960 resultados para Pannelli Fotovoltaici, MPPT, Energia Solare, Simulink, Matlab, Cella Fotovoltaica, Modello, Confronto algoritmi, P


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This paper introduces how artificial intelligence technologies can be integrated into a known computer aided control system design (CACSD) framework, Matlab/Simulink, using an object oriented approach. The aim is to build a framework to aid supervisory systems analysis, design and implementation. The idea is to take advantage of an existing CACSD framework, Matlab/Simulink, so that engineers can proceed: first to design a control system, and then to design a straightforward supervisory system of the control system in the same framework. Thus, expert systems and qualitative reasoning tools are incorporated into this popular CACSD framework to develop a computer aided supervisory system design (CASSD) framework. Object-variables an introduced into Matlab/Simulink for sharing information between tools

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

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Today, the trend within the electronics industry is for the use of rapid and advanced simulation methodologies in association with synthesis toolsets. This paper presents an approach developed to support mixed-signal circuit design and analysis. The methodology proposed shows a novel approach to the problem of developing behvioural model descriptions of mixed-signal circuit topologies, by construction of a set of subsystems, that supports the automated mapping of MATLAB (R)/SINIULINK (R) models to structural VHDL-AMS descriptions. The tool developed, named (MSSV)-S-2, reads a SIMULINK (R) model file and translates it to a structural VHDL-AMS code. It also creates the file structure required to simulate the translated model in the SystemVision (TM). To validate the methodology and the developed program, the DAC08, AD7524 and AD5450 data converters were studied and initially modelled in MATLAB (R)/SIMULINK (R). The VHDL-AMS code generated automatically by (MSSV)-S-2, (MATLAB (R)/SIMULINK (R) to SystemVision (TM)), was then simulated in the SystemVision (TM). The simulation results show that the proposed approach, which is based on VHDL-AMS descriptions of the original model library elements, allows for the behavioural level simulation of complex mixed-signal circuits.

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Today, the trend within the electronics industry is for the use of rapid and advanced simulation methodologies in association with synthesis toolsets. This paper presents an approach developed to support mixed-signal circuit design and analysis. The methodology proposed shows a novel approach to the problem of developing behvioural model descriptions of mixed-signal circuit topologies, by construction of a set of subsystems, that supports the automated mapping of MATLAB®/SIMULINK® models to structural VHDL-AMS descriptions. The tool developed, named MS 2SV, reads a SIMULINK® model file and translates it to a structural VHDL-AMS code. It also creates the file structure required to simulate the translated model in the System Vision™. To validate the methodology and the developed program, the DAC08, AD7524 and AD5450 data converters were studied and initially modelled in MATLAB®/ SIMULINK®. The VHDL-AMS code generated automatically by MS 2SV, (MATLAB®/SIMULINK® to System Vision™), was then simulated in the System Vision™. The simulation results show that the proposed approach, which is based on VHDL-AMS descriptions of the original model library elements, allows for the behavioural level simulation of complex mixed-signal circuits.

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Electrical energy from photovoltaic panels (PV) has became an increasing viable alternative because of the great concern for environmental preservation and the possibility of the reduction of the conventional fuels, and this natural energy source is free, abundant and clean. In addition, Brazil is a privileged country because of the high levels of irradiation throughout its territory all over the year. Thus the exploitation of the energy from PV is one of the best alternatives to overcome the supply electrical energy issues. However, nowadays the energy conversion efficiency is low and the initial costs are high for these energy systems. Therefore, in order to increase the efficiency of these systems the extraction of the maximum power point (MPP) from PV is extremely necessary, and it is done using the maximum power point tracking (MPPT) techniques. The MPP of the PV varies non linearly with the environmental conditions and several MPPT techniques are available in literature, and this paper presents a careful comparison among the most usual techniques, doing meaningful comparisons with respect to the amount of energy extracted, PV voltage ripple, dynamic response and use of sensors, considering that the models are implemented via MatLab/Simulink®. © 2010 IEEE.

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This paper presents a careful evaluation among the most usual MPPT (Maximum Power Point Tracking) techniques, doing meaningful comparisons with respect to the amount of energy extracted from the photovoltaic (PV) panel, PV voltage ripple, dynamic response and use of sensors. Firstly, the MPPT and boost converter models were implemented via MatLab/Simulink®, and after a DC to DC boost converter, digitally controlled, was implemented and connected to an Agilent Solar Array simulator, in order to validate the simulation results. The algorithms are digitally developed and the main experimental results are also presented from the implemented prototype. Furthermore, the experimental dynamic results and the computed tracking factors are presented. © 2011 IEEE.

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This paper presents a careful evaluation among the most usual MPPT techniques, doing meaningful comparisons with respect to the amount of energy extracted from the photovoltaic (PV) panel, PV voltage ripple, dynamic response and use of sensors, considering that the models are first implemented via MatLab/Simulink®, and after a digitally controlled boost DC-DC converter was implemented and connected to an Agilent Solar Array simulator in order to verify the simulation results. The prototype was built, the algorithms are digitally developed and the main experimental results are also presented, including dynamic responses and the experimental tracking factor (TF) for the analyzed MPPT techniques. © 2011 IEEE.

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This paper presents the analysis of some usual MPPT (Maximum Power Point Tracking) strategies intended for small wind energy conversion (up to 1kW) based on permanent magnet synchronous generators (PMSG), considering the stand-alone application for a novel buck-boost integrated inverter. Each MPPT method is analytically introduced and then it is simulated using MatLab/Simulink considering standard conditions of wind and also commercially available turbines and generators. The extracted power in each case is compared with the maximum available power, so the tracking factor is calculated for each method. Thus, the focus is on the application to improve the efficiency of stand-alone wind energy conversion systems (WECS) with battery chargers and AC load supplied by inverter. Therefore, for this purpose a novel single phase buck-boost integrated inverter is introduced. Finally, the main experimental results for the introduced inverter are presented. © 2011 IEEE.

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This paper presents evaluations among the most usual maximum power point tracking (MPPT) techniques, doing meaningful comparisons with respect to the amount of energy extracted from the photovoltaic (PV) panel [tracking factor (TF)] in relation to the available power, PV voltage ripple, dynamic response, and use of sensors. Using MatLab/Simulink and dSPACE platforms, a digitally controlled boost dc-dc converter was implemented and connected to an Agilent Solar Array E4350B simulator in order to verify the analytical procedures. The main experimental results are presented for conventional MPPT algorithms and improved MPPT algorithms named IC based on proportional-integral (PI) and perturb and observe based on PI. Moreover, the dynamic response and the TF are also evaluated using a user-friendly interface, which is capable of online program power profiles and computes the TF. Finally, a typical daily insulation is used in order to verify the experimental results for the main PV MPPT methods. © 2012 IEEE.

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Pós-graduação em Engenharia Elétrica - FEIS