Add to ORKGAbstract — This paper deals with the Artificial Intelligent control of Doubly-Fed Induction Generator using Adaptive Neuro-Fuzzy Inference System in order to generate maximum power at variable wind speed. The rotor control is achieved here using the combined features of neural network and fuzzy logic controller. Index Terms—Doubly-fed Induction Generator (DFIG), Win
Wind energy is one of the extraordinary sources of renewable energy due to its clean character and f...
This paper presents fuzzy logic control of Doubly Fed Induction Generator (DFIG) wind turbine in a s...
Abstract. With the increasing size of wind power generation it is required to perform power system s...
This paper proposes an adaptive neuro-fuzzy inference system (ANFIS) maximum power point tracking (M...
A Takagi-Sugeno neuro-fuzzy inference system for direct power control of a doubly fed induction gene...
This paper proposes a novel variable speed control algorithm for a grid connected doubly-fed inducti...
This paper proposes a new computational control strategy. The control and analysis of Doubly Fed Ind...
A neural network controller is presented for the direct power control of a doubly fed induction gene...
This paper deals with a variable speed device to produce electrical energy on a power network, base...
Artificial intelligence techniques, such as fuzzy logic, neural network and genetic algorithm are re...
Abstract: This paper describes fuzzy logic control of induction generator speed in wind turbine appl...
This paper studies maximum wind power extraction from magnetic gear generator using an artificial ne...
Abstract--This paper presents the simulation and control of a grid connected doubly-fed induction ge...
The objective of this paper is to study the dynamic response of the wind energy conversion system (W...
Aim. This paper presents the minimization of reactive and active power ripples of doubly fed inducti...
Wind energy is one of the extraordinary sources of renewable energy due to its clean character and f...
This paper presents fuzzy logic control of Doubly Fed Induction Generator (DFIG) wind turbine in a s...
Abstract. With the increasing size of wind power generation it is required to perform power system s...
This paper proposes an adaptive neuro-fuzzy inference system (ANFIS) maximum power point tracking (M...
A Takagi-Sugeno neuro-fuzzy inference system for direct power control of a doubly fed induction gene...
This paper proposes a novel variable speed control algorithm for a grid connected doubly-fed inducti...
This paper proposes a new computational control strategy. The control and analysis of Doubly Fed Ind...
A neural network controller is presented for the direct power control of a doubly fed induction gene...
This paper deals with a variable speed device to produce electrical energy on a power network, base...
Artificial intelligence techniques, such as fuzzy logic, neural network and genetic algorithm are re...
Abstract: This paper describes fuzzy logic control of induction generator speed in wind turbine appl...
This paper studies maximum wind power extraction from magnetic gear generator using an artificial ne...
Abstract--This paper presents the simulation and control of a grid connected doubly-fed induction ge...
The objective of this paper is to study the dynamic response of the wind energy conversion system (W...
Aim. This paper presents the minimization of reactive and active power ripples of doubly fed inducti...
Wind energy is one of the extraordinary sources of renewable energy due to its clean character and f...
This paper presents fuzzy logic control of Doubly Fed Induction Generator (DFIG) wind turbine in a s...
Abstract. With the increasing size of wind power generation it is required to perform power system s...