(untitled) (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
The Indian government has set an ambitious goal of satisfying the country’s fast expanding demand, which is currently fulfilled primarily by coal and oil. By 2030, the government wants renewable energy to account for 40% of total energy generation. New Delhi is working hard to develop 175 GW (GW) of renewable energy by 2022, with an aim of 100 GW of solar power and 100 GW of wind power. Increasing environmental concerns, dwindling fuel supplies, and rising energy demands have shifted our focus to an idealistic future based solely on renewable and non-polluting energy supply technology. Photovoltaic (PV) power generation is becoming more popular in contrast to other renewable energy sources due to advantages such as ease of access, low cost, less environmental contamination, and lower maintenance costs. In this paper, different maximum power point tracking strategies based on particle swarm optimization and improved cuckoo search based optimization are employed to develop a solar PV system (MPPT). To validate the effectiveness of the proposed system, modelling and simulation using the MATLAB Simulink software are carried out. In the complex operating environment, a maximum point tracking system based on the cuckoo search algorithm has demonstrated promising results. Two partial shade patterns are used to analyse the model. We created partial shading conditions using the PV Array Block by giving distinct input radiation values for all four serial-connection modules. The optimization block generates the panel output, which is fed to the boost converter via its duty cycle output. The results reveal that if partial shading is possible, the optimization of the cuckoo search method produces better results than the methodology for perturbing, watching, and incremental behavior.