In recent years, renewable energy resources (RERs) are taken into account as the popular generation units due to economic advantages as well as trouncing the environmental emissions. Indeed, increasing the level of RERs in the energy generation cycle has made the prediction of the amount of energy production more difficult and intermittent. Therefore, in spite of the existence of a strong motivation for high usage of RERs in the energy generation process, some basic challenges as well as uncertainty modeling of the system should be considered in optimal operation of the renewable-based multi-carrier energy networks (MCENs). After analyzing the MCENs from different aspects in the previous chapters, this chapter is targeted to provide the mathematical models for MCENs and their uncertainty quantification with the aim of facilitating their implementation in real hybrid energy networks. Given the provided mathematical models, the optimal scheduling of the interconnected microgrids with a full share of RERs is considered as a case study for examining a sample MCENs with real-recorded data. Indeed, each microgrid is only equipped with the RERs with the aim of the complete production of clean energy. In the studied system, the probabilistic modeling of the problem has been performed using the information gap decision theory (IGDT) method, in which both the robustness and opportunistic states of the RERs are respectively modeled as the risk-averse and risk-seeker strategies. In order to reliably meet the energy demand in the presence of 100% RERs, transactive multi-carrier energy technology is exerted for building a local energy trading environment considering both the economic and control mechanisms. The result analysis indicated the effectiveness of the proposed model for the MCENs with 100% RERs.