This paper recommends a framework to optimally size a hybrid energy system based on photovoltaic (PV) panels, wind turbines (WTs) and fuel cell (FC). For this aim, all the components are modeled and an objective function is defined based on the total annual cost. In the optimization problem, the maximum allowable loss of power supply probability (LPSPmax) is also considered to have a reliable system. In order to minimize the objective function, an efficient artificial bee swarm optimization (ABSO) algorithm is proposed. ABSO is a recently invented metaheuristic algorithm which is inspired by the intelligent behaviors of honey bees such as collection and processing of nectar. Instead of gradient information, ABSO uses stochastic rules to escape local optima and find the global solution. The proposed methodology is applied to a real case study and the results are discussed. It is seen that at LPSPmax set to 0%, 0.3% and 1% the PV/WT/FC is the most cost-effective energy system and at LPSPmax = 2% the WT/FC is the most cost-effective hybrid system. (C) 2014 Elsevier Ltd. All rights reserved.