Pedro Pereira

Sand pile and Bean models have already been applied to describe single grain HTS bulks. An extension to that approach was used to model multiseed bulks, needed for several practical applications as electric motors or flywheels with superconducting bearings. The use of genetic algorithms was then proposed to determine intra- and intergrain current densities, and application to two and three seeds samples using trapped flux experimental measurements was exemplified. However, this model assumed some simplifications, as equal properties in grain boundaries between neighboring grains. In this paper an extension to this methodology is proposed and evaluated by analyzing measurements performed in plans at different distances from surfaces of samples with three seeds. Discussion of its influence on a practical application is also explored.

The study and assessment of Power Quality issues is nowadays a very important subject, particularly regarding Cyber-physical and Industrial Agents based systems, which are extremely sensitive to Power Quality disturbances. Giving students or engineers practical experience in this field requires a large investment from teaching institutions. This paper presents a laboratory device that emulates Power Quality disturbances in order to provide the required experimental expertize in the subject. It addresses limiting aspects such as harmonic distortion, flicker, sags, swells and transients. The developed system presents a good opportunity for technicians, even without deep knowledge on the field of power quality, to learn basic principles and be able to identify Power Quality events. Since the system is based on real data, represents a valuable approach giving trainees practical knowledge on the field.

In this paper, three metaheuristics are investigated to optimize RF Integrated Inductors; namely Differential Evolution (DE) from the field of evolutionary computation, Gravitational Search Algorithm (GSA) based on the law of gravity and mass interactions and Particle Swarm Optimization (PSO) inspired by swarm behaviors in nature. A particular interest is given to the optimization of RF Integrated Inductors. Performances in terms of optimum quality and computing time of the metaheuristics are checked via three test functions and one application that consist of optimizing performances of characterize integrated inductors based on the double$π$-model.

Abstract This paper deals with multiobjective analog circuit optimization taking into consideration performance sensitivity vis-a-vis parameters' variations. It mainly considers improving computation time of the inloop optimization approaches by including sensitivity considerations in the Pareto front generation process, not as a constraint, but by involving it within the used metaheuristic evolution process. Different approaches are proposed and compared. NSGA-II metaheuristic is considered. The proposed sensitivity aware approaches are showcased via two analog circuits, namely, a second generation \{CMOS\} current conveyor and a \{CMOS\} voltage follower. We show that the proposed ideas considerably alleviate the long computation time of the process and improve the quality of the generated front, as well.

This work deals with the multi-objective optimization of analog circuits by generating the Pareto front where elements are low sensitive to parameters' variations. NSGA-II is used for obtaining the non-dominated solutions. Richardson extrapolation technique is used for the in-loop optimization approach for computing partial derivatives and, thus, the solutions' sensitivity. NSGA-II Pareto fronts' intrinsic ranking is exploited for the generation of the new ‘low-sensitive’ Pareto front. The case of the optimal sizing of a CMOS voltage follower is considered to exemplify the proposed approach.

The integration of high temperature superconductors (HTS) in electrical machines potentially allows reduction in devices dimensions or performance improvement for the same active volume, when compared with their conventional ones. The use of polycrystalline HTS samples allows big bulk samples. An axial disc motor with HTS material or conventional aluminium in the rotor and conventional armature has been designed and developed. This paper describes simulations and laboratory experiments performed at liquid nitrogen temperature (77 K) in order to analyze the motor's behaviour and its electromechanical characteristics and to define an electric equivalent circuit that allows describing its operation. In order to evaluate the superconducting quality of the bulks and flux pinning phenomena, Hall probe mapping system was performed in order to define the field profiles at 77 K for different polar configurations. The analysis of the obtained results allows confirm the flux pinning phenomena, being the entire rotor magnetized and conclude that the motor with the HTS rotor behaves as a conventional hysteresis motor even though with a different nature, while the motor with aluminium rotor behaves as a conventional induction motor. In asynchronous regime, the HTS motor exhibits a constant torque, higher than the conventional aluminium one. For both cases, the developed torque is proportional to the poles pairs.

Electrical Protective Devices are key elements in the electrical network. Their purpose is to perform fault detection in electric power systems, by analysing power system voltages and currents. In order to achieve a more centralized control, protective devices can be connected using Web Services through a Service-Oriented Architecture (SOA) approach. This work targets planning and specification of a mapping between Abstract Communication Service Interface (ACSI) Reporting and Device Profile for Web Services (DPWS) Eventing to achieve a better protective electrical devices control, obtaining an event based alert software system, replacing conventional polling-based systems.

Progressive scaling of CMOS technology towards nanoscale regime enables the design of highly integrated systems for the wireless communications market. As technology continues to scale, the variability in process parameters may cause significant deviations in device behaviour. The complexity of designing spiral inductors has lead to the development of multi-objective optimization based design methodologies yielding the generation of Pareto-optimal surfaces. However, the variability of the process parameters is usually ignored, yielding the selection of ideally optimal solutions in detriment of quasi-optimal solutions that may prove to be better, should the robustness against process parameter variation be accounted for. We propose the generation of an extended Pareto front containing both optima and quasi-optima solutions. Finally information on the robustness to process parameter variations, is used for electing the best design solutions.The evaluation of the extended set of sub-optima solutions requires methods capable to find the set of local optima, since solutions that are close to each other in the performance index space may be very distant in the design parameter space.

Power Quality is a generic term focusing on several issues, going from reliability to the quality of service provided by the energy supplier. It addresses limiting aspects such as harmonic distortion, flicker, sags, swells and transients... It is important for the students to understand the differences between the large amounts of events that fit into poor power quality category. Moreover it is important for them to analyze real time non-laboratory events. To provide this experience to the students this paper presents a remote m-learning experimental system where several types of poor power quality events can be tested. The developed system is based on a power quality analysis distributed network and can be remotely accessed from a remote computer or smart phones.

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.