José Manuel Lavié Martínez

Ga-based passive loop optimization for magnetic field mitigation of transmission lines

This paper presents a systematic method to assist in the design of passive loops with the aim of mitigating the magnetic field generated by overhead transmission lines. The procedure is based on a two-dimensional (2D) modeling of the magnetic field, using a genetic algorithm (GA) to obtain the optimal mitigation design both for non-compensated and compensated coils. The proposed technique is applied to a horizontal line using three different passive mitigating configurations. Numerical results of the convergence and mitigation effectiveness, as well as discussion of the results, are provided.

“Feminizing” Middle Management? An Inquiry Into the Gendered Subtexts in University Department Headship

This article summarizes a number of issues emerging in a research in progress that is concerned with the analysis of university department headship from a gender perspective. The article interprets the narratives produced by 20 women as they talk about their experience as heads of departments at three different universities in the city of Barcelona (Spain). The three universities, which are all publicly funded, are going through a similar process of change in many different aspects concerning teaching, research, and management. Overall, what these and other changes mean to middle management is an intensification of administrative workload, an increased capacity required to manage and implement external changes, and a displacement of formerly held prerogatives in the hiring and promotion of the staff. All these issues have emerged in some or other way in the narratives of the 20 heads of department that took part in this study as involving multiple tensions and contradictions that have to be sorted out at the department level. They all carry with them, too, a gender subtext that is not always discernible at first sight.

INCA: A tool for the assessment and improvement of supply reliability indices

This paper presents a software tool, named INCA, for the assessment and improvement of supply reliability indices. Based on statistical failure rates associated to each individual component, and other recorded information, such as restoration and reparation times, INCA obtains expected reliability indices related with the number and duration of interruptions, for a feeder or set of feeders. INCA then allows the user to improve the resulting indices so that they are within permisible limits. This is carried out, either automatically or assisted by the user, by means of systematic procedures such as the addition of protecting devices or the modification of the feeder topology.

Topology–independent artificial neural network for overload screening

Abstract The process of determining whether a power system is in a secure or insecure state is a crucial task which must be addressed on-line in any energy management system. In this paper, an artificial neural network, capable of accurately identifying the set of harmful contingencies, is presented, along with several results obtained from a real-size power network. The proposed approach makes use of classical numerical techniques to compensate the ANNs inputs so that it can deal with topological changes in the power system.