Affiliations: [a]
EEE Department, Kalasalingam Academy of Research and Education, Krishnan Koil, India
| [b]
EEE Department, Velammal College of Engineering and Technology, Madurai, India
Correspondence:
[*]
Corresponding author. B. KanagaSakthivel, EEE Department, Kalasalingam Academy of Research and Education, Krishnan Koil, 626126, India. E-mail: sakthieee33@gmail.com.
Abstract: A hybrid renewable energy scheme comprising of the wind and solar PV electric power systems with appropriate maximum power point tracking is presented in this paper. The maximum power point tracking for the wind generator is carried out using Adaptive Neuro Fuzzy Inference System. The MPPT technique adopted for the photovoltaic power generation system is the Incremental Conductance (IC) algorithm. A power flow control scheme based on fuzzy logic is developed to regulate the power transaction from the wind and solar power sources as well as for the battery charging and discharging. Based on the available velocity of wind and solar insolation and based on the electrical demand different modes of operation are selected automatically using the ANFIS based control strategy. Considering the non linearity’s of the converters and the unpredictable nature of the renewable sources an advanced adaptive controller is necessary. The proposed ANFIS controller performs well and the proposed idea has been validated using MATLAB/Simulink and the simulation results are reported.
Keywords: Hybrid energy system, wind energy, solar PV, ANFIS, SVPWM
