Power converters systems aimed at renewable energy applications have become a common option for sustainable electricity and distributed generation, since their performance has improved, and prices have steadily been reduced in the last years. However, there are still several drawbacks that hinder their widespread installation, such as the simultaneous minimization of cost and volume, efficiency maximization, size reduction, etc. Quite often, accomplishing these goals requires dealing with complicated optimization problems, which are difficult to solve by classical methods. Metaheuristic techniques provide a viable alternative to solve complex, intricate optimization problems, such as those encountered in the development of power electronics converters. This paper presents a comprehensive coverage of metaheuristic methodologies applied in the area of power converters. The review includes a classification of the methodologies and main objective functions in each paper surveyed. An aim for this paper is to highlight the importance of the optimization tools, and the many benefits they provide to tackle the challenges encountered in the design, operation and control of power converters. O 0885-8993 (c)

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Current methods for reliability prediction are based on Physics-of-Failure approaches. Such is the case of the FIDES methodology, that takes into account the times sequences of operation of an electronic assembly. In this paper, the reliability of a DC/DC converter aimed at photovoltaic applications is explored, considering the mission profiles for three different installations sites, at latitudes ranging from N 18.65 to N 32.67. Meteorological data collected in a 10-years time span was available for these sites. The mission profiles were obtained by first dividing the output power provided by a PV panel into ten levels, and then retrieving the temperature and humidity conditions that concur at each level. The components with the highest contribution to the overall failure rate  were the diodes, followed by the capacitor at the output. The results indicate that the thermal factor has the largest impact on the failure rate , highlighting the importance of efficient heatmanagement techniques. When the effect of the individual operational phases was assessed, it was also found that those linked to power levels above 70 % are responsible of the largest contribution to . In the case of the dormant condition, the highest humidity produces the highest failure rate.

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