Luis Manuel Ramos de Oliveira
@ualg.pt
Universidade do Algarve
EDUCATION
PhD - Electrical Eng.
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Nelson Pinto, Dario Cruz, Jânio Monteiro, Cristiano Cabrita, Jorge Semião, Pedro J. S. Cardoso, Luís M. R. Oliveira, and João M. F. Rodrigues
IGI Global
In many countries, renewable energy production already represents an important percentage of the total energy that is generated in electrical grids. In order to reach higher levels of integration, demand side management measures are yet required. In fact, different from the legacy electrical grids, where at any given instant the generation levels are adjusted to meet the demand, when using renewable energy sources, the demand must be adapted in accordance with the generation levels, since these cannot be controlled. In order to alleviate users from the burden of individual control of each appliance, energy management systems (EMSs) have to be developed to both monitor the generation and consumption patterns and to control electrical appliances. In this context, the main contribution of this chapter is to present the implementation of such an IoT-based monitoring and control system for microgrids, capable of supporting the development of an EMS.
Pedro J. S. Cardoso, Jânio Monteiro, Cristiano Cabrita, Jorge Semião, Dario Medina Cruz, Nelson Pinto, Célia M.Q. Ramos, Luís M. R. Oliveira, and João M. F. Rodrigues
IGI Global
Energy consumption and, consequently, the associated costs (e.g., environmental and monetary) concern most individuals, companies, and institutions. Platforms for the monitoring, predicting, and optimizing energy consumption are an important asset that can contribute to the awareness about the ongoing usage levels, but also to an effective reduction of these levels. A solution is to leave the decisions to smart system, supported for instance in machine learning and optimization algorithms. This chapter involves those aspects and the related fields with emphasis in the prediction of energy consumption to optimize its usage policies.
Pedro J. S. Cardoso, Jânio Monteiro, Cristiano Cabrita, Jorge Semião, Dario Medina Cruz, Nelson Pinto, Célia M.Q. Ramos, Luís M. R. Oliveira, and João M. F. Rodrigues
IGI Global
Energy consumption and, consequently, the associated costs (e.g., environmental and monetary) concern most individuals, companies, and institutions. Platforms for the monitoring, predicting, and optimizing energy consumption are an important asset that can contribute to the awareness about the ongoing usage levels, but also to an effective reduction of these levels. A solution is to leave the decisions to smart system, supported for instance in machine learning and optimization algorithms. This chapter involves those aspects and the related fields with emphasis in the prediction of energy consumption to optimize its usage policies.
Dario Cruz, Nelson Pinto, Jânio Monteiro, Pedro J. S. Cardoso, Cristiano Cabrita, Jorge Semião, Luís M. R. Oliveira, and João M. F. Rodrigues
Springer International Publishing
Luis M. R. Oliveira and Antonio J. Marques Cardoso
Institute of Electrical and Electronics Engineers (IEEE)
This paper presents a comparison of two of the most sensitive methods to detect low-level turn-to-turn faults in the windings of three-phase transformers. The performance of the negative sequence component and of the space vector protection algorithms is tested under several internal and/or external fault conditions. The simulation results indicate that the fault detection sensitivity of both methods is very similar.
X. M. Lopez-Fernandez, H. Ertan and J. Turowski
CRC Press
Luis M. R. Oliveira and A.J. Marques Cardoso
IEEE
This paper presents a comparison of two of the most sensitive methods to detect low-level turn-to-turn faults in the windings of three-phase transformers. The performance of the negative sequence component and of the space-vector protection algorithms is tested under several internal and/or external fault conditions. The results indicate that the space-vector approach is slightly more sensitive for detecting low-level turn-to-turn winding faults. For more severe defects, the fault detection sensitivity of both methods is similar.
Luis M. R. Oliveira and A. J. Marques Cardoso
Institute of Electrical and Electronics Engineers (IEEE)
This paper presents a general approach to compute the leakage inductances of power transformers with turn-to-turn winding faults. The leakage inductances are obtained by using well-known conventional formulas, adapted to the asymmetrical conditions produced by the interturn fault in the leakage flux distribution. Two methods for calculating the leakage inductances are presented: the first requires detailed information about the geometry of the windings whereas the second uses simplifying assumptions, allowing to express the leakage inductances as a function of the nameplate short-circuit inductance, the number of turns, and core dimensions. A leakage inductance model of the transformer with faulty turns is also proposed, which is based on the three-winding transformer theory. This leakage inductance equivalent circuit can be easily integrated into other electromagnetic transient simulators. The results obtained from the application of the analytical methods and the equivalent circuit are validated using data obtained from finite-element analysis and experimental short-circuit tests.
Luís M. R. Oliveira and A. J. Marques Cardoso
Springer Berlin Heidelberg
L.M.R. Oliveira and A.J.M. Cardoso
Institution of Engineering and Technology (IET)
This study presents a new scheme for power transformers protection, which is based on the analysis of the harmonic content of the differential current Park's vector modulus. The proposed method is able to detect turn-to-turn winding insulation failures, and to distinguish them from magnetising inrush current transients. Experimental and simulation results are presented and discussed.
Luís M.R. Oliveira and A.J. Marques Cardoso
Elsevier BV
Luís M. R. Oliveira and António J. Marques Cardoso
Springer Berlin Heidelberg
Luís M.R. Oliveira, A.J. Marques Cardoso, and Sérgio M.A. Cruz
Elsevier BV
Luís M. R. Oliveira and A. J. Marques Cardoso
Institute of Electrical and Electronics Engineers (IEEE)
In the above titled paper (ibid., vol. 25, no. 3, pp. 1589-1598, Jul. 10), there were some textual errors that are corrected here.
Luis M. R. Oliveira and A. J. Marques Cardoso
IEEE
This paper intends to provide a detailed characterization of the transformer behavior under the influence of inrush currents and/or incipient winding faults. Experimental and simulation results are presented and discussed. Finally, a promising new method to identify inrush currents, and to distinguish them from internal faults, is suggested.
Luís. M. R. Oliveira and A. J. Marques Cardoso
Institute of Electrical and Electronics Engineers (IEEE)
This paper investigates the behavior of power transformers under the occurrence of permanent or intermittent winding insulation faults. For the study of these phenomena, a simple and efficient permeance-based electromagnetic transformer model is proposed, which is based on the simultaneous consideration of magnetic and electric equivalent circuits. To incorporate the internal faults in this model, a suitable equivalent circuit of the faulty winding is described. With the aid of this transformer model, the onload exciting current Park's Vector Approach will be applied for diagnosing the occurrence of permanent and intermittent winding faults. Experimental and simulation tests results are presented in this paper, which demonstrate not only the adequacy of the digital transformer model for winding fault studies, but also the effectiveness of the proposed technique for detecting winding interturn insulation faults in operating three-phase transformers.
Luis M. R. Oliveira and A. J. Marques Cardoso
IEEE
This paper presents the application of the on-load exciting current Park's vector approach for diagnosing permanent and intermittent turn-to-turn winding faults in operating power transformers. A digital model for the simulation of the behavior of three-phase transformers affected by the presence of winding faults is also proposed. Experimental and simulated results demonstrate the effectiveness of the proposed diagnostic technique, which is based on the on-line monitoring of the .on-load exciting current Park's Vector patterns.