Distributed power generation is a technology that could help to enable efficient, renewable energy production both in the developed and developing world. It includes all use of small electric power generators, whether located on the utility system, at the site of a utility customer, or at an isolated site not connected to the power grid. Induction generator (IG) is the most commonly used and cheapest technology, compatible with renewable energy resources. Permanent magnet (PM) generators have traditionally been avoided due to high fabrication costs; however, compared with IGs they are more reliable and productive.Distributed Generation thoroughly examines the principles, possibilities and limitations of creating energy with both IGs and PM generators. It takes an electrical engineering approach in the analysis and testing of these generators, and includes diagrams and extensive case study examples to better demonstrate how the integration of energy sources can be accomplished. The book also provides the practical tools needed to model and implement new techniques for generating energy through isolated or grid-connected systems.Besides a chapter introducing the technical, economic and environmental impacts of distributed generation, this book includes: an examination of various phase-balancing schemes for a three-phase IG operating on a single-phase power system;a coupled circuit 2-D finite element analysis of a grid-connected IG, with Steinmetz connection;a study of self-excited induction generator (SEIG) schemes for autonomous power systems, and the voltage and frequency control of SEIG with a slip-ring machine (SESRIG);a report on a PM synchronous generator with inset rotor for achieving a reduced voltage regulation when supplying an autonomous power system, and an analysis of its performance using a two-axis model and finite element method;experimental work on various IG and SEIG schemes.This book is a must-read for engineers, consultants, regulators, and environmentalists involved in energy production and delivery, helping them to evaluate renewable energy sources and to integrate these into an efficient energy delivery system. It is also a superior reference for undergraduates and postgraduates. Designers, operators, and planners will appreciate its unique contribution to the literature in this field.

Distributed power generation is a technology that could help to enable efficient, renewable energy production both in the developed and developing world. It includes all use of small electric power generators, whether located on the utility system, at the site of a utility customer, or at an isolated site not connected to the power grid. Induction generator (IG) is the most commonly used and cheapest technology, compatible with renewable energy resources. Permanent magnet (PM) generators have traditionally been avoided due to high fabrication costs; however, compared with IGs they are more reliable and productive.

Distributed Generation thoroughly examines the principles, possibilities and limitations of creating energy with both IGs and PM generators. It takes an electrical engineering approach in the analysis and testing of these generators, and includes diagrams and extensive case study examples to better demonstrate how the integration of energy sources can be accomplished. The book also provides the practical tools needed to model and implement new techniques for generating energy through isolated or grid-connected systems.

Besides a chapter introducing the technical, economic and environmental impacts of distributed generation, this book includes:

an examination of various phase-balancing schemes for a three-phase IG operating on a single-phase power system; a coupled circuit 2-D finite element analysis of a grid-connected IG, with Steinmetz connection; a study of self-excited induction generator (SEIG) schemes for autonomous power systems, and the voltage and frequency control of SEIG with a slip-ring machine (SESRIG); a report on a PM synchronous generator with inset rotor for achieving a reduced voltage regulation when supplying an autonomous power system, and an analysis of its performance using a two-axis model and finite element method; experimental work on various IG and SEIG schemes.

This book is a must-read for engineers, consultants, regulators, and environmentalists involved in energy production and delivery, helping them to evaluate renewable energy sources and to integrate these into an efficient energy delivery system. It is also a superior reference for undergraduates and postgraduates. Designers, operators, and planners will appreciate its unique contribution to the literature in this field.

Induction motors are the most important workhorses in industry. They are mostly used as constant-speed drives when fed from a voltage source of fixed frequency. Advent of advanced power electronic converters and powerful digital signal processors, however, has made possible the development of high performance, adjustable speed AC motor drives. This book aims to explore new areas of induction motor control based on artificial intelligence (AI) techniques in order to make the controller less sensitive to parameter changes. Selected AI techniques are applied for different induction motor control strategies. The book presents a practical computer simulation model of the induction motor that could be used for studying various induction motor drive operations. The control strategies explored include expert-system-based acceleration control, hybrid-fuzzy/PI two-stage control, neural-network-based direct self control, and genetic algorithm based extended Kalman filter for rotor speed estimation. There are also chapters on neural-network-based parameter estimation, genetic-algorithm-based optimized random PWM strategy, and experimental investigations. A chapter is provided as a primer for readers to get started with simulation studies on various AI techniques. Presents major artificial intelligence techniques to induction motor drivesUses a practical simulation approach to get interested readers started on drive developmentAuthored by experienced scientists with over 20 years of experience in the fieldProvides numerous examples and the latest research resultsSimulation programs available from the book's Companion WebsiteThis book will be invaluable to graduate students and research engineers who specialize in electric motor drives, electric vehicles, and electric ship propulsion. Graduate students in intelligent control, applied electric motion, and energy, as well as engineers in industrial electronics, automation, and electrical transportation, will also find this book helpful.Simulation materials available for download at www.wiley.com/go/chanmotor

Induction motors are the most important workhorses in industry. They are mostly used as constant-speed drives when fed from a voltage source of fixed frequency. Advent of advanced power electronic converters and powerful digital signal processors, however, has made possible the development of high performance, adjustable speed AC motor drives.

This book aims to explore new areas of induction motor control based on artificial intelligence (AI) techniques in order to make the controller less sensitive to parameter changes. Selected AI techniques are applied for different induction motor control strategies. The book presents a practical computer simulation model of the induction motor that could be used for studying various induction motor drive operations. The control strategies explored include expert-system-based acceleration control, hybrid-fuzzy/PI two-stage control, neural-network-based direct self control, and genetic algorithm based extended Kalman filter for rotor speed estimation. There are also chapters on neural-network-based parameter estimation, genetic-algorithm-based optimized random PWM strategy, and experimental investigations. A chapter is provided as a primer for readers to get started with simulation studies on various AI techniques.

Presents major artificial intelligence techniques to induction motor drives Uses a practical simulation approach to get interested readers started on drive development Authored by experienced scientists with over 20 years of experience in the field Provides numerous examples and the latest research results Simulation programs available from the book''s Companion Website

This book will be invaluable to graduate students and research engineers who specialize in electric motor drives, electric vehicles, and electric ship propulsion. Graduate students in intelligent control, applied electric motion, and energy, as well as engineers in industrial electronics, automation, and electrical transportation, will also find this book helpful.

Simulation materials available for download at www.wiley.com/go/chanmotor

Distributed power generation is a technology that could help to enable efficient, renewable energy production both in the developed and developing world. It includes all use of small electric power generators, whether located on the utility system, at the site of a utility customer, or at an isolated site not connected to the power grid. Induction generator (IG) is the most commonly used and cheapest technology, compatible with renewable energy resources. Permanent magnet (PM) generators have traditionally been avoided due to high fabrication costs; however, compared with IGs they are more reliable and productive.Distributed Generation thoroughly examines the principles, possibilities and limitations of creating energy with both IGs and PM generators. It takes an electrical engineering approach in the analysis and testing of these generators, and includes diagrams and extensive case study examples to better demonstrate how the integration of energy sources can be accomplished. The book also provides the practical tools needed to model and implement new techniques for generating energy through isolated or grid-connected systems.Besides a chapter introducing the technical, economic and environmental impacts of distributed generation, this book includes: an examination of various phase-balancing schemes for a three-phase IG operating on a single-phase power system;a coupled circuit 2-D finite element analysis of a grid-connected IG, with Steinmetz connection;a study of self-excited induction generator (SEIG) schemes for autonomous power systems, and the voltage and frequency control of SEIG with a slip-ring machine (SESRIG);a report on a PM synchronous generator with inset rotor for achieving a reduced voltage regulation when supplying an autonomous power system, and an analysis of its performance using a two-axis model and finite element method;experimental work on various IG and SEIG schemes.This book is a must-read for engineers, consultants, regulators, and environmentalists involved in energy production and delivery, helping them to evaluate renewable energy sources and to integrate these into an efficient energy delivery system. It is also a superior reference for undergraduates and postgraduates. Designers, operators, and planners will appreciate its unique contribution to the literature in this field.

Distributed power generation is a technology that could help to enable efficient, renewable energy production both in the developed and developing world. It includes all use of small electric power generators, whether located on the utility system, at the site of a utility customer, or at an isolated site not connected to the power grid. Induction generator (IG) is the most commonly used and cheapest technology, compatible with renewable energy resources. Permanent magnet (PM) generators have traditionally been avoided due to high fabrication costs; however, compared with IGs they are more reliable and productive.

Distributed Generation thoroughly examines the principles, possibilities and limitations of creating energy with both IGs and PM generators. It takes an electrical engineering approach in the analysis and testing of these generators, and includes diagrams and extensive case study examples to better demonstrate how the integration of energy sources can be accomplished. The book also provides the practical tools needed to model and implement new techniques for generating energy through isolated or grid-connected systems.

Besides a chapter introducing the technical, economic and environmental impacts of distributed generation, this book includes:

an examination of various phase-balancing schemes for a three-phase IG operating on a single-phase power system; a coupled circuit 2-D finite element analysis of a grid-connected IG, with Steinmetz connection; a study of self-excited induction generator (SEIG) schemes for autonomous power systems, and the voltage and frequency control of SEIG with a slip-ring machine (SESRIG); a report on a PM synchronous generator with inset rotor for achieving a reduced voltage regulation when supplying an autonomous power system, and an analysis of its performance using a two-axis model and finite element method; experimental work on various IG and SEIG schemes.

This book is a must-read for engineers, consultants, regulators, and environmentalists involved in energy production and delivery, helping them to evaluate renewable energy sources and to integrate these into an efficient energy delivery system. It is also a superior reference for undergraduates and postgraduates. Designers, operators, and planners will appreciate its unique contribution to the literature in this field.

Induction motors are the most important workhorses in industry. They are mostly used as constant-speed drives when fed from a voltage source of fixed frequency. Advent of advanced power electronic converters and powerful digital signal processors, however, has made possible the development of high performance, adjustable speed AC motor drives. This book aims to explore new areas of induction motor control based on artificial intelligence (AI) techniques in order to make the controller less sensitive to parameter changes. Selected AI techniques are applied for different induction motor control strategies. The book presents a practical computer simulation model of the induction motor that could be used for studying various induction motor drive operations. The control strategies explored include expert-system-based acceleration control, hybrid-fuzzy/PI two-stage control, neural-network-based direct self control, and genetic algorithm based extended Kalman filter for rotor speed estimation. There are also chapters on neural-network-based parameter estimation, genetic-algorithm-based optimized random PWM strategy, and experimental investigations. A chapter is provided as a primer for readers to get started with simulation studies on various AI techniques. Presents major artificial intelligence techniques to induction motor drivesUses a practical simulation approach to get interested readers started on drive developmentAuthored by experienced scientists with over 20 years of experience in the fieldProvides numerous examples and the latest research resultsSimulation programs available from the book's Companion WebsiteThis book will be invaluable to graduate students and research engineers who specialize in electric motor drives, electric vehicles, and electric ship propulsion. Graduate students in intelligent control, applied electric motion, and energy, as well as engineers in industrial electronics, automation, and electrical transportation, will also find this book helpful.Simulation materials available for download at www.wiley.com/go/chanmotor

Induction motors are the most important workhorses in industry. They are mostly used as constant-speed drives when fed from a voltage source of fixed frequency. Advent of advanced power electronic converters and powerful digital signal processors, however, has made possible the development of high performance, adjustable speed AC motor drives.

This book aims to explore new areas of induction motor control based on artificial intelligence (AI) techniques in order to make the controller less sensitive to parameter changes. Selected AI techniques are applied for different induction motor control strategies. The book presents a practical computer simulation model of the induction motor that could be used for studying various induction motor drive operations. The control strategies explored include expert-system-based acceleration control, hybrid-fuzzy/PI two-stage control, neural-network-based direct self control, and genetic algorithm based extended Kalman filter for rotor speed estimation. There are also chapters on neural-network-based parameter estimation, genetic-algorithm-based optimized random PWM strategy, and experimental investigations. A chapter is provided as a primer for readers to get started with simulation studies on various AI techniques.

Presents major artificial intelligence techniques to induction motor drives Uses a practical simulation approach to get interested readers started on drive development Authored by experienced scientists with over 20 years of experience in the field Provides numerous examples and the latest research results Simulation programs available from the book''s Companion Website

This book will be invaluable to graduate students and research engineers who specialize in electric motor drives, electric vehicles, and electric ship propulsion. Graduate students in intelligent control, applied electric motion, and energy, as well as engineers in industrial electronics, automation, and electrical transportation, will also find this book helpful.

Simulation materials available for download at www.wiley.com/go/chanmotor