Small-scale wind turbine is typically designed to resisted extreme wind; this work aims to adjust their pitch angle based on simulations that use standardization codes for wind turbines. Proportional integral derivative (PID) and artificial neural network (ANN) controllers are used to control the speed of wind turbines. The ideal action for controlling the blade pitch angle can be attained by providing the controller with speed information ahead of time, allowing the controller to provide the best action for blade pitch angle control. The results of this work represent the relationship between the turbine speed with respect to time at different pitch angle. It has been concluded that the ANN controller produced the best time response as com...
This paper proposes the method combining artificial neural network (ANN) with particle swarm optimiz...
The present work proposes an artificial neural network (ANN) to analyze vertical axis wind turbines ...
Abstract—This paper focuses on developing a novel algorithm which dynamically optimizes the controll...
Abstract – Control of pitch angle of turbine blades is among the controlling methods in the wind tur...
In this work, a neural controller for wind turbine pitch control is presented. The controller is bas...
Wind has proven to be one of the most successful of all available sources of renewable energy offeri...
In the present contribution, the modelling of the aerodynamic coefficients of wind turbines are obta...
A BP Neural Network PID control method was applied in the variable speed adjustable pitch wind turbi...
A neural network controller is presented for the direct power control of a doubly fed induction gene...
Wind energy conversion systems (WECS) now play a significant role in meeting the world's energy need...
Since wind power is directly influenced by wind speed, long-term wind speed forecasting (WSF) plays ...
In recent years, world energy crisis is getting serious. Much new energy is found to take the posit...
International audienceIn this paper, an adaptive control scheme for maximum power point tracking of ...
This study aims to propose a robust hybrid sliding mode artificial neural network control (SM-ANN) s...
In this paper, a new type of multi-variable compensation control method for the wind energy conversi...
This paper proposes the method combining artificial neural network (ANN) with particle swarm optimiz...
The present work proposes an artificial neural network (ANN) to analyze vertical axis wind turbines ...
Abstract—This paper focuses on developing a novel algorithm which dynamically optimizes the controll...
Abstract – Control of pitch angle of turbine blades is among the controlling methods in the wind tur...
In this work, a neural controller for wind turbine pitch control is presented. The controller is bas...
Wind has proven to be one of the most successful of all available sources of renewable energy offeri...
In the present contribution, the modelling of the aerodynamic coefficients of wind turbines are obta...
A BP Neural Network PID control method was applied in the variable speed adjustable pitch wind turbi...
A neural network controller is presented for the direct power control of a doubly fed induction gene...
Wind energy conversion systems (WECS) now play a significant role in meeting the world's energy need...
Since wind power is directly influenced by wind speed, long-term wind speed forecasting (WSF) plays ...
In recent years, world energy crisis is getting serious. Much new energy is found to take the posit...
International audienceIn this paper, an adaptive control scheme for maximum power point tracking of ...
This study aims to propose a robust hybrid sliding mode artificial neural network control (SM-ANN) s...
In this paper, a new type of multi-variable compensation control method for the wind energy conversi...
This paper proposes the method combining artificial neural network (ANN) with particle swarm optimiz...
The present work proposes an artificial neural network (ANN) to analyze vertical axis wind turbines ...
Abstract—This paper focuses on developing a novel algorithm which dynamically optimizes the controll...