SUMMARY This study presents a selection of optimal energy alternatives for electrical self‐sufficiency in a rural university (Universidad del Istmo, UNISTMO), located in the state of Oaxaca, Mexico and for the electricity supply for a rural community (Gran Piedra) in Santiago, Cuba. The analysis follows a multicriteria approach. It uses a method called compromise programming and takes into account the technical, economical, environmental and social criteria. The hybrid optimization model for electric renewables (HOMER) software was used to generate alternative energy sets through enumerative search, with which decisional matrices were built for each case study. The influence of weighting for each criterion was assessed. In the case of self‐sufficiency in UNISTMO, when the decision‐making center has a preference for the minimization of equivalent emissions in the life cycle (ESLC), a wind system is suitable. On the other hand, when there is a preference for the minimization of levelized cost of energy, a photovoltaic (PV) system is suitable; both systems connected to the national electrical grid. Obviously, a preference for the minimization of capital cost led to keeping the power supply from the grid. In the case of Gran Piedra, a diesel generator‐based system is suitable when the criterion ‘capital cost’ absorbs 70% or more of the preferences of the decision‐making centers. When the preference is less than 70% regardless of the weighting given to other criteria, the best alternatives are those involving renewable technologies, reaching renewable fractions of 75% and 94% in two potential configurations of energetic systems. Copyright © 2013 John Wiley & Sons, Ltd.
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 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 © 2011 John Wiley & Sons, Ltd.
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