Publication Type:

Journal Article

Source:

International Journal of Innovative Research in Science, Engineering and Technology, Volume 4, Issue 6 (2015)

URL:

http://www.ijirset.com/upload/2015/multicon/eee/39_EE087.pdf

Keywords:

Photovoltaics; MPPT; DSP; Artificial neural networks; Genetic algorithms; Brushless dc motors

Abstract:

This paper presents photovoltaic system with a maximum power point tracking (MPPT) controller is connected to brushless dc motor drive for heating, ventilating and air conditioning fans. The MPPT controller is based on a genetic assisted, multi-layer perceptron neural network (GA-MLP-NN) structure and includes a DC–DC boost converter. Genetic assistance in the neural network is used to optimize the size of the hidden layer. Also, for training the network, a genetic assisted, Levenberg–Marquardt (GA-LM) algorithm is utilized. The off line GA-MLP-NN, trained by this hybrid algorithm, is utilized for online estimation of the volt-age and current values in the maximum power point. A brushless dc (BLDC) motor drive system that incorporates a motor controller with proportional integral (PI) speed control loop is successfully implemented to operate the fans. The digital signal processor (DSP) based unit provides rapid achievement of the MPPT and current control of the BLDC motor drive.

Cite this Research Publication

S. .Selvakani, Sindhu, D., and Anand Rajendran, “PV System Based MPPT Controller Supplying BLDC Motor Drive”, International Journal of Innovative Research in Science, Engineering and Technology, vol. 4, no. 6, 2015.