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.

Yes / Clean water demand has significantly increased due to the rise in the global population. However, most water on the Earth has high saline content that cannot be consumed directly; only about one over forty of the total water source is freshwater. Desalinated water is one of the potential solutions to meet the growing demand for freshwater, which is highly energy intensive. This paper analyses the energy, economic and environmental performance of a 5 m3/day PV (photovoltaic) powered reverse osmosis (RO) desalination system. Three scenarios of PV-RO with and without battery storage and diesel generator hybrid systems have been analyzed and investigated for the annual estimate load, net present value, and payback period of the water and electricity production costs. Also, the CO2 avoidance over the lifetime operation of all scearios is evaluated. This study shows that the PV-RO system without battery with 6.3 kW PV panels installed and with a 2-days water storage tank system is the most profitable economically f. For this scenario, the Levelized Cost of Electricity (LCOE), Levelized Cost of Water (LCOW), and Payback Period (PBP) are found to be $0.154/kWh, $0.627/m3, and five years, respectively. In addition, for this scenario, the CO2 emissions avoidance was the maximum (111,690 kg.CO2eq per year) compared to other scenarios.

Master of Science / Department of Electrical and Computer Engineering / Anil Pahwa / In Afghanistan, electricity is mostly generated by hydroelectric, diesel and natural gas generators. A significant amount of electricity also is imported from neighboring countries. Accessibility of electricity is mostly limited to the capital and main towns. The government of Afghanistan and other development organizations, such as The United States Agency for International Development (USAID) and Deutsche Gesellschaft für Internationale Zusammenarbeit (German Agency for International Cooperation “GIZ”), are striving to develop accessibility of electricity to remote communities by supporting the local population of people to enhance living conditions. Although some of these remote communities are served by local diesel fuel generators for just a couple of hours during the night, still most communities do not have access to electricity and they are using wood and kerosene as major sources of energy in cooking, heating and lighting. For those remote communities who are served by local diesel fuel generators, the cost of electricity is much higher than from the national grid. On the other hand, grid extensions are too expensive and, in some cases, impossible for such communities because of the geographical features of Afghanistan. Afghanistan is a mountainous country which receives a significant amount of snow during the winter and once it melts the water runs into rivers, lakes and streams. Therefore mostly it does not face any shortage of running water during the year. Also Afghanistan has plentiful wind and solar energy. Therefore, small hydro-power, wind turbine and solar energy are attractive renewable energy sources for remote communities. The development of such a hybrid power system is a complex process and technical expertise is essential in design and construction phases. The main challenges are the high cost of civil works and equipment, technical expertise for design and construction and encouragement of local people for the support of the project. This report will give an insight into design, cost-effectiveness and feasibility of the system using HOMER in order to encourage private investors and local community people to take advantage of this potential available in Afghanistan and be convinced of the sustainability for investments in micro-hydropower, wind and solar.

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.

This thesis describes a systematical study, including multidisciplinary modeling, simulation, control, and optimization, of a fuel cell - gas turbine hybrid power system that aims to increase the system efficiency and decrease the energy costs by combining two power sources. The fuel cell-gas turbine hybrid power systems can utilize exhaust fuel and waste heat from fuel cells in the gas turbines to increase system efficiency. This research considers a hybrid power system consisting of an internally reforming solid oxide fuel cell and a gas turbine. In the hybrid power system, the anode exhaust, which contains the remainder of the fuel, is mixed with the cathode exhaust as well as an additional supply of fuel and compressed air and then burned in a catalytic oxidizer. The hot oxidizer exhaust is expanded through the turbine section, driving an electric generator. After leaving the gas turbine, the oxidizer exhaust passes through a heat recovery unit in which it preheats the compressed air that is to be supplied to the fuel cell and the oxidizer. This research concentrates on multidisciplinary modeling and simulation of the fuel cell-gas turbine hybrid power system. Different control strategies for the power sharing between the subsystems are investigated. Also, the power electronics interfaces and controls for the hybrid power system are discussed. Two different power sharing strategies are studied and compared. Simulation results are presented and analyzed. Transient response of the hybrid energy system is studied through time-domain simulation. In addition, in this effort, Particle Swarm Optimization (PSO) is used to optimize the power sharing for the hybrid power system to increase the efficiency and decrease the fuel consumption.

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.

No description available.