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Papers in International Journals with Referee or Books

  • Unsupervised Neural-Network Based Algorithm for an On-Line Diagnosis of Three-Phase Induction Motor Stator Fault ; J. F. Martins, V. Fernão Pires, A. J. Pires – IEEE Transactions on Industrial Electronics (to appear). (Abstract)

  • Entropy Based Choice of a Neural Network Drive Model ; J. F. Martins, P. J. Santos, A. J. Pires, L. E. Borges da Silva and R. Vilela Mendes – IEEE Transactions on Industrial Electronics (to appear). (Abstract)

  • An Average Values Global Model for the Switched Reluctance Machine ; A. J. Pires, J. F. Martins, P. J. Branco, J. A. Dente, Special Issue of the Transactions of IMACS on Mathematics and Computers in Simulation (to appear).

  • Entropy Analysis on Electrical Drives Language Modeling; J. F. Martins, J. A. Dente, A. J. Pires, R. Vilela Mendes, Intelligent Systems at the Service of Mankind, Volume 2, Ubooks; Alemanha, 2006.(Abstract)

  • Short-term load forecast using trend information and process reconstruction ; P. J. Santos, A. G. Martins, A. J. Pires, J. F. Martins and R. V. Mendes – International Journal of Energy Research, 2006 (DOI: 10.1002/er.1187) . (Abstract)

  • Automatic Language Control of Electrical Drives. Background and Applications; J. F. Martins, J. A. Dente, A. J. Pires, R. Vilela Mendes, Intelligent Systems at the Service of Mankind, Volume 1, ISBN 3-935798-25-3; Ubooks; Alemanha, 2004.(Abstract)

  • A Neural Space Vector Fault Location for Parallel Double-Circuit Distribution Lines ; Sousa Martins, L.; Martins, J. F.; Fernão Pires, V.; Alegria, C. M – EPES - International Journal of Electrical Power & Energy Systems, Elsevier Science Ltd, 2005. (Abstract)

  • Fixed-Frequency Active Current Controller and Low-Sensitivity Voltage Regulator for a Voltage Sourced Buck-Boost Type Rectifier ; V. Fernão Pires, J. Fernando Silva, A. J. Pires – European Transactions on Electrical Power (ETEP) – 2004; 14:223-233 (DOI: 10.1002/etep.17) – John Wiley & Sons Ltd. (Abstract)

  • The ICT in the Polytechnic Institute of Setúbal – The Beginning of a New Phase; Armando J. Pires; Vítor T. Rodrigues – Journal on Systemics, Cybernetics and Informatics (JSCI), vol. 2 – n.º 1 – 2004 – ISSN 1690-4524.

  • A New Control Strategy Based On Optimised Smooth-Torque Current Waveforms for Switched Reluctance Motors; P. Lobato, A. J. Pires, J. A. Dente – Electromotion International Journal – Special Issue: 5th International Symposium on Advanced Electromechanical Motion Systems – vol. 10, n.º 4, pp. 579-583, October-December 2003 – Mediamira Science Publisher – ISSN 1223-057X.(Abstract)

  • On the use of Reactive Power as an Endogenous Variable in Short-term Load Forecasting; P. Jorge Santos, A. Gomes Martins, A. J. Pires - International Journal of Energy Research – 2003; 27:513-529 (DOI: 10.1002/er.892) - John Wiley & Sons Ltd.(Abstract)

 

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Communications in scientific meetings with Referee

  •  WPEC - A New Web Tool for the Power Electronics Learning”; Luis Esteves, V. Fernão Pires31h Annual Conference of the IEEE Industrial Electronics Society (IECON 2005), pp 2152-2155, November 6-10, 2005, Raleigh, USA. (Abstract)

  • The Switched Reluctance Generator for Wind Power Conversion; P. Lobato, A. Cruz, J. Silva, A.J. Pires – Proceedings do 9º Congresso Hispano Luso de Engenharia Electrotécnica, Marbella, Espanha, June/July 2005.(Abstract)

  •  O Gerador Eléctrico de Relutância Comutada como Alternativa aos Geradores Clássicos nos Aproveitamentos de Energia Eólica; P. Lobato, A. Cruz, J. Silva, A.J. Pires, Proceedings do International Congress Energy and Environment of Engineering and Management - ICIIEM2005, Portalegre, Portugal, May 2005 (in Portuguese).(Abstract)

  •  A Simple PID Controller with Adaptive Parameter in a dsPIC; Case of Study; João Chaínho, Pedro Pereira, Silviano Rafael and A.J. Pires  – Proceedings do 9º Congresso Hispano Luso de Engenharia Electrotécnica, Marbella, Espanha, June/July 2005.(Abstract)

  •  An Adaptive Learning Rate Approach for an On-Line Neuro-Fuzzy Speed Controller Applied to a Switched Reluctance Machine; Silviano Rafael, A.J. Pires, P.J. Costa Branco – IEEE International Symposium on Industrial Electronics - ISIE 2005, June 2005, Dubrovnik, Croatia. (Abstract)

  •  A Neuro-Fuzzy Multilayer Weights Approach for an On-Line Learning Speed Controller Applied to a Switched Reluctance Machine: Why and How to Use; Silviano Rafael, A. J. Pires, P. J. Costa Branco – 11º European Conference on Power Electronics and Applications – EPE 2005, Sepetember 2005 , Dresden , Germany. (Abstract)

  • On-Line Diagnosis of Three-Phase Induction Motor Using an Eigenvalue alfa beta–Vector Approach; V. Fernão Pires, J. F. Martins, A. J. Pires – IEEE International Symposium on Industrial Electronics - ISIE 2005, June 2005, Dubrovnik, Croatia. (Abstract)

  • An Average Values Global Model for the Switched Reluctance Machine; A. J. Pires, J. F. Martins, P. J. Branco, J. A. Dente – Proceedings da Conferência ELECTRIMACS 2005 – 8th International Conference on Modeling and Simulation of Electric Machines, Converters and Systems – Hammamet, Tunisia, April 2005. (Abstract)

  •  Performance of a Four Phase Switched Reluctance Motor Speed Control Based On an Adaptive Fuzzy System: Experimental Tests, Analysis and Conclusions; Silviano Rafael, A.J. Pires, P.J. Costa Branco – 9th Online World Conference on Soft Computing in Industrial Applications (WSC 9) – Setembro/Outubro 2004 (conferência on-line).(Abstract)

  • SVM Voltage Control implementation using low-cost reconfigurable FPGA system”; João Ferreira, J.F. Martins; Proceedings of EPE-PEMC 2004 – 11th International Power Electronics and Motion Control Conference - Riga, Latvia, September 2004.(Abstract)

  • Design and Implementation of a Laboratory Pseudo Master Oscilloscope Network”; Aurélio Costa, João Nunes, Silviano Rafael, J.F. Martins; Proceedings of EPE-PEMC 2004 – 11th International Power Electronics and Motion Control Conference - Riga, Latvia, September 2004.(Abstract)

  • On the Use of Matlab/Simulink as a Tool for the Study of Power Systems Transient”; Sousa Martins, L.; Pires, D. F.; Fernão Pires, V; Proceedings of EPE-PEMC 2004 – 11th International Power Electronics and Motion Control Conference - Riga, Latvia, September 2004.(Abstract)

  •  “A Model for the Switched Reluctance Machine with Global Parameters and Global Variables; A. J. Pires, J. F. Martins, P. J. Branco, J. A. Dente – Proceedings da Conferência CBA2004 – XV Brazilian Automation Congress - Gramado, Brasil, Setembro 2004. (Abstract)

  •  Metodologia de Parametrização de um Controlador Neuro-Fuzzy de Velocidade para uma Máquina de Relutância Variável; Silviano Rafael, A. J. Pires, P. J. Costa Branco – Proceedings da Conferência CBA2004 – XV Brazilian Automation Congress - Gramado, Brasil, Setembro 2004 (in Portuguese).(Abstract)

  • Network Operating Characteristics Based on Imposed MMF Waveforms for Switched Reluctance Generators“; P. Lobato , A. J. Pires, J. A. Dente – Proceedings da Conferência EPE-PEMC 2004 – 11th International Power Electronics and Motion Control Conference - Riga, Letónia, Setembro 2004 – ISBN: 9984-32-033-2.(Abstract)

  • Implementation of an On-Line Learning Speed Controller for a Switched Reluctance Machine“; Silviano Rafael, A.J. Pires, P.J. Costa Branco – Proceedings da Conferência EPE-PEMC 2004 – 11th International Power Electronics and Motion Control Conference - Riga, Letónia, Setembro 2004 – ISBN: 9984-32-033-2.(Abstract)

  • Formal Language Modelling of a Switched Reluctance Machine“; João F. Martins, Silviano Rafael, A. J. Pires – Proceedings of EPE-PEMC 2004 – 11th International Power Electronics and Motion Control Conference - Riga, Latvia, September 2004.(Abstract)

  • Short-term load forecasting based on ANN applied to electrical distribution Substations“; P. Jorge Santos, A. Gomes Martins, A. J. Pires – Proceedings da Conferência UPEC 2004 – International Universities Power Engineering Conference, Bristol, UK, Setembro 2004.(Abstract)

  •  A Methodology Based on Energy-Conversion Diagrams to Improve Switched Reluctance Generators Control; Pedro Lobato; A. J. Pires; J. A. Dente – Proceedings da Conferência ICEM’04, Cracóvia, Polónia, Setembro 2004.(Abstract)

  • The Polytechnic Institute of Setúbal and the ICT – The Example of an e-Learning Project Based on the Theory of Organized Activity; Armando J. Pires; José Cordeiro; Vítor T. Rodrigues; Joaquim Filipe – Proceedings da Conferência EISTA’2004 – Education and Information Systems: Technologies and Applications – vol.I, pp. 183 a 187 – Orlando, USA, Julho 2004 – ISBN: 980-6560-11-6.

  • Information System in the Polytechnic Institute of Setúbal"; Vítor Rodrigues; Armando Pires – Proceedings da Conferência EUNIS 2004 – 10th International Conference on European University Information Systems – pp. 458 a 462 – Bled, Eslovénia, Julho 2004 – ISBN: 961-6209-46-9.

  •  “Estimating Load Diagrams in Electricity Distribution Substations; P. Jorge Santos, A. Gomes Martins, A. J. Pires – Proceedings da Conferência ISAP 2003 – 12th Intelligent Systems Application to Power System Conference - Lemnos, Grécia, Setembro 2003.(Abstract)

  • The ICT in the Polytechnic Institute of Setúbal – The Beginning of a New Phase; Armando J. Pires; Vítor T. Rodrigues – Proceedings da Conferência EISTA’2003 –Education and Information Systems: Technologies and Applications – pp. 75 a 79 – Orlando, USA, Agosto 2003 – ISBN: 980-6560-03-5 (also published as a journal paper)

  • A Criteria for Designing Switched Reluctance Motors with Torque Ripple Reduction; Pedro Lobato; A. J. Pires; J. A. Dente – Proceedings do 8º Congresso Luso-Espanhol de Engenharia Electrotécnica – vol. III: Máquinas Eléctricas e Electrónica de Potência – pp. 6.209 a 6.214 - Vilamoura, Julho 2003 – ISBN 972-8822-00-6. (Abstract)

  • Implementation of a Speed Neuro-Fuzzy Controller for a Switched Reluctance Machine; Silviano Rafael; A. J. Pires; P. J. Costa Branco – Proceedings do 8º Congresso Luso-Espanhol de Engenharia Electrotécnica – vol. III: Máquinas Eléctricas e Electrónica de Potência – pp. 6.345 a 6.350 - Vilamoura, Julho 2003 – ISBN 972-8822-00-6 . (Abstract)

  • Implementation of an 8/6 Switched Reluctance MOSFET Current Controller: Simulation Study and Experimental Tests”; S. Rafael; A.J.Pires; P.J.Costa Branco – Proceedings da Conferência IEEE ISIE’03 – International Symposium on Industrial Electronics - Rio de Janeiro, Brasil, Junho 2003 – ISBN: 0-7803-7912-8. (Abstract)

  • Obtaining the Magnetic Characteristics of an 8/6 Switched Reluctance Machine: FEM Analysis and Experimental Tests”; B. Parreira; S. Rafael; A.J.Pires; P.J.Costa Branco – Proceedings da Conferência IEEE ISIE’03 – International Symposium on Industrial Electronics - Rio de Janeiro, Brasil, Junho 2003 – ISBN: 0-7803-7912-8.  (Abstract)

  • Supervision Language Control of Electromechanical Drives; J.F.Martins; A.J.Pires; R.Vilela Mendes; J.A.Dente – Proceedings da Conferência IEEE ISIE’03 – International Symposium on Industrial Electronics - Rio de Janeiro, Brasil, Junho 2003 – ISBN: 0-7803-7912-8  (Abstract)

  • A Network Distribution Power System Fault Location Based on Neural Eigenvalue Algorithm”; L. Sousa Martins, J. F. Martins, C. M. Alegria, V. Fernão Pires; IEEE PowerTech’03, Bologna, Italy, Junho 2003. (Abstract)

 

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Technical Reports

 

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Automatic Language Control of Electrical Drives. Background and Applications

A new formal language concept for automatic control of electrical drives is presented. The proliferation of these systems promises improved efficiency and reliability, reduced maintenance and operative costs, and a more environment friendly operation. However, they exhibit considerable complexities related with their behaviour such as large uncertainties at structural and parameter levels, multidimensionality, and strong mutual interactions. The integration of these systems with information processing techniques allows a better adaptative modelling of their behaviour. The electrical drive system is assumed as a linguistic source producing a certain language. A developed grammatical inference algorithm is used in order to extract the productions that govern a grammar representing that language. The formalism of the developed formal language based control algorithm is presented and experimental results are discussed.Home

Supervision Language Control of Electromechanical Drives

The aim of this paper is to introduce a formal language based approach to the automatic supervision control of electromechanical drives. Modern applications often involve electromechanical drives with high dynamical complexity. The proliferation of these systems promises improved efficiency and reliability, reduced maintenance and operative costs, and a more environment friendly operation. However, they exhibit considerable complexities related with their behavior such as large uncertainties at a structural and parameter levels, multidimensionality, and strong mutual interactions. The integration of these systems with information processing techniques allows a better adaptative modeling of their behavior and thus better supervision concepts. Formal language techniques have been used in the past to study autonomous dynamical systems. Assuming the drive system as a linguistic source, producing a certain language, the modeling framework is based on a formulation in terms of context-dependent grammars, distinguishing between information generated by the system and by the input control. Making use of the formal language descriptive characteristics the grammatical supervision algorithm governs the overall behavior of the drive. The formalism of the formal language based supervision control algorithm is presented and experimental results are discussed.Home

SVM Voltage Control implementation using low-cost reconfigurable FPGA system

This paper describes a full VHDL implementation of a voltage Space-Vector Modulation in a FPGA reconfigurable system. A VHDL code was specially developed and optimized based on a finite state machine, which has been proven a more flexible and integrated environment for performing the SVM. A FPGA XC4005XL from Xilinx is used to allow a high economical solution. MATLAB functions automatically optimize and generate a configuration bitstream for the FPGA. Experimental results confirm the validity of the proposed methodology.Home

Design and Implementation of a Laboratory Pseudo‑Master Oscilloscope Network

This paper presents the design, development and implementation of a laboratory pseudo-master oscilloscope network. The purpose of the network is to centralize the data from a series of several laboratory working benches into only one regular PC. The decision to store the experimental data is taken in each working bench, running the oscilloscopes as pseudo-master units. In order to cover large inter-benches distances the RS-485 protocol was adopted to establish the network over several oscilloscopes. A management software was developed to manage the data flow through all the network, the storage, in different folders, and visualization of the data obtain from the oscilloscopes. The stored data can be sent directly to a printer or embedded in other software applications. The potential of the developed system is shown, namely regarding to flexibility, cost and performance, in the scope of laboratory working quality.Home

Formal Language Modelling of a Switched Relutance Machine

The Switched Reluctance Machine is being widely spread among industrial and domestic applications, replacing other electrical machines. However its modelling and control present important difficulties, due to complex system nonlinearities. In this paper it is shown how the use of formal language technique can help in the modelling of a Switched Reluctance Machine, overcoming these difficulties. Experimental tests with a lab prototype are performed in order to obtain a realistic and automatic machine model.Home

A Network Distribution Power System Fault Location Based on Neural Eigenvalue Algorithm

A new approach to fault location for distribution network power system is presented. This approach uses the Eigenvalue and an artificial neural network based learning algorithm. The neural network is trained to map the non-linear relationship existing between fault location and characteristic Eigenvalue. The proposed approach is able to identify, to classify and to locate different types of faults such as: single-line-to-ground, double-line-to-ground, double-line and three-phase. Using the Eigenvalue as neural network inputs the proposed algorithm is able to locate the fault distance. The results presented show the effectiveness of the proposed algorithm for correct fault diagnosis and fault location on a distribution power system networks.Home

A neural space vector fault location for parallel double-circuit distribution lines

A new approach to fault location for parallel double-circuit distribution power lines is presented. This approach uses the Clarke–Concordia transformation and an artificial neural network based learning algorithm. The α, β, 0 components of double line currents resulting from the Clarke–Concordia transformation are used to characterize different states of the system. The neural network is trained to map the non-linear relationship existing between fault location and characteristic eigenvalue. The proposed approach is able to identify and to locate different types of faults such as: phase-to-earth, phase-to-phase, two-phase-to-earth and three-phase. Using the eigenvalue as neural network inputs the proposed algorithm locates the fault distance. Results are presented which shows the effectiveness of the proposed algorithm for a correct fault location on a parallel double-circuit distribution line.Home

Implementation of an On-Line Learning Speed Controller for a Switched Reluctance Machine

In the classical speed control of electrical machines it is usual to have linear PID controllers. This kind of controllers can present good results near a given operating point, where the machine may be considered as a linear system. However, the classical PID controller may have some limitations if it is planed to be used in a wide working region. In this case a good alternative can be the learning controllers using fuzzy logic and neural networks.In this paper it is presented and mainly discussed a neuro-fuzzy learning controller for speed regulation of an 8/6 Switched Reluctance Machine. Experimental results are presented and discussed showing how the controller can learn in real time the “good” rules. The results obtained with a classical PID controller are shown as a reference speed controller for the analysis. Home

Performance of a Four Phase Switched Reluctance Motor Speed Control Based On an Adaptive Fuzzy System: Experimental Tests, Analysis and Conclusions

In this paper, the controller’s tuning and performance of a speed controller prototype for switched reluctance motor is presented by a number of significative experimental tests. The system uses an on-line learning mechanism to acquire and modify, if needed, the “good” fuzzy control rules. Experimental essays are analysed and discussed to reveal some advantages of having a learning speed controller to the SR machine, and also the drawbacks that using these controllers can introduce to the drive system and possible ways to overcome them.Home

Metodologia de Parametrização de um Controlador Neuro-Fuzzy de Velocidade para uma Máquina de Relutância Variável In the classical speed control of electrical machines it is usual to have linear PID controllers. This kind of controllers can present good results near a given operating point, where the machine can be considered as a linear system. However, the classical PID controller has some limitations if it is planned to be used in a wide working region of electrical machines. In this case a good alternative can be the adaptive controllers using fuzzy logic and neural networks. One problem is tunning all parameters of the controller. This work presents the applied method and experimental results.Home
Implementation of a Neuro-Fuzzy Speed Controller for a Switched Reluctance Machine In the classical speed control of electrical machines it is usual to have linear PID controllers. This kind of controllers can present good results near a given operating point, where the machine can be considered as a linear system. However, the classical PID controller has some limitations if it is planed to be used in a wide working region of electrical machines. In this case a good alternative can be the “intelligent” controllers using fuzzy logic and neural networks.Home
Obtaining the Magnetic Characteristics of an 8/6-Switched Reluctance Machine: FEM Analysis and Experimental Tests

This paper describes the step-by-step procedure for modeling an 8/6 switched reluctance machine. Starting from establishing the geometry of the machine, a nite element modeling approach is initially developed to compute the [1]ux linkage/current/rotor position relationship extracting proper and mutual inductances, also its torque and eld distribution  characteristics. Experimental tests are performed to obtain the characteristics. Experimental tests are performed to obtain the magnetic characteristics of themachine, comparing, correcting, and discussing the results obtained with those of FEM analysis.Home

Implementation of an 8/6 Switched Reluctance mosfet Current Controller: Simulation Study And Experimental Tests

This paper describes the systematic procedure for designing a MOSFET power converter for an 8/6-switched reluctance machine. Starting from establishing its topology and subsystems, a Matlab simulation approach is initially developed to design its driving circuits, test different converter operating modes, and phase current controllers. Experimental tests are performed to verify the converter functionality and performance, comparing, correcting and discussing the results obtained with simulation analysis.Home
On the use of Reactive Power as an Endogenous Variable in Short-term Load Forecasting

In the last decades, short-term load forecasting (STLF) has been the object of particular attention in the power systems field. STLF has been applied almost exclusively to the generation sector, based on variables, which are transversal to most models. Among the most significant variables we can find load, expressed as active power (MW), as well as exogenous variables, such as weather and economy related ones, although the latter are applied in larger forecasting horizons than STLF.
In this paper the application of STLF to the distribution sector is suggested including inductive reactive power as a forecasting endogenous variable. The inclusion of this additional variable is mainly due to the evidence that correlations between load and weather variables are tenuous, due to the mild climate of the actual case-study system and the consequent feeble penetration of electrical heating ventilation and air conditioning (HVAC) loads.
Artificial neural networks (ANN) have been chosen as the forecasting methodology, with standard feed forward back propagation algorithm, because it is a largely used method with generally considered satisfactory results.
Usually, the input vector to ANN applied to load forecasting is defined in a discretionary way, mainly based on experience, on engineering judgement criteria and on concern about the ANN dimension, always taking into consideration the apparent (or actually evaluated) correlations within the available data. The approach referred in the paper includes pre-processing the data in order to influence the composition of the input vector in such a way as to reduce the margin of discretion in its definition. A relative entropy analysis has been performed to the time series of each variable. The paper also includes an illustrative case study.Home

Estimating load diagrams in electricity substations Load forecast is dealt with in this paper from the point of view of distribution networks. The issues associated with network management, as load dispatch and network reconfiguration, under quality of service constraints, require reliable short-term (next hour) load forecasts. Maintenance issues and eventual power purchase decisions within liberalised electricity markets require, among others, reliable next-day load forecasts. Substations in electricity distribution networks are usually monitored to such an extent that power and energy data is available at dispatch centres with a reasonable spatial and time detail, as provided by SCADA systems spread throughout the networks. This availability allows forecast models to be tailored to specific networks, in such a way that it is possible to grasp the particular load behaviour and provide forecasts with a good level of confidence. The paper deals with a methodological approach to the use of artificial neural networks (ANN) as forecast models. It makes use of a procedural sequence for the pre-processing phase that allows capturing certain predominant relations among certain different sets of available data, providing a more solid basis to decisions regarding the composition of the input vector to ANN. The methodological approach is discussed and a real life case study is used for illustrating the defined steps, the ANN and the quality level of the results.Home
Load Forecast Using Trend Information ANN Process Reconstruction

The algorithms for short-term load forecast (STLF), especially within the next-hour horizon, belong to a group of methodologies that aim to render more effective the actions of planning, operating and controlling electric energy systems (EES). In the context of the progressive liberalisation of the electricity sector, unbundling of the previous monopolistic structure emphasizes the need for load forecast, particularly at the network level. Methodologies such as artificial neural networks (ANN) have been widely used in next-hour load forecast. Designing an ANN requires, amongst other things, the proper choice of input variables, avoiding overfitting and an unnecessarily complex input vector (IV). This may be achieved by trying to reduce the arbitrariness in the choice of endogenous variables. At a first stage, we have applied the mathematical techniques of process-reconstruction to the underlying stochastic process, using coding and block entropies to characterize the measure and memory range. At a second stage, the concept of consumption trend in homologous days of previous weeks has been used. The possibility to include weather-related variables in the IV has also been analyzed, the option finally being to establish a model of the non-weather sensitive type. The paper uses a real-life case study.Home

A New Control Strategy Based On Optimised Smooth-Torque Current Waveforms for Switched Reluctance Motors

With the purpose of improving the dynamic performance of the Switched Reluctance Motor (SRM) one analyses its operation using MMF waveforms imposed in the linear region of its magnetic characteristics. Three factors are important in the control strategy: the dwell angle concerning the phase current and its location in the phase inductance profile; the phase current profiling; and the current control suitable to the application of the adopted strategy. In this paper, the first two points are analysed and a methodology is proposed to reduce the torque ripple and attenuate the phase voltage, by modelling current waveforms with specific criteria.Home

Network Operating Characteristics Based on Imposed MMF Waveforms for Switched Reluctance Generators

With the propose of improving the dynamic performance of the Switched Reluctance Generator (SRG) one analyses its operation using magnetomotive force (MMF) waveforms imposed in the linear region of the magnetic characteristics. In this paper, based on the proposed location of the dwell angle in the phase inductance profile, supported by energetic criteria, the SRG network operating characteristics were analysed for two typical cases: feeding a passive (ohmic) load and connected to a power network (infinite busbar).Home

A Methodology Based on Energy-Conversion Diagrams to Improve Switched Reluctance Generators Control With the aim of improving the dynamic performance of the Switched Reluctance Generator one analyses its operation using magnetomotive force (MMF) waveforms imposed in the linear region of its magnetic characteristics. Three factors are important in the control strategy of a SRG: the dwell angle concerning the phase current and its location in the inductance profile; the phase current profile; and the current control. In this paper, the first point is analyzed and a methodology based on energetic aspects is proposed in order to achieve higher efficiency.Home
Entropy Analysis on Electrical Drives Language Modeling This paper discusses the relationship between the memory range of a controlled dynamical system and the maximum type of allowed productions in a grammatical learning algorithm. This is an important issue when the performance of the learning process is discussed. The shorter the maximum type of allowed productions is the faster the learning process will be. However small values assigned for the maximum type of allowed productions can damage the learning process, being the obtained grammar an insufficient model of the electrical drive. The memory range of a dynamical system can be achieved by using mathematical techniques of process-reconstruction, using coding and block entropies. These modeling techniques allow a precise knowledge of the electrical drive dynamics, fundamental topic in modern control approaches.Home
The Switched Reluctance Generator for Wind Power Conversion The use of wind energy has become increasingly important as a renewable energy source, and therefore there is an increasing interest in exploiting it using a Switched Reluctance Machine (SRM) as a generator and optimise its characteristics in this domain. It is in this context that this paper analyzes the generator mode of the SRM 1) in a direct coupling to the turbine shaft and 2) coupled to the shaft through a gearbox. This paper is aimed at analyzing and proposing an alternative technical solution for wind power conversion, regarding the electrical generator system.Home
O Gerador Eléctrico de Relutância Comutada como Alternativa aos Geradores Clássicos nos Aproveitamentos de Energia Eólica A redução de emissões gasosas nefastas para o meio ambiente e a diminuição da dependência do petróleo como fonte primária de energia, são as principais razões que conduzem ao interesse crescente nas energias renováveis. De entre os vários tipos de energias renováveis existentes, a eólica é onde recai maior atenção, reflectindo-se naturalmente na investigação e desenvolvimento, particularmente nos sistemas electromecânicos e seus componentes, entre os quais os geradores eléctricos. Actualmente, as máquinas síncrona e assíncrona dominam o panorama das aplicações de energia eólica, no entanto, a Máquina Eléctrica de Relutância Comutada (MERC) tem sido alvo de investigação e é apontada como alternativa válida nestes aproveitamentos de energia. A despeito da MERC estar mais divulgada como motor, quer em aplicações de carácter industrial quer doméstico, como gerador existem aplicações na indústria aeronáutica e ainda, em menor número, trabalhos no domínio de geradores em aproveitamentos de energia eólica .Home
A Simple PID Controller with Adaptive Parameter in a dsPIC; Case of Study The main goal of this work consists in the development and implementation of a discrete PID controller with fast response and parameters adaptation capability, in an automatic way. This controller is based on a classic PID where a parameters adaptation algorithm was associated in order to control a process. This PID do not require any kind of adjustment or calibration from the operator. For the parameters adaptation one fuzzy system with a Takagi-Sugeno inference mechanism was chosen and some simplification of this system of decreasing the processing time and the controller response (250ms), in order to control fast processes without losing stability. The developed algorithm was implemented in a recent dsPIC30F. Home
An Adaptive Learning Rate Approach for an On-Line Neuro-Fuzzy Speed Controller Applied to a Switched Reluctance Machine The mostly used neuro-fuzzy motor speed control systems are time consuming and have an high computation effort when the speed reference changes gradually and the system has to learn the new operating point most of the time. In this cases a degradation of the system performance is evident has is demonstrated by experimental results in this paper. To surpass these effects, a decision and adaptation algorithm of the learning rate applied to the neuro-fuzzy control’s approach is proposed. The adaptive learning rate algorithm with the controller is tested and compared in the speed control system for an 8/6 switched reluctance motor by experimental tests. The proposed solution is explained, tested and the experimental tests are presented and discussed. Home
A Neuro-Fuzzy Multilayer Weights Approach for an On-Line Learning Speed Controller Applied to a Switched Reluctance Machine: Why and How to Use The most used neuro-fuzzy motor speed control systems are time consuming and have an high computation effort when the speed reference changes suddenly and the system, most of the time, has to learn this new operating point. In this case a degradation of the system performance is evident, as is demonstrated by our experimental results in this paper. To surpass these effects, a new neuro-fuzzy multilayer control’s approach is proposed. The multilayer controller is tested and compared in the speed control system for an 8/6 switched reluctance motor by experimental tests. The proposed solution is explained, tested and the experimental results are presented and discussed. Home
On-Line Diagnosis of Three-Phase Induction Motor Using an Eigenvalue alfa beta–Vector Approach An on-line diagnosis of three-phase induction motor using an automatic algorithm based on Park’s vector approach is presented. This algorithm uses the Eigenvalue approach and allows an interpretation of the ab–vector. In fact, stator current ab–vector patterns are first obtained, then the Eigenvalue algorithm is used to see if the motor is healthy or not. Experimental results are presented in order to show the effectiveness of the proposed method. Home
On the Use of Matlab/Simulink as a Tool for the Study of Power Systems Transient This paper presents a methodology for the modelling of power systems on the transient analysis. In this methodology the MATLAB/SIMULINK" program is used. This program width their non linear blocks can be advantageously used for different kind of variable situations on electrical power networks, such as fault diagnosis and stability control. Furthermore, the modelling effort and required simulation times are smaller than the conventional simulators, such as EMTP. Since state space models are used, this simulation tool is useful to study the transient phenomena and easier to compare with power systems laboratory results. This paper summarizes the used method and gives some examples. Home
A Neural Space Vector Fault Location for Parallel Double-Circuit Distribution Lines A new approach to fault location for parallel double-circuit distribution power lines is presented. This approach uses the Clarke-Concordia transformation and an artificial neural network based learning algorithm. The a,b,0 components of double line currents resulting from the Clarke-Concordia transformation are used to characterize different states of the system. The neural network is trained to map the non-linear relationship existing between fault location and characteristic Eigenvalue. The proposed approach is able to identify and to locate different types of faults such as: Phase-to-Earth, Phase-to-Phase, Two-Phase-to-Earth and Three-Phase. Using the Eigenvalue as neural network inputs the proposed algorithm locates the fault distance. Results are presented which shows the effectiveness of the proposed algorithm for a correct fault location on a parallel double-circuit distribution line. Home
An Average Values Global Model for the Switched Reluctance Machine The main subject of this paper is to present a new simplified global model for the Switched Reluctance Machine (SRM), useful, namely, for the command and control analysis of this kind of system. The concepts of power and energy are used in the global model construction, with the definition of global parameters and variables. This new global model presents an advantage over the classical detailed one, which is the reduction of the number of dynamic equations. The time-dependent global parameters disadvantage, which appears in the model construction process, is overcome with the consideration of average values for global variables and global parameters, allowing the representation of the machine non-detailed behavior. An Average Values Global Model is obtained. An 8/6 SRM with four phases, eight stator poles and six rotor poles is characterized and used for illustration of the system behavior, regarding its variables evolution. In the SRM command it is assumed that the m.m.f. is imposed, which means that the system current is controlled. Home
A Model for the Switched Reluctance Machine with Global Parameters and Global Variables O objectivo principal deste artigo é apresentar um modelo para a Máquina Eléctrica de Relutância Comutada, útil na análise do comando e controlo deste tipo de máquina. Utilizando os conceitos de potência e energia construiu-se um modelo com variáveis e parâmetros globais, que serão definidos no artigo. Este modelo tem a vantagem formal sobre o modelo detalhado tradicional de ter um reduzido número de equações dinâmicas. Esta abordagem pode ser vista como um caminho inicial no sentido de uma maior simplificação do modelo da máquina recorrendo a aproximações na determinação dos parâmetros e variáveis. Para ilustrar o comportamento do sistema, através da evolução dos vários parâmetros e variáveis, é utilizada uma máquina 8/6, com quarto fases, oito pólos no estator e seis pólos no rotor. No comando da máquina será assumido que a força magnetomotriz é imposta, o que significa que a corrente do sistema será controlada. Isto é útil na optimização do comportamento da máquina. Home
Fixed-Frequency Active Current Controller and Low-Sensitivity Voltage Regulator for a Voltage Sourced Buck-Boost Type Rectifier We present an active fixed-frequency input current controller and a low-sensitivity output voltage regulator for a voltage-source buck-boost type rectifier operating in the continuous current mode. The current controller enforces the input line current to track the desired sinusoidal waveform in phase with the input source voltage, ensuring a near-unity power-factor operation of the rectifier. The current control strategy actively shapes the input current allowing a near sinusoidal input current even with high variations in the DC inductor current. A low-sensitivity output voltage regulator modulating the amplitude of the sinusoidal reference for the current controller is also proposed. Both the current controller and the voltage regulator are based on sliding-mode theory. Experimental results are presented and the performance compared to that obtained using a conventional Proportional Integral (PI) output voltage controller. Home
A Criteria for Designing Switched Reluctance Motors with Torque Ripple Reduction With the goal of improving the dynamic performance of a Switched Reluctance Motor (SRM), it is important to find control strategies that reduce the machine torque ripple. In this way the settlement of a reference MMF synchronised with the rotor position, in conjunction with a suitable design of the SRM, allow to minimize the torque ripple, maintaining the torque nominal level of this type of machine. In this paper, an attention is devoted to the SRM design, concerning especially the relation between the number of stator and rotor poles. It is defined a criteria, based in the construction parameters of the machine, that indicates, a priori, which are the machine configurations that allow the minimization of torque ripple. Home
Short-term load forecast using trend information and process reconstruction The algorithms for short-term load forecast (STLF), especially within the next-hour horizon, belong to a group of methodologies that aim to render more effective the actions of planning, operating and controlling electric energy systems (EES). In the context of the progressive liberalization of the electricity sector, unbundling of the previous monopolistic structure emphasizes the need for load forecast, particularly at the network level. Methodologies such as artificial neural networks (ANN) have been widely used in next-hour load forecast. Designing an ANN requires the proper choice of input variables, avoiding overfitting and an unnecessarily complex input vector (IV). This may be achieved by trying to reduce the  arbitrariness in the choice of endogenous variables. At a first stage, we have applied the mathematical techniques of process-reconstruction to the underlying stochastic process, using coding and block entropies to characterize the measure and memory range. At a second stage, the concept of consumption trend in homologous days of previous weeks has been used. The possibility to include weather-related variables in the IV has also been analysed, the option finally being to establish a model of the non-weather sensitive type. The paper uses a real-life case study.Home
Unsupervised Neural-Network Based Algorithm for an On-Line Diagnosis of Three-Phase Induction Motor Stator Fault In this paper an automatic algorithm based an unsupervised neural-network for an on‑line diagnostics of three-phase induction motor stator fault is presented. This algorithm uses the alfa‑beta stator currents as input variables. Then a fully automatic unsupervised method is applied in which a hebbian-based unsupervised neural-network is used to extract the principal components of the stator current data. These main directions are used to decide where the fault occurs and a relationship between the current components is calculated to verify the severity of the fault. One of the characteristics of this method, given its unsupervised nature, is that it does not need a prior identification of the system. The proposed methodology has been experimentally tested on a 1kW induction motor. The obtained experimental results show the effectiveness of the proposed method.Home
Entropy Based Choice of a Neural Network Drive Model The design of a neural network requires, among other things, a proper choice of input variables, avoiding over fitting and an unnecessarily complex input vector. This may be achieved by trying to reduce the arbitrariness in the choice of the input layer.
This paper discusses the relation between the memory range of a particular controlled dynamical system (induction drive) and the dimension of the neural network input vector. Mathematical techniques of process-reconstruction of the underlying process, using coding and block entropies to characterize the measure and memory range, were applied. These modeling techniques provide a precise knowledge of the drive dynamics, a fundamental requirement in modern control approaches.Home
WPEC - A New Web Tool for the Power Electronics Learning This paper presents a new web tool for the power electronics learning. This tool has several goals. The first goal is to teach power electronics through interactive animations. To support the student’s learning in a more active way a chat option is also provided. This interactive option allows the students to communicate with the teacher and with other students. In order to test and verify the students knowledge an option with questions are also provided. This option provides several oriented questions in order to identify some problems in the learning of the students. This last tool will give to the students a path where they should focus their study.Home
Short-term load forecasting based on ANN applied to electrical distribution Substations The short-term load forecasting (STLF) algorithms belong to the set of methodologies which aim to furnish more effectiveness in planning, operation and conduction in electric energy systems (EES). The presence of a de-regulated environment reinforces the need of forecast, particularly in distribution networks. Actions like network management, load dispatch and network reconfiguration, under quality of service constraints, require reliable short-term (next hour) load forecasts. Artificial neural networks (ANN) are widely used in this horizon of prevision, with satisfactory results. The construction of an “efficient” ANN goes through, among, other factors, the construction of an “efficient” input vector, in order to avoid over fitting problems and keeping the global simplicity of the model. This paper deals with a methodological approach, in order to provide more solid basis decision regarding the composition of the input vector, namely, in the choice of the number of the contiguous values of the principle variable (active power). In a first approach it was established a search for any “chains with complete connections”, in the active power signal, based on Gibbs measure, and a relative entropy analysis. It was introduced the concept of “consumption tendency” in past homologous days. It was also analyzed the correlation between the consumption and the climatic data, having been established a non-weather sensitive model. The methodological approach is discussed and compared with another input vector. The model was tested in a real life case study for illustration of defined steps.Home