Design, implementation and empirical analysis of a cascaded hybrid MPPT controller for grid tied solar photovoltaic systems under partial shaded conditions

Abstract

Solar Photovoltaic (PV) system based power generation is going to become the major power source in the following few decades. Because of the advantages such as reliability, cleanliness, feasibility in small scale to medium scale power generation etc., Solar Photovoltaic (PV) based power generation is developing very rapidly. Hybrid MPPT control methods are essential to track and achieve maximum power generation from solar PV systems under normal and Partially Shaded Conditions (PSC). The proposed Hybrid Grey Wolf Optimization (GWO) algorithm with Adaptive Neuro-Fuzzy Inference System (ANFIS) will effectively tracks the Maximum Power Point when compared to the conventional hybrid MPPT methods. Luo converter is employed as DC-DC converter to convert the variable DC output from solar panel into a nominal DC level. The Luo converter output is given to a single phase Voltage Source Inverter (VSI) and the inverter is connected to grid. The Arithmetic Optimization Algorithm (AOA) tuned Fractional order Proportional Integral controller (FOPI) is adopted to maintain the stability of the grid connected inverter. The tracking efficiency of the proposed system is maintained around 98 % even under different irradiance conditions with very less convergence time of 0.016 s.

Keywords

• Adaptive neuro-fuzzy inference system (ANFIS)
• Arithmetic optimization algorithm (AOA)
• Fractional order proportional integral controller (FOPI)
• Grey wolf optimization (GWO)
• Partially shaded conditions (PSC)
• Photovoltaic (PV)