AN ENHANCED MPPT TECHNIQUE FOR SMALL-SCALE WIND ENERGY CONVERSION SYSTEMS

Monica.S, Ramesh K

Abstract: This paper proposes an enhanced Maximum Power Point Technique (MPPT) based on Artificial Neural Network (ANN) for small-scale wind energy conversion systems using Permanent Magnet synchronous Generators (PMSGs). The conventional MPPT technique which used a Perturb and observes (P&O) method is compared with the proposed ANN method. For this, MATLAB/Simulink is used to simulate both the conventional P&O method and the proposed ANN method. The proposed ANN uses the dc- link voltage and duty cycle as the control variables for MPPT. The advantages of the proposed MPPT are low system cost, increase reliability, less mechanical stress of the generator and no need for shaft speed sensing. Moreover the conversion efficiency of the proposed ANN method is increased while comparing with the conventional P&O method.

Keywords: Maximum Power Point Technique (MPPT), Perturb and Observe Algorithm (P&O), Artificial Neural Network (ANN), Wind Energy Conversion System (WECS)

DOI: https://doi.org/10.15623/ijret.2014.0319150