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Pereira, P., S. Valtchev, J. Pina, A. Gonçalves, V. M. Neves, and A. L. Rodrigues, "Power electronics performance in cryogenic environment: evaluation for use in HTS power devices", Journal of Physics: Conference Series, vol. 97, no. 1, pp. 012219, 2008. AbstractWebsite

Power electronics (PE) plays a major role in electrical devices and systems, namely in electromechanical drives, in motor and generator controllers, and in power grids, including high-voltage DC (HVDC) power transmission. PE is also used in devices for the protection against grid disturbances, like voltage sags or power breakdowns. To cope with these disturbances, back-up energy storage devices are used, like uninterruptible power supplies (UPS) and flywheels. Some of these devices may use superconductivity. Commercial PE semiconductor devices (power diodes, power MOSFETs, IGBTs, power Darlington transistors and others) are rarely (or never) experimented for cryogenic temperatures, even when designed for military applications. This means that its integration with HTS power devices is usually done in the hot environment, raising several implementation restrictions. These reasons led to the natural desire of characterising PE under extreme conditions, e. g. at liquid nitrogen temperatures, for use in HTS devices. Some researchers expect that cryogenic temperatures may increase power electronics' performance when compared with room-temperature operation, namely reducing conduction losses and switching time. Also the overall system efficiency may increase due to improved properties of semiconductor materials at low temperatures, reduced losses, and removal of dissipation elements. In this work, steady state operation of commercial PE semiconductors and devices were investigated at liquid nitrogen and room temperatures. Performances in cryogenic and room temperatures are compared. Results help to decide which environment is to be used for different power HTS applications.

Cardoso, T., P. Pereira, V. Fernao Pires, and J. F. Martins, "Power quality and long life education", Industrial Electronics (ISIE), 2014 IEEE 23rd International Symposium on, Istanbul - Turkey, pp. 2224 - 2228, 2014/06. Abstract

This paper presents a remote laboratory linked with mobile devices for real data analysis on the field of power quality. A global system was developed from the power quality analyzer into the human machine interface devoted to the m-learning system. This m-learning system is intended to be used in a long life learning perspective. The developed remote laboratory is a good opportunity for people, even without deep knowledge on the field, to learn power quality principles in an applied way. Since the system is based on real data, is a good approach to give trainees practical knowledge on the field.

Pereira, P., F. Coito, and H. Fino, "PSO-Based Design of RF Integrated Inductor", Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2012, vol. 372, Costa de Caparica - Portugal, Springer Boston, pp. 475-482, 2012. Abstract

This paper addresses an optimization-based approach for the design of RF integrated inductors. The methodology presented deals with the complexity of the design problem by formulating it as a multi-objective optimization. The multi-modal nature of the underlying functions combined with the need to be able to explore design trade-offs leads to the use of niching methods. This allows exploring not only the best trade-off solutions lying on the Pareto-optimum surface but also the quasi-optimum solutions that would be otherwise discarded. In this paper we take advantage of the niching properties of lbest PSO algorithm using ring topology to devise a simple optimizer able to find the local-optima. For the efficiency of the process analytical models are used for the passive/active devices. In spite the use of physics-based analytical expressions for the evaluation of the lumped elements, the variability of the process parameters is ignored in the optimization stage due to the significant computational burden it involves. Thus in the final stage both the Pareto-optimum solutions and the quasi-optimum solutions are evaluated with respect to the sensitivity to process parameter variations.