Thesis (Ph. D.)--Ohio State University, 2007. / Full text release at OhioLINK's ETD Center delayed at author's request

Thesis (Ph.D.)--Clemson University, 2007. / Adviser: Elham B. Makram. Includes bibliographical references.

Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, June 2002. / Thesis advisor(s): John Ciezki, Sherif Michael. Includes bibliographical references (p. 101-102). Also available online.

Thesis (M.Eng.)--Memorial University of Newfoundland, 2004. / Bibliography: leaves 115-129.

Thesis (Ph.D.)--Montana State University--Bozeman, 2006. / Typescript. Chairperson, Graduate Committee: Steven R. Shaw. Includes bibliographical references (leaves 115-119).

Thesis (M.S.)--Missouri University of Science and Technology, 2009. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed November 17, 2009) Includes bibliographical references (p. 67-70).

Battery charging wind turbines like, Hybrid Field Generator, have become more popular in the growing renewable energy market. With wind energy, voltage and current control is generally provided by means of power electronics. The paper describes the analytical investigation in to control aspects of a hybrid field generator controller for optimized performance. The project objective is about maintaining the generated voltage at 28V through out a generator speed range, between 149 rpm and 598 rpm. The over voltage load, known as dump load, is connected to the control circuit to reduce stress on the bypass transistor for speeds above 598 rpm. Maintaining a stable voltage through out the speed range, between 149rpm and 598rpm, is achieved by employing power electronics techniques. This is done by using power converters and inverters to vary the generator armature excitation levels hence varying its air gap flux density. All these take place during each of the three modes of generator operation, which are: buck, boost and permanent magnet modes. Although the generator controller is power electronics based, it also uses software to optimize its performance. In this case, a PIC16F877 microcontroller development system has been used to test the controller function blocks.

Este trabalho apresenta o desenvolvimento e simulação de um Controlador Supervisório Inteligente para sistemas híbridos de energia de pequeno porte. O controlador utiliza técnicas de inteligência artificial, baseadas em redes neurais artificiais e lógica neuro-fuzzy, para realizar previsões de velocidade de vento e demanda de curto prazo, permitindo a tomada de decisões otimizadas de despacho para o sistema híbrido de energia. Os principais objetivos do controlador são: o atendimento à carga, a maximização na utilização da fonte renovável eólica e a redução da participação do gerador diesel, assim como são tomados procedimentos adequados para preservar a vida útil da bateria. Um modelo computacional foi criado para calcular o balanço energético de qualquer sistema híbrido a partir de séries de dados medidos de demanda e velocidade de vento. A avaliação do desempenho do controlador foi realizada comparando-se os resultados obtidos com dois outros algoritmos comumente usados para controle de sistemas híbridos. Também foi feita uma análise econômica simplificada usando a figura de mérito do custo de ciclo de vida (CCV) para destacar as vantagens do novo controlador supervisório inteligente para sistemas híbridos. / This work presents the development and simulation results of an Intelligent Supervisory Controller for hybrid power systems. The controller uses artificial intelligence techniques, based on artificial neural networks and neuro-fuzzy logic, to forecast both wind power and load, and to take optimal dispatch decisions for hybrid power systems. The main controller objectives are: supply the load, priorize wind power and minimize diesel contribution while following appropriate procedures to preserve batteries life. A simulation tool has been created to compute the energy balance of any hybrid system using measured load and wind speed time series. The performance analysis was carried out by comparing the simulation results against two other common hybrid systems\' control algorithms. Also, a simplified life cycle cost analysis (CCV) has been executed in order to point out the economic advantages of the new intelligent supervisory controller for hybrid power systems.

Este trabalho apresenta o desenvolvimento e simulação de um Controlador Supervisório Inteligente para sistemas híbridos de energia de pequeno porte. O controlador utiliza técnicas de inteligência artificial, baseadas em redes neurais artificiais e lógica neuro-fuzzy, para realizar previsões de velocidade de vento e demanda de curto prazo, permitindo a tomada de decisões otimizadas de despacho para o sistema híbrido de energia. Os principais objetivos do controlador são: o atendimento à carga, a maximização na utilização da fonte renovável eólica e a redução da participação do gerador diesel, assim como são tomados procedimentos adequados para preservar a vida útil da bateria. Um modelo computacional foi criado para calcular o balanço energético de qualquer sistema híbrido a partir de séries de dados medidos de demanda e velocidade de vento. A avaliação do desempenho do controlador foi realizada comparando-se os resultados obtidos com dois outros algoritmos comumente usados para controle de sistemas híbridos. Também foi feita uma análise econômica simplificada usando a figura de mérito do custo de ciclo de vida (CCV) para destacar as vantagens do novo controlador supervisório inteligente para sistemas híbridos. / This work presents the development and simulation results of an Intelligent Supervisory Controller for hybrid power systems. The controller uses artificial intelligence techniques, based on artificial neural networks and neuro-fuzzy logic, to forecast both wind power and load, and to take optimal dispatch decisions for hybrid power systems. The main controller objectives are: supply the load, priorize wind power and minimize diesel contribution while following appropriate procedures to preserve batteries life. A simulation tool has been created to compute the energy balance of any hybrid system using measured load and wind speed time series. The performance analysis was carried out by comparing the simulation results against two other common hybrid systems\' control algorithms. Also, a simplified life cycle cost analysis (CCV) has been executed in order to point out the economic advantages of the new intelligent supervisory controller for hybrid power systems.

D. Tech. Electrical Engineering. / Aims to : 1. Derive the analytical solutions for describing the spectral characteristics of multicarrier based multilevel PWM inverter using double Fourier transform. 2. To carry out a comprehensive modelling of a cascaded NPC/H-bridge for PV-Grid application. 3. To integrate the Cascaded NPC/H-bridge inverter, grid and PV model and analyze the power flow characteristics for varying PV source current and voltage. Detailed analysis of PV and development of MPPT algorithm are not part of this thesis. 4. To develop a novel hybrid phase shifted PWM control algorithm and test its superior harmonic suppression in MATLAB simulation. 5. To compare the developed control algorithm with conventional multicarrier approach in terms of harmonic suppression and component count 6. To develop a control scheme that is capable of injecting maximum power into the grid from the model at different environmental conditions. 7. To explore and develop analytical tools for DC- link voltage control of the model. 8. To design and built a scaled down. 9 Level cascaded NPC/H-bridge inverter for grid connected application.