The design of autonomous systems for the rural electrification is a complex task due to the diversity of variables involved in such processes. The absence of programs and methods that carry out this task in a clear and precise manner constitutes a barrier to the dissemination of these systems, although some tools have been developed that present other possible limitations. The exclusion of the environmental dimension in the design and evaluation process of hybrid systems means that the true benefits are not evaluated in terms of quality and quantity. In an attempt to overcome such deficiencies, this work presents a new method of design; approached from the multi-objective optimization of systems. The multi-objective optimization by means of enumerative search implemented by the Hybrid Optimization Model for Electric Renewable program is used to generate a set of solutions optimized economically by the value of the net present cost (NPC). The analysis of greenhouse gas emissions (in tCO2-eq.) in the life cycle of each one of the system components is carried out and a set of solutions with the values of the two objective functions is generated, namely NPC and NAESLC (net avoided emissions in the system life cycle). The method is applied to a case study in a Cuban rural community. The compromise solution obtained by means of the proposed algorithm includes a wind turbine (WT) of 25.4 and 8?kW of photovoltaic panels, while that of the HOGA includes a WT of 76 and 21?kW of photovoltaic panels. Both commitment solutions consider hydrogen storage instead of storage in batteries, as a better option for the energy storage. Copyright (C) 2011 John Wiley & Sons, Ltd.