Distributed power allocation (DPA) in micro-grids (MGs) has a significant potential for attaining a cost effective and reliable solution of power dispatch. Considering the significant risks posed by cyber-attacks and system limitations to the MGs, it is important to develop resilient methods for an efficient DPA, which is valuable both in terms of theoretical understanding and practical application for energy 5.0 framework. This work addresses the DPA problem in MGs, specifically focusing on the economic dispatch (ED) for the generation side while taking into account ramp-rate limits (RRLs) and stochastic false-data injection (FDI) attacks. A consensus-based protocol has been developed by considering the information of the incremental costs of neighbouring generators and local power mismatch for a generation facility. A stochastic FDI attack at the shared information over the network has been accounted. The proposed technique guarantees robust (and resilient) convergence by providing a sufficient criterion under RRLs and stochastic FDI attacks. The proposed approach is based of the distributed ED framework, and convergence analysis has been performed via two Lyapunov functions. The convergence of total power mismatch and error in synchronization of incremental costs to bounded sets are ensured by the proposed approach. The presented framework achieves an efficient energy production cost. The network's robustness and resilience for the shared information of incremental cost of energy production units as the consensus variable are accounted. The simulation study for a set of five generators under stochastic FDI attacks and RRLs are provided which confirm the theoretical findings of the proposed scheme.