Adaptive Maximum Power Point Tracking Using Improved Cuckoo Search for Solar Panels During Variable Sunlight and Shaded Conditions

Vivek Jain; Prateek Tiwari; Pramod Sharma

Abstract

India's government seeks to keep up with the country's quickly increasing energy needs, which are mostly satisfied by burning coal and oil. By 2030, 40% of the country's energy is expected to originate from renewable sources, according to official plans. By 2022, New Delhi hopes to generate 175 GW of renewable energy, primarily from solar and wind power, with a target of 100 gigawatts. Although India has very few renewable energy resources, the nation does have 230,000 kW of installed wind power and 450,000 kW of hydropower. The country's expansion ambitions largely rely on solar energy. Solar energy needs to be converted from DC to AC to meet grid or AC demand. An IGBT inverter transforms the DC voltage applied to the DC connector into a single-phase AC voltage. With this modulation approach, there are several pulses in each half cycle, and the width of the pulses varies according to the phase of the cycle in which the pulsing takes place. Only 30 to 40% of the energy generated by solar radiation can be produced by standard solar panels. Monitoring the peak power output of solar photovoltaic systems can help to improve their operational efficacy. The photovoltaic system may thus monitor entire power transfer while modifying the boost converter's duty cycle because it is linked to the source impedance. In the present study, a MATLAB circuit description for a diode-dependent photovoltaic system was constructed. In the present study, we have utilized particle swarm optimization to develop more sophisticated duty cycle optimization models. The enhanced cuckoo search-based optimization model includes both acceleration and velocity factor optimization. Early convergence can be prevented, and the global peak power point can be properly tracked. Many studies on grid-connected solar systems have led to the establishment of a prediction model for the evaluation of systems. The proposed solution exhibited a reduced transient and steady-state response when compared to conventional PowerPoint management approaches and existing soft computing technologies.

Abstract

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