INTERNATIONAL JOURNAL OF ENERGY RESEARCH Optimization of autonomous hybrid systems with hydrogen storage: Life cycle assessment Geovanni Herna ´ ndez Galvez 1 , Oliver Probst 2 , O. Lastres 3 , Airel Nu ´n ˜ ez Rodrı ´guez 3 , Alina Juantorena Uga ´s 4 , Edgar Andrade Dura ´n 1 and P. J. Sebastian 1,Ã,y 1 Centro de Investigacio ´ n en Energı ´a-UNAM, Temixco, Morelos 62580, Me ´ xico 2 Instituto Tecnolo ´ gico del Estudios Superiores de Monterre, Ave. Eugenio Garza Sada 2501 Sur, Col. Tecnolo ´ gico 64849, Monterrey, Nuevo Leo ´n, Me ´ xico 3 Instituto de Estudios de la Energı ´a, Universidad del Istmo, Oaxaca, Me ´ xico 4 Universidad Polite ´ cnica del Estado de Morelos, Jiutepec, Morelos, Me ´ xico SUMMARY 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 tCO 2 -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 NAE SLC (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 21kW of photovoltaic panels. Both commitment solutions consider hydrogen storage instead of storage in batteries, as a better option for the energy storage. Copyright r 2011 John Wiley & Sons, Ltd. KEY WORDS stand-alone wind energy system; multi-objective optimization; life cycle analysis; fuel cells; electrolyzers Correspondence *P. J. Sebastian, Centro de Investigacio ´ n en Energı ´a-UNAM, Temixco, Morelos 62580, Me ´ xico. y E-mail: sjp@cie.unam.mx Received 7 October 2010; Revised 28 December 2010; Accepted 30 December 2010 1. INTRODUCTION Poverty reduction and sustainable development remain a top priority at international level. Climate change threatens the entire world, but developing countries are the most vulnerable. They are estimated to bear approximately 75–80% of the cost of damage caused by climate change. Even warming of 21C above pre- industrial temperatures could result in a permanent reduction in gross domestic product between 4 and 5% in Africa and South Asia. For the temperature not to deviate from the 21C above pre-industrial levels (probably the best outcome that can be achieved), a true revolution is needed in the energy sector. This entails the rapid dissemination of energy efficient technologies with low carbon emission levels, accom- panied by massive investment in next generation technologies, without which growth cannot be achieved with low carbon emissions. In its 2009 publication of World Energy Outlook (WEO), the International Energy Agency (IEA) addresses issues of special relevance to the world energy situation and forecasts for this area until 2030. According to the report, expanding access to modern energy for the world’s poor remains a priority. An estimated 1.5 billion people (more than a fifth of the world population) still lack access to electricity. Approximately 85% of these people live in rural areas, mainly in sub-Saharan Africa and South Asia. It is estimated that by 2030 the total number will be Copyright r 2011 John Wiley & Sons, Ltd. Int. J. Energy Res. 2012; 36: – Published online 28 February 2011 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/er.1830 749 763 749