The unpredictable nature of renewable energy resources (RERs) makes obtaining optimum operation and grid integration in today’s smart power distribution networks challenging. Thus, to mitigate the fluctuations in RERs, the penetration of diesel generators, batteries, and electric vehicles (EV) must be considered for an effective energy management study (EMS) in the IEEE-33 bus system. This paper addresses the energy management of a microgrid linked to the main power system under deterministic and probabilistic circumstances. Apart from economic considerations, modern distribution networks must maintain an acceptable range of system reliability indexes. Failure of reliability in the distribution network may result in irreversible harm to the distribution network. For multi-objective functions such as cost reduction, voltage profile improvement, and voltage stability improvement are the main objectives of this article. An efficient method known as a novel slime mould algorithm (SMA) is used to solve these issues and validate the performance with the existing evolutionary algorithms. However, the SMA can optimally address the grid-connected various types of RERs installed, which can significantly compensate network losses, voltage deviations and improve the system performance. Finally, the algorithm’s effectiveness on the EMS approach is verified under different algorithms through 2021a MATLAB/Simulink and the proposed methods prove the best results with the convergence of other algorithms also.