Efficient maximum power tracking technique in grid connected PV-wind system

Abstract

• This paper develops a design and analysis of the hybrid system with a DC-DC converter controlled by hybrid approach. • This hybrid approach is a combination of Adaptive Neuro Fuzzy Interference System- Honey Badger Algorithm (ANFIS-HBA) for extracting maximum power and power compensation. • The hybrid system is designed with PV and WT for compensating load demand in the grid side. • The main objective of the proposed methodology is to extract the maximum power of the system (PV and WT). The sustainable energy resources are considered to generate the power without consumption of fuel. From that, the Photovoltaic (PV) and Wind Turbine (WT) are selected because of advantages such as pollution free and low computational cost. In the sustainable energy source, the partial shading is a main issue in the generating power. In literature, some of the methods are reviewed and it is not provided efficient results. This paper develops a design and analysis of the hybrid system with a DC-DC converter controlled by hybrid approach. This hybrid approach is a combination of Adaptive Neuro Fuzzy Interference System- Honey Badger Algorithm (ANFIS-HBA) for extracting maximum power and power compensation. The hybrid system is designed with PV and WT for compensating load demand in the grid side. The main objective of the proposed methodology is to extract the maximum power of the system (PV and WT). The proposed methodology is executed in the MATLAB and performances are evaluated with the performance metrices. The proposed method is achieved efficient results which concluded with the comparison analysis such as Adaptive Neuro Fuzzy Interference System -Genetic Algorithm (ANFIS-GA) and ANFIS- Particle Swarm Optimization (PSO) at various partial shading conditions. The proposed method is achieved the efficient maximum tracking in PV and WT systems under partial shading conditions.