Islanded microgrids (IMGs) are embedded power networks with distributed energy resources (DERs) providing a reliable and flexible energy option for off‐grid customers. This work addresses the planning model of renewable‐based IMGs feeding multi‐energy demands considering investment and emission related objectives. The proposed solution is to determine the optimal mix and sizing of various energy sources in IMG, including renewables; for multiple energy demands. This study also presents a hybrid‐scenario and Monte Carlo approach to gauge the uncertainty involved in multi‐energy demands, i.e. electrical, heating, and cooling loads; together with correlation among wind and solar generations. The spatial interdependence among renewable generations is implemented using copula; that generates a synthetic set of stochastic correlated data. The combined load scenarios for multi‐energy demands and renewable samples are implemented with the proposed hybrid approach in the formulated stochastic planning model. In this work, the formulated problem is proposed to solve using meta‐heuristic multi‐objective ant lion optimiser algorithm, that is validated on the test system. The superiority of the proposed approach is highlighted in comparison with other multi‐objective optimisers. The multi‐energy dispatch between associated sources and loads were simulated to show how the obtained capacity can suffice the seasonal multi‐energy demands of a typical day considered.