adequate solutions for each committee. The application of this methodology proposed in the context of BES is done to help different segments of the industry (academia, industry and regulator) to identify which model of scenario generation best suits the preferences of these segments. To this end, the specialists of these three sectors were grouped and from the revelation of the preferences of each committee a new ordering of the scenario generating models was proposed. The preferences revealed for the academy and industry committees corroborated the conjectures about the predilections of these sectors, fidelity in the representation of the moments for the academy and capacity of replication of the variance for the industry, however the hypothesis for predilection for the replication of deficit was not able to be verified to the regulatory committee. Among the new solutions obtained, the best classified model for the academy and industry was the PAR (p) Multiplicative and for the regulatory committee the PAR (p) Boot-MC.