2 Power control of modified type III DFIG-based wind turbine system using four-mode type I fuzzy logic controller
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Bibhu Prasad Ganthia
Abstract
This chapter is devoted to the implementation of advanced controlled techniques to enhance the generation in wind energy system. Here, in this chapter, various modified fuzzy logic controllers are used to regulate the active power (P) and reactive power (Q) under transient conditions. The transient or the fault analysis is done with three-phase fault applied to the grid-integrated wind energy system. Here, in this chapter, modified rotor-based type III wind turbine system is implemented. Doubly fed induction generator is used in type III wind turbine system as the operating generator. Various modes of fuzzy logic structures are used as controllers in addition to the conventional PI controller. This adaptive controller is able to offer quicker settling time and faster response toward the transients occurred due to rapid change in wind speed or any other criteria for causing faults. All techniques are applied in the wind turbine design to get better result in comparison to other fuzzy logic controllers. Here, MATLAB is used for simulink design of the system and validated using real-time software TYPHOON HIL. The main motive is to validate that the modified type III wind turbine system can give efficient result using adaptive techniques to control active and reactive power. This chapter can be helpful for the researchers to analyze their works reference with these research findings.
Abstract
This chapter is devoted to the implementation of advanced controlled techniques to enhance the generation in wind energy system. Here, in this chapter, various modified fuzzy logic controllers are used to regulate the active power (P) and reactive power (Q) under transient conditions. The transient or the fault analysis is done with three-phase fault applied to the grid-integrated wind energy system. Here, in this chapter, modified rotor-based type III wind turbine system is implemented. Doubly fed induction generator is used in type III wind turbine system as the operating generator. Various modes of fuzzy logic structures are used as controllers in addition to the conventional PI controller. This adaptive controller is able to offer quicker settling time and faster response toward the transients occurred due to rapid change in wind speed or any other criteria for causing faults. All techniques are applied in the wind turbine design to get better result in comparison to other fuzzy logic controllers. Here, MATLAB is used for simulink design of the system and validated using real-time software TYPHOON HIL. The main motive is to validate that the modified type III wind turbine system can give efficient result using adaptive techniques to control active and reactive power. This chapter can be helpful for the researchers to analyze their works reference with these research findings.
Chapters in this book
- Frontmatter I
- Preface V
- Contents VII
- 1 Artificial intelligence and Internet of things for renewable energy systems 1
- 2 Power control of modified type III DFIG-based wind turbine system using four-mode type I fuzzy logic controller 41
- 3 An IoT-based approach for efficient home automation 91
- 4 Design and implementation of IoT-enabled smart single-phase energy meter monitoring system 123
- 5 Internet of things (IoT)-based smart grids 165
- 6 Maximum power point tracking control under partial shading conditions using particle swarm optimization algorithm 185
- 7 Wireless monitoring of substation using IoT 215
- 8 Smart grid–based big data analytics using machine learning and artificial intelligence: a survey 241
- 9 IoT-based intelligent solar energyharvesting technique with improved efficiency 279
- Editor’s Brief Biographies 303
- Index 307
Chapters in this book
- Frontmatter I
- Preface V
- Contents VII
- 1 Artificial intelligence and Internet of things for renewable energy systems 1
- 2 Power control of modified type III DFIG-based wind turbine system using four-mode type I fuzzy logic controller 41
- 3 An IoT-based approach for efficient home automation 91
- 4 Design and implementation of IoT-enabled smart single-phase energy meter monitoring system 123
- 5 Internet of things (IoT)-based smart grids 165
- 6 Maximum power point tracking control under partial shading conditions using particle swarm optimization algorithm 185
- 7 Wireless monitoring of substation using IoT 215
- 8 Smart grid–based big data analytics using machine learning and artificial intelligence: a survey 241
- 9 IoT-based intelligent solar energyharvesting technique with improved efficiency 279
- Editor’s Brief Biographies 303
- Index 307
