TITLE:
Solar PV System for Energy Conservation Incorporating an MPPT Based on Computational Intelligent Techniques Supplying Brushless DC Motor Drive
AUTHORS:
R. Anand, Dr. S. Saravanan
KEYWORDS:
Photovoltaic, Genetic Algorithms, Neural Network, Brushless DC Motors and Maximum Power Point Tracking
JOURNAL NAME:
Circuits and Systems,
Vol.7 No.8,
June
16,
2016
ABSTRACT: This paper proposes an effective Maximum Power Point Tracking (MPPT) controller being incorporated into a solar Photovoltaic system supplying a Brushless DC (BLDC) motor drive as the load. The MPPT controller makes use of a Genetic Assisted Radial Basis Function Neural Network based technique that includes a high step up Interleaved DC-DC converter. The BLDC motor combines a controller with a Proportional Integral (PI) speed control loop. MATLAB/Simulink has been used to construct the dynamic model and simulate the system. The solar Photovoltaic system uses Genetic Assisted-Radial Basis Function-Neural Network (GA-RBF-NN) where the output signal governs the DC-DC boost converters to accomplish the MPPT. This proposed GA-RBF-NN based MPPT controller produces an average power increase of 26.37% and faster response time.