A standalone microgrid plays an important role in supplying power to residential and remote areas by integrating different types of distributed generation. One of the key open issues in both academic and engineering fields is how to provide an optimal planning strategy for distributed generations and storage systems in a standalone microgrid, considering multi-objective performance indices such as reliability and cost. In this paper, a novel constrained multi-objective population extremal optimization (CMOPEO) is proposed for standalone microgrid optimal planning. The fundamental concept of the suggested approach is to frame the problem as a standard constrained multi-objective problem, where power loss probability, fuel emission, and power cost of the system are considered as the objectives, and the maximum amount of extra power and the availability of renewable resources are the constraints. The superiority of the CMOPEO algorithm is demonstrated through simulation results on a standalone microgrid case over multi-objective particle swarm optimization.